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https://api.github.com/repos/pandas-dev/pandas/issues/43823 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/43823/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/43823/comments | https://api.github.com/repos/pandas-dev/pandas/issues/43823/events | https://github.com/pandas-dev/pandas/pull/43823 | 1,012,624,323 | PR_kwDOAA0YD84shxbu | 43,823 | PERF: tolist | {
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} | 1 | "2021-09-30T21:04:24Z" | "2021-09-30T23:01:58Z" | "2021-09-30T22:57:57Z" | MEMBER | null | The parent class implementation is faster.
```
dti = pd.date_range("2016-01-01", periods=10**5, freq="S")
%timeit dti.tolist()
286 ms ± 3 ms per loop (mean ± std. dev. of 7 runs, 1 loop each) # <- master
62.8 ms ± 765 µs per loop (mean ± std. dev. of 7 runs, 10 loops each) # <- PR
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} | 2 | "2021-09-30T21:36:08Z" | "2021-10-01T18:25:00Z" | "2021-10-01T16:36:36Z" | MEMBER | null | Change summary:
- `numeric` -> `numeric_t`
- This replaces usages of `asof_t`
- `numeric` + `object` -> `numeric_object_t`
- This replaces usages of `algos_t`, `join_t`, `reshape_t`
- `i64 + u64 + f32 + f64` -> `iu_64_floating_t` (don't love this name, suggestions welcome)
- This replaces `groupby_t`
- `iu_64_floating_t` + `object` -> `iu_64_floating_obj_t`
- This replaces `rank_t` (which was renamed to `numeric_object_t` in #43789, so it replaces `numeric_object_t` in this pr)
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} | 2 | "2021-09-30T22:59:37Z" | "2021-10-01T02:06:45Z" | "2021-10-01T02:04:16Z" | MEMBER | null | - [ ] closes #xxxx
- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
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} | 2 | "2021-10-01T01:43:36Z" | "2021-10-01T14:14:49Z" | "2021-10-01T14:10:48Z" | MEMBER | null | - [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
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https://api.github.com/repos/pandas-dev/pandas/issues/43827 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/43827/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/43827/comments | https://api.github.com/repos/pandas-dev/pandas/issues/43827/events | https://github.com/pandas-dev/pandas/pull/43827 | 1,012,798,996 | PR_kwDOAA0YD84siSjt | 43,827 | REF: add indices prop to sparse | {
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} | 1 | "2021-10-01T02:04:43Z" | "2021-10-03T22:37:53Z" | "2021-10-03T22:28:26Z" | MEMBER | null | Future prs will use this more too, so figured adding it made sense
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https://api.github.com/repos/pandas-dev/pandas/issues/43828 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/43828/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/43828/comments | https://api.github.com/repos/pandas-dev/pandas/issues/43828/events | https://github.com/pandas-dev/pandas/pull/43828 | 1,012,812,597 | PR_kwDOAA0YD84siVDT | 43,828 | TYP: enable disallow_untyped_decorators | {
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} | 23 | "2021-10-01T02:29:35Z" | "2021-10-30T15:10:19Z" | "2021-10-30T15:10:04Z" | CONTRIBUTOR | null | - [ ] closes #33455, closes #41588, (closes #43388, closes #43387)
- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
Some of the many type errors unveiled by `cache_readonly` might be easily fixable. This PR simply ignores all the uncovered errors to quickly enable mypy's `disallow_untyped_decorators` to prevent future untyped decorators.
I enabled mypy's `disallow_untyped_decorators` but pyright's `reportUntypedFunctionDecorator` finds the following three functions that are not found by mypy, so I didn't enable `reportUntypedFunctionDecorator` (can't add ignore statements, otherwise mypy will complain about unused ignore statements, edit: using pyright's file-based ignore comments):
- pandas/conftest.py:1505
- ~~pandas/core/util/numba_.py:93~~
- pandas/core/window/numba_.py:244 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/43829 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/43829/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/43829/comments | https://api.github.com/repos/pandas-dev/pandas/issues/43829/events | https://github.com/pandas-dev/pandas/issues/43829 | 1,012,815,365 | I_kwDOAA0YD848XlYF | 43,829 | BUG: test_equals_various failing locally with incorrect name | {
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] | open | false | null | [] | null | 0 | "2021-10-01T02:35:33Z" | "2021-10-03T17:45:12Z" | null | MEMBER | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
pandas/tests/computation/test_eval.py test_equals_various has what looks like a kludge:
@pytest.mark.parametrize(
"other",
[
"'x'",
"...",
],
)
def test_equals_various(other):
df = DataFrame({"A": ["a", "b", "c"]})
result = df.eval(f"A == {other}")
expected = Series([False, False, False], name="A")
if USE_NUMEXPR:
# https://github.com/pandas-dev/pandas/issues/10239
# lose name with numexpr engine. Remove when that's fixed.
expected.name = None
tm.assert_series_equal(result, expected)
```
For a few weeks now this has been failing locally (both parameters) because `result.name == "A"`, i.e. what `expected` would have without the USE_NUMEXPR check.
I get this behavior when running a full (--skip-slow --skip-db) test run, but not when I run just this file or just this test.
```
### Issue Description
See above
### Expected Behavior
test_equals_various
### Installed Versions
```
INSTALLED VERSIONS
------------------
commit : ad4e091c19623608a2a016506167e6cbc1de46e4
python : 3.9.6.final.0
python-bits : 64
OS : Darwin
OS-release : 20.3.0
Version : Darwin Kernel Version 20.3.0: Thu Jan 21 00:07:06 PST 2021; root:xnu-7195.81.3~1/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.4.0.dev0+804.gad4e091c19.dirty
numpy : 1.21.1
pytz : 2021.1
dateutil : 2.8.1
pip : 21.2.4
setuptools : 57.0.0
Cython : 0.29.24
pytest : 6.2.5
hypothesis : 6.8.1
sphinx : 3.3.1
blosc : None
feather : None
xlsxwriter : 3.0.1
lxml.etree : 4.6.1
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.24.0
pandas_datareader: 0.9.0
bs4 : None
bottleneck : 1.3.2
fsspec : 0.8.5
fastparquet : 0.6.3
gcsfs : None
matplotlib : 3.4.2
numexpr : 2.7.3
odfpy : None
openpyxl : 3.0.7
pandas_gbq : None
pyarrow : 5.0.0
pyxlsb : None
s3fs : None
scipy : 1.6.3
sqlalchemy : 1.4.0
tables : 3.6.1
tabulate : 0.8.7
xarray : 0.16.1
xlrd : 2.0.1
xlwt : None
numba : 0.53.1
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https://api.github.com/repos/pandas-dev/pandas/issues/43830 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/43830/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/43830/comments | https://api.github.com/repos/pandas-dev/pandas/issues/43830/events | https://github.com/pandas-dev/pandas/pull/43830 | 1,012,979,774 | PR_kwDOAA0YD84si0O_ | 43,830 | ⬆️ UPGRADE: Autoupdate pre-commit config | {
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} | 0 | "2021-10-01T07:07:30Z" | "2021-10-01T08:58:24Z" | "2021-10-01T08:58:21Z" | CONTRIBUTOR | null | <!-- START pr-commits -->
<!-- END pr-commits -->
## Base PullRequest
default branch (https://github.com/pandas-dev/pandas/tree/master)
## Command results
<details>
<summary>Details: </summary>
<details>
<summary><em>add path</em></summary>
```Shell
/home/runner/work/_actions/technote-space/create-pr-action/v2/node_modules/npm-check-updates/bin
```
</details>
<details>
<summary><em>pip install pre-commit</em></summary>
```Shell
Collecting pre-commit
Downloading pre_commit-2.15.0-py2.py3-none-any.whl (191 kB)
Collecting pyyaml>=5.1
Downloading PyYAML-5.4.1-cp39-cp39-manylinux1_x86_64.whl (630 kB)
Collecting cfgv>=2.0.0
Downloading cfgv-3.3.1-py2.py3-none-any.whl (7.3 kB)
Collecting identify>=1.0.0
Downloading identify-2.2.15-py2.py3-none-any.whl (98 kB)
Collecting toml
Downloading toml-0.10.2-py2.py3-none-any.whl (16 kB)
Collecting virtualenv>=20.0.8
Downloading virtualenv-20.8.1-py2.py3-none-any.whl (5.3 MB)
Collecting nodeenv>=0.11.1
Downloading nodeenv-1.6.0-py2.py3-none-any.whl (21 kB)
Collecting six<2,>=1.9.0
Downloading six-1.16.0-py2.py3-none-any.whl (11 kB)
Collecting platformdirs<3,>=2
Downloading platformdirs-2.4.0-py3-none-any.whl (14 kB)
Collecting filelock<4,>=3.0.0
Downloading filelock-3.2.0-py2.py3-none-any.whl (10 kB)
Collecting backports.entry-points-selectable>=1.0.4
Downloading backports.entry_points_selectable-1.1.0-py2.py3-none-any.whl (6.2 kB)
Collecting distlib<1,>=0.3.1
Downloading distlib-0.3.3-py2.py3-none-any.whl (496 kB)
Installing collected packages: six, platformdirs, filelock, distlib, backports.entry-points-selectable, virtualenv, toml, pyyaml, nodeenv, identify, cfgv, pre-commit
Successfully installed backports.entry-points-selectable-1.1.0 cfgv-3.3.1 distlib-0.3.3 filelock-3.2.0 identify-2.2.15 nodeenv-1.6.0 platformdirs-2.4.0 pre-commit-2.15.0 pyyaml-5.4.1 six-1.16.0 toml-0.10.2 virtualenv-20.8.1
```
</details>
<details>
<summary><em>pre-commit autoupdate || (exit 0);</em></summary>
```Shell
Updating https://github.com/MarcoGorelli/absolufy-imports ... [INFO] Initializing environment for https://github.com/MarcoGorelli/absolufy-imports.
already up to date.
Updating https://github.com/python/black ... [INFO] Initializing environment for https://github.com/python/black.
updating 21.8b0 -> 21.9b0.
Updating https://github.com/codespell-project/codespell ... [INFO] Initializing environment for https://github.com/codespell-project/codespell.
already up to date.
Updating https://github.com/pre-commit/pre-commit-hooks ... [INFO] Initializing environment for https://github.com/pre-commit/pre-commit-hooks.
already up to date.
Updating https://github.com/cpplint/cpplint ... [INFO] Initializing environment for https://github.com/cpplint/cpplint.
already up to date.
Updating https://gitlab.com/pycqa/flake8 ... [INFO] Initializing environment for https://gitlab.com/pycqa/flake8.
already up to date.
Updating https://github.com/PyCQA/isort ... [INFO] Initializing environment for https://github.com/PyCQA/isort.
already up to date.
Updating https://github.com/asottile/pyupgrade ... [INFO] Initializing environment for https://github.com/asottile/pyupgrade.
updating v2.25.0 -> v2.29.0.
Updating https://github.com/pre-commit/pygrep-hooks ... [INFO] Initializing environment for https://github.com/pre-commit/pygrep-hooks.
already up to date.
Updating https://github.com/asottile/yesqa ... [INFO] Initializing environment for https://github.com/asottile/yesqa.
already up to date.
```
</details>
<details>
<summary><em>pre-commit run -a || (exit 0);</em></summary>
```Shell
[INFO] Initializing environment for https://gitlab.com/pycqa/flake8:flake8-bugbear==21.3.2,flake8-comprehensions==3.1.0,pandas-dev-flaker==0.2.0.
[INFO] Initializing environment for https://github.com/asottile/yesqa:flake8-bugbear==21.3.2,flake8-comprehensions==3.1.0,flake8==3.9.2,pandas-dev-flaker==0.2.0.
[INFO] Initializing environment for local:[email protected].
[INFO] Initializing environment for local:flake8-rst==0.7.0,flake8==3.7.9.
[INFO] Initializing environment for local:pyyaml,toml.
[INFO] Initializing environment for local:pyyaml.
[INFO] Initializing environment for local.
[INFO] Installing environment for https://github.com/MarcoGorelli/absolufy-imports.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
[INFO] Installing environment for https://github.com/python/black.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
[INFO] Installing environment for https://github.com/codespell-project/codespell.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
[INFO] Installing environment for https://github.com/pre-commit/pre-commit-hooks.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
[INFO] Installing environment for https://github.com/cpplint/cpplint.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
[INFO] Installing environment for https://gitlab.com/pycqa/flake8.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
[INFO] Installing environment for https://gitlab.com/pycqa/flake8.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
[INFO] Installing environment for https://github.com/PyCQA/isort.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
[INFO] Installing environment for https://github.com/asottile/pyupgrade.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
[INFO] Installing environment for https://github.com/asottile/yesqa.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
[INFO] Installing environment for local.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
[INFO] Installing environment for local.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
[INFO] Installing environment for local.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
[INFO] Installing environment for local.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
[INFO] Installing environment for local.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
absolufy-imports................................................................................................Passed
black...........................................................................................................Passed
codespell.......................................................................................................Passed
Debug Statements (Python).......................................................................................Passed
Fix End of Files................................................................................................Passed
Trim Trailing Whitespace........................................................................................Passed
cpplint.........................................................................................................Passed
flake8..........................................................................................................Passed
flake8 (cython).................................................................................................Passed
flake8 (cython template)........................................................................................Passed
isort...........................................................................................................Passed
pyupgrade.......................................................................................................Passed
rst ``code`` is two backticks...................................................................................Passed
rst directives end with two colons..............................................................................Passed
rst ``inline code`` next to normal text.........................................................................Passed
Strip unnecessary `# noqa`s.....................................................................................Passed
pyright.........................................................................................................Failed
- hook id: pyright
- exit code: 1
No configuration file found.
pyproject.toml file found at /home/runner/work/pandas/pandas.
Loading pyproject.toml file at /home/runner/work/pandas/pandas/pyproject.toml
Assuming Python platform Linux
stubPath /home/runner/work/pandas/pandas/typings is not a valid directory.
Searching for source files
Found 307 source files
/home/runner/work/pandas/pandas/pandas/core/base.py
/home/runner/work/pandas/pandas/pandas/core/base.py:1251:9 - error: Overload 2 for "searchsorted" will never be used because its parameters overlap overload 1 (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/common.py
/home/runner/work/pandas/pandas/pandas/core/common.py:398:5 - error: Overload 2 for "random_state" will never be used because its parameters overlap overload 1 (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/frame.py
/home/runner/work/pandas/pandas/pandas/core/frame.py:1370:9 - error: Overload 1 for "dot" overlaps overload 2 and returns an incompatible type (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/array_algos/take.py
/home/runner/work/pandas/pandas/pandas/core/array_algos/take.py:44:5 - error: Overload 2 for "take_nd" will never be used because its parameters overlap overload 1 (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/arrays/_mixins.py
/home/runner/work/pandas/pandas/pandas/core/arrays/_mixins.py:216:9 - error: Overload 2 for "__getitem__" will never be used because its parameters overlap overload 1 (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/arrays/base.py
/home/runner/work/pandas/pandas/pandas/core/arrays/base.py:309:9 - error: Overload 2 for "__getitem__" will never be used because its parameters overlap overload 1 (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/arrays/base.py:539:9 - error: Overload 2 for "astype" will never be used because its parameters overlap overload 1 (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/arrays/base.py:543:9 - error: Overload 3 for "astype" will never be used because its parameters overlap overload 1 (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/arrays/boolean.py
/home/runner/work/pandas/pandas/pandas/core/arrays/boolean.py:421:9 - error: Overload 2 for "astype" will never be used because its parameters overlap overload 1 (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/arrays/boolean.py:425:9 - error: Overload 3 for "astype" will never be used because its parameters overlap overload 1 (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/arrays/categorical.py
/home/runner/work/pandas/pandas/pandas/core/arrays/categorical.py:498:9 - error: Overload 2 for "astype" will never be used because its parameters overlap overload 1 (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/arrays/categorical.py:502:9 - error: Overload 3 for "astype" will never be used because its parameters overlap overload 1 (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/arrays/categorical.py:2031:9 - error: Overload 2 for "__getitem__" will never be used because its parameters overlap overload 1 (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/arrays/datetimelike.py
/home/runner/work/pandas/pandas/pandas/core/arrays/datetimelike.py:324:9 - error: Overload 2 for "__getitem__" will never be used because its parameters overlap overload 1 (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/arrays/datetimelike.py:320:9 - error: Overload 1 for "__getitem__" overlaps overload 2 and returns an incompatible type (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/arrays/floating.py
/home/runner/work/pandas/pandas/pandas/core/arrays/floating.py:286:9 - error: Overload 2 for "astype" will never be used because its parameters overlap overload 1 (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/arrays/floating.py:290:9 - error: Overload 3 for "astype" will never be used because its parameters overlap overload 1 (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/arrays/integer.py
/home/runner/work/pandas/pandas/pandas/core/arrays/integer.py:348:9 - error: Overload 2 for "astype" will never be used because its parameters overlap overload 1 (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/arrays/integer.py:352:9 - error: Overload 3 for "astype" will never be used because its parameters overlap overload 1 (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/arrays/interval.py
/home/runner/work/pandas/pandas/pandas/core/arrays/interval.py:649:9 - error: Overload 2 for "__getitem__" will never be used because its parameters overlap overload 1 (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/arrays/interval.py:645:9 - error: Overload 1 for "__getitem__" overlaps overload 2 and returns an incompatible type (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/arrays/masked.py
/home/runner/work/pandas/pandas/pandas/core/arrays/masked.py:152:9 - error: Overload 2 for "__getitem__" will never be used because its parameters overlap overload 1 (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/arrays/masked.py:323:9 - error: Overload 2 for "astype" will never be used because its parameters overlap overload 1 (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/arrays/masked.py:327:9 - error: Overload 3 for "astype" will never be used because its parameters overlap overload 1 (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/arrays/string_arrow.py
/home/runner/work/pandas/pandas/pandas/core/arrays/string_arrow.py:275:9 - error: Overload 2 for "__getitem__" will never be used because its parameters overlap overload 1 (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/arrays/string_arrow.py:271:9 - error: Overload 1 for "__getitem__" overlaps overload 2 and returns an incompatible type (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/arrays/sparse/array.py
/home/runner/work/pandas/pandas/pandas/core/arrays/sparse/array.py:867:9 - error: Overload 2 for "__getitem__" will never be used because its parameters overlap overload 1 (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/dtypes/cast.py
/home/runner/work/pandas/pandas/pandas/core/dtypes/cast.py:448:5 - error: Overload 2 for "ensure_dtype_can_hold_na" will never be used because its parameters overlap overload 1 (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/dtypes/cast.py:1068:5 - error: Overload 2 for "astype_nansafe" will never be used because its parameters overlap overload 1 (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/groupby/ops.py
/home/runner/work/pandas/pandas/pandas/core/groupby/ops.py:282:9 - error: Overload 2 for "_get_result_dtype" will never be used because its parameters overlap overload 1 (reportOverlappingOverload)
/home/runner/work/pandas/pandas/pandas/core/tools/datetimes.py
/home/runner/work/pandas/pandas/pandas/core/tools/datetimes.py:626:5 - error: Overload 1 for "to_datetime" overlaps overload 3 and returns an incompatible type (reportOverlappingOverload)
31 errors, 0 warnings, 0 infos
Completed in 27.79sec
flake8-rst......................................................................................................Passed
Unwanted patterns...............................................................................................Passed
Check Cython casting is `<type>obj`, not `<type> obj`...........................................................Passed
Check for backticks incorrectly rendering because of missing spaces.............................................Passed
Check for unnecessary random seeds in asv benchmarks............................................................Passed
Check for invalid EA testing....................................................................................Passed
Generate pip dependency from conda..............................................................................Passed
Check flake8 version is synced across flake8, yesqa, and environment.yml........................................Passed
Validate correct capitalization among titles in documentation...................................................Passed
Import pandas.array as pd_array in core.........................................................................Passed
Use bool_t instead of bool in pandas/core/generic.py............................................................Passed
Ensure pandas errors are documented in doc/source/reference/general_utility_functions.rst.......................Passed
```
</details>
</details>
## Changed files
<details>
<summary>Changed file: </summary>
- .pre-commit-config.yaml
</details>
<hr>
[:octocat: Repo](https://github.com/technote-space/create-pr-action) | [:memo: Issues](https://github.com/technote-space/create-pr-action/issues) | [:department_store: Marketplace](https://github.com/marketplace/actions/create-pr-action) | {
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} | 2 | "2021-10-01T10:26:39Z" | "2021-10-03T13:50:22Z" | "2021-10-03T13:50:22Z" | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [ ] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
d = {'a': [1, 2], 'b': {'b_1': 2, 'b_2': (3, 4)}}
r = pd.json_normalize(d, sep='__')
```
### Issue Description
When using a separator with more then 1 character, for example '__', the new column names get the separator as prefix, too. If you use a separator with only 1 character, for example '_', everything works fine.
I get the following output from the code provided:
> a __b__b_1 __b__b_2
> 0 [1, 2] 2 (3, 4)
### Expected Behavior
> a b__b_1 b__b_2
> 0 [1, 2] 2 (3, 4)
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 73c68257545b5f8530b7044f56647bd2db92e2ba
python : 3.9.6.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.18363
machine : AMD64
processor : Intel64 Family 6 Model 158 Stepping 9, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : de_DE.cp1252
pandas : 1.3.3
numpy : 1.21.1
pytz : 2021.1
dateutil : 2.8.2
pip : 21.2.4
setuptools : 49.6.0.post20210108
Cython : 0.29.24
pytest : 6.2.5
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.1
IPython : 7.26.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : 2021.07.0
fastparquet : None
gcsfs : None
matplotlib : 3.4.2
numexpr : 2.7.3
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 1.0.1
pyxlsb : None
s3fs : 0.4.2
scipy : 1.7.1
sqlalchemy : 1.3.23
tables : 3.6.1
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
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- [X] I have searched the [[pandas] tag](https://stackoverflow.com/questions/tagged/pandas) on StackOverflow for similar questions.
- [X] I have asked my usage related question on [StackOverflow](https://stackoverflow.com).
### Link to question on StackOverflow
https://stackoverflow.com/a/64335734
### Question about pandas
Currently, I'm using the following method to get rid of `Unnamed: 0` column in a pandas DataFrame according to the comments noted [here](https://stackoverflow.com/questions/36519086/how-to-get-rid-of-unnamed-0-column-in-a-pandas-dataframe/66704993#66704993) and [here](https://stackoverflow.com/questions/52297740/typeerror-bad-operand-type-for-unary-float):
```python
import pandas as pd
excel='2021-2022-1.xlsx'
dfs = pd.read_excel(excel)
dfs = dfs.loc[:, ~dfs.columns.str.contains('^Unnamed', na=False)]
```
But I am puzzled by the meaning of the `~` symbol used above. I try to find some relevant explanations by googling or digging into the source code of pandas, but still got nothing. Any hints for this question will be greatly appreciated.
Regards,
HZ | {
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https://api.github.com/repos/pandas-dev/pandas/issues/43833 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/43833/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/43833/comments | https://api.github.com/repos/pandas-dev/pandas/issues/43833/events | https://github.com/pandas-dev/pandas/pull/43833 | 1,013,412,095 | PR_kwDOAA0YD84skH2Z | 43,833 | update fix ignored sort in api.py and add test | {
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} | 7 | "2021-10-01T14:23:14Z" | "2021-10-10T17:28:34Z" | "2021-10-10T17:28:31Z" | MEMBER | null | - [x] closes #43375
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [x] whatsnew entry
As mentioned in the ticket, the function `api.union_indexes` does not handle the sort parameter. I added support for it, but we explicitly check that sort can only take the values `False` and `None` in [here](https://github.com/pandas-dev/pandas/blob/62d1f5c0fb16b6990aceabb8491d61de63cd042a/pandas/core/indexes/base.py#L2898) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/43835 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/43835/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/43835/comments | https://api.github.com/repos/pandas-dev/pandas/issues/43835/events | https://github.com/pandas-dev/pandas/issues/43835 | 1,013,426,105 | I_kwDOAA0YD848Z6e5 | 43,835 | ENH: rolling() for discontinuous time series data | {
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] | closed | false | null | [] | null | 5 | "2021-10-01T14:36:28Z" | "2021-10-13T17:27:59Z" | "2021-10-13T17:27:59Z" | NONE | null | Here is a discontinued time series data
|DATE|VALUE|
|----|----|
|2020-01-01|1|
|2020-01-02|1|
|2020-01-05|1|
|2020-01-06|1|
when I use rolling function
`
df.rolling(2, on='A', min_periods=2).sum()
`
OUTPUT is
|DATE|VALUE|
|----|----|
|2020-01-01|NaN|
|2020-01-02|2|
|2020-01-05|2|
|2020-01-06|2|
However, I expect the result as follows:
|DATE|VALUE|
|----|----|
|2020-01-01|NaN|
|2020-01-02|2|
|2020-01-05|NaN|
|2020-01-06|2|
It would be appreciated that the feature can be add in next update.
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https://api.github.com/repos/pandas-dev/pandas/issues/43836 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/43836/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/43836/comments | https://api.github.com/repos/pandas-dev/pandas/issues/43836/events | https://github.com/pandas-dev/pandas/issues/43836 | 1,013,446,442 | I_kwDOAA0YD848Z_cq | 43,836 | ENH: Should `pandas.CategoricalDtype` use `pandas.NA` as the sentinel value instead of `float('nan')` ? | {
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] | open | false | null | [] | null | 0 | "2021-10-01T14:56:09Z" | "2021-10-02T00:50:02Z" | null | NONE | null | Almost all of the the new nullable data types (which are incredibly useful btw.) seem to use `pd.NA` as the null-value.
However, I noticed that `pandas.CategoricalDtype` still uses `float('nan')`, which I suppose is for historical reasons.
Are there any plans - for the sake of consistency - to switch `CategoricalDtype`'s sentinel value to `pandas.NA` in the future? | {
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] | open | false | null | [] | null | 7 | "2021-10-01T16:58:51Z" | "2021-10-02T20:48:57Z" | null | NONE | null | Currently, [`DataFrame.astype(dtype: dict)`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.astype.html) requires that the `dict` keys are a subset of the `DataFrame`'s columns. This feels like an unnecessary restriction, in my opinion it would suffice / be more intuitive if it would roughly perform:
```python
for col in df.columns:
if col in dtype:
df[col] = df.col.astype(dtype[col])
```
The fact that this currently raises an error becomes annoying, for example if one needs to repair data types after they became destroyed by a stacking operation - one needs to slice the `dtype`-dictionary by the column keys every time!
Of course, a strong argument can be made that raising an error is a good idea to prevent users from erroneously believing the type-casting was performed in the case when a key was miss-typed.
#### Describe the solution you'd like
I propose the following changes:
1. If `df.columns` is a subset of `dtype`, do not raise an error if superfluous keys are present
- In this case all columns are identified and there is a negligible chance that there is an error due to a typo.
2. Extent the functionality of the already present `errors='ignore'` option to also ignore superfluous keys in the `dtype`-dictionary.
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https://api.github.com/repos/pandas-dev/pandas/issues/43838 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/43838/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/43838/comments | https://api.github.com/repos/pandas-dev/pandas/issues/43838/events | https://github.com/pandas-dev/pandas/issues/43838 | 1,013,609,740 | I_kwDOAA0YD848anUM | 43,838 | BUG: Named aggregations do not work together with unnamed ones | {
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] | open | false | null | [] | null | 2 | "2021-10-01T17:42:45Z" | "2021-10-03T16:38:39Z" | null | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
import numpy as np
groupbyObj = pd.DataFrame({"A": [1, 2, 3], "B": [10, 5, 1], "C": ["x", "x", "y"]}).groupby("C")
methods = {
"A": np.mean,
"NewName": pd.NamedAgg(column='B', aggfunc='max')
}
# now regardless if you pass it as a dict...
groupbyObj.agg(methods)
# ... or as keyword arguments, it fails
groupbyObj.agg(**methods)
```
### Issue Description
There seems to be no way to include both the unnamed and named aggregations as (an) argument(s) in the same groupby `agg`. It might be convenient and useful to name just a few specific aggregations rather than all or none of them. Currently, pandas behaviour leads to either a `KeyError: "Column(s) ['NewName'] do not exist"` or a `TypeError: Must provide 'func' or tuples of '(column, aggfunc).`
### Expected Behavior
Ideally, running
```
groupbyObj.agg(**methods)
```
would work instead of leading to an error.
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : f00ed8f47020034e752baf0250483053340971b0
python : 3.9.6.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19042
machine : AMD64
processor : Intel64 Family 6 Model 140 Stepping 1, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : Polish_Poland.1250
pandas : 1.3.0
numpy : 1.21.0
pytz : 2021.1
dateutil : 2.8.1
pip : 21.2.1
setuptools : 56.0.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.1
IPython : 7.25.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.4.2
numexpr : None
odfpy : None
openpyxl : 3.0.7
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.7.1
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
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} | 3 | "2021-10-01T17:56:44Z" | "2021-10-04T15:55:49Z" | null | NONE | null | ###
- [X] I have checked that the issue still exists on the latest versions of the docs on `master` [here](https://pandas.pydata.org/docs/dev/)
### Location of the documentation
https://pandas.pydata.org/docs/dev/reference/api/pandas.DataFrame.groupby.html
### Documentation problem
The reference for `DataFrame.groupby` is absent of any reference to [iterating through groups](https://pandas.pydata.org/pandas-docs/dev/user_guide/groupby.html#iterating-through-groups), which seems like a fairly critical piece of information (I ended up brewing my own solution, before eventually finding the user guide link). A link to the user guide is included, but it's easy to miss.
### Suggested fix for documentation
The documentation could be improved by including some suggestions of what one might find in the user guide. For example, the text "See the user guide for more." could be replaced with something like the following:
> See the user guide for detailed usage and examples, including splitting an object into groups, iterating through groups, selecting a group, aggregation, and more. | {
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] | open | false | null | [] | null | 4 | "2021-10-01T18:39:06Z" | "2021-11-17T16:28:46Z" | null | MEMBER | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
N/A
```
### Issue Description
cc @jorisvandenbossche unless I'm missing something? ive misunderstood the design/behavior of EA.argsort in the past.
### Expected Behavior
NA
### Installed Versions
<details>
Replace this line with the output of pd.show_versions()
</details>
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- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [ ] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
x = pd.DataFrame({'a': [1,2]})
x = x.query('a.isna()')
```
### Issue Description
The code above produces the following error. This is in being run in a fresh (nothing else) conda environment with only python3.7 and pandas 1.3.3 installed.
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/project_folder/env/lib/python3.7/site-packages/pandas/core/frame.py", line 4060, in query
res = self.eval(expr, **kwargs)
File "/project_folder/env/lib/python3.7/site-packages/pandas/core/frame.py", line 4191, in eval
return _eval(expr, inplace=inplace, **kwargs)
File "/project_folder/env/lib/python3.7/site-packages/pandas/core/computation/eval.py", line 353, in eval
ret = eng_inst.evaluate()
File "/project_folder/env/lib/python3.7/site-packages/pandas/core/computation/engines.py", line 80, in evaluate
res = self._evaluate()
File "/project_folder/env/lib/python3.7/site-packages/pandas/core/computation/engines.py", line 120, in _evaluate
_check_ne_builtin_clash(self.expr)
File "/project_folder/env/lib/python3.7/site-packages/pandas/core/computation/engines.py", line 36, in _check_ne_builtin_clash
names = expr.names
File "/project_folder/env/lib/python3.7/site-packages/pandas/core/computation/expr.py", line 833, in names
return frozenset([self.terms.name])
TypeError: unhashable type: 'Series'
### Expected Behavior
Did not expect an error. Pretty sure this used to work, but now it does not. Considering that this happening in a fresh conda environment, not sure what in my setup could be causing this.
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 73c68257545b5f8530b7044f56647bd2db92e2ba
python : 3.7.0.final.0
python-bits : 64
OS : Darwin
OS-release : 19.6.0
Version : Darwin Kernel Version 19.6.0: Thu Sep 16 20:58:47 PDT 2021; root:xnu-6153.141.40.1~1/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.3.3
numpy : 1.20.3
pytz : 2021.1
dateutil : 2.8.2
pip : 21.2.2
setuptools : 58.0.4
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : 1.3.2
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : 2.7.3
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
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- [X] tests added / passed
- [X] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
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} | 2 | "2021-10-01T20:41:13Z" | "2021-10-05T06:26:02Z" | "2021-10-05T00:32:37Z" | CONTRIBUTOR | null | Fixes #27937. As described in that issue, assigning a mixture of NaN and
Interval values into a slice of a categorical-typed series would raise
an exception. This is no longer the case.
- [x] closes #27937
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
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Moves `abs` to be adjacent to `__abs__`. | {
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} | 1 | "2021-10-02T03:21:00Z" | "2021-10-03T17:21:48Z" | "2021-10-03T13:49:10Z" | MEMBER | null | - [ ] closes #42026
- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
Testing a change out to see if it fixes it. Not sure if this is a bug on our side our on fsspec side.
It seems the change is that fastparquet apends a slash in front of paths now.
cc @martindurant | {
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} | 1 | "2021-10-02T09:06:18Z" | "2021-10-03T14:44:12Z" | "2021-10-03T14:12:55Z" | CONTRIBUTOR | null | - [x] closes #40661
- [x] tests added / passed
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Added a test for the cut method which uses Timestamp tuples as labels. Using cut with such labels raised error in v1.2.3 as reported in the issue, but it runs correctly after v1.3.0. | {
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} | 1 | "2021-10-02T10:05:15Z" | "2021-10-03T13:50:24Z" | "2021-10-03T13:50:22Z" | CONTRIBUTOR | null | - [x] closes #43831
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
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- [ ] closes #xxxx
- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
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} | 3 | "2021-10-02T14:21:51Z" | "2021-10-31T21:41:30Z" | "2021-10-29T21:19:43Z" | CONTRIBUTOR | null | This might be controversial. The setter allows any `Mapping` but the getter returns a `dict`.
[reportPropertyTypeMismatch](https://github.com/microsoft/pyright/blob/main/docs/configuration.md):
> [...] type of the value passed to the setter is not assignable to the value returned by the getter. Such mismatches violate the intended use of properties, which are meant to act like variables. The default value for this setting is 'error'. | {
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} | 4 | "2021-10-02T16:46:40Z" | "2021-10-03T13:53:06Z" | "2021-10-03T13:52:20Z" | MEMBER | null | - [x] closes #43386
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [x] whatsnew entry
The regression is caused by the groupby paths requiring the data to be sorted by groups.
cc @mroeschke and @simonjayhawkins | {
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} | 6 | "2021-10-02T18:46:56Z" | "2021-11-14T16:38:12Z" | "2021-11-14T16:38:06Z" | CONTRIBUTOR | null | Towards #41610
This doesn't help with any ignore statements, as `Buffer` is defined as `Buffer = Union[IO[AnyStr], RawIOBase, BufferedIOBase, TextIOBase, TextIOWrapper, mmap]`: `IO[AnyStr]` will be replaced with `IO[str]` or `IO[bytes]`.
btw., `Buffer` is a "bad" union as it contains one generic and many actual types (I think, I'm the one to blame for that). It is often used without an actual type (`Buffer` instead of `Buffer[str]` or `Buffer[bytes]`). | {
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} | 2 | "2021-10-03T04:50:04Z" | "2021-10-03T19:12:52Z" | "2021-10-03T18:47:04Z" | MEMBER | null | Refactored out of a branch that implements `Index.__array_ufunc__` | {
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Is it possible to set pandas dtype-like to index.dtype
**Pandas Dtypes Examples**
```python
pandas.Int64Dtype(), pandas.Int8Dtype()
```
**Expected result**
```python
df.index = pd.Series(df['X'].astype('Int64'))
Index([1, 2, 3, 4, 5], dtype='Int64', name='X')
# instead of
Index([1, 2, 3, 4, 5], dtype='object', name='X')
```
**Workaround**
Im forcing change in dtype convertion (it expects to have not nullable values)
```python
INDEX_TYPE_MAP = {
pandas.Int8Dtype(): numpy.int8,
pandas.Int16Dtype(): numpy.int16,
pandas.Int32Dtype(): numpy.int32,
pandas.Int64Dtype(): numpy.int64,
pandas.Float32Dtype(): numpy.float32,
pandas.Float64Dtype(): numpy.float64
}
```
Br
Nicolas | {
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"labels_url": "https://api.github.com/repos/pandas-dev/pandas/milestones/33/labels",
"node_id": "MDk6TWlsZXN0b25lOTk3NTQ0",
"number": 33,
"open_issues": 11,
"state": "open",
"title": "No action",
"updated_at": "2021-11-19T17:33:16Z",
"url": "https://api.github.com/repos/pandas-dev/pandas/milestones/33"
} | 4 | "2021-10-03T13:41:23Z" | "2021-10-07T03:00:49Z" | "2021-10-07T03:00:05Z" | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [ ] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
for serial_num in range(0,10)
file = f'gs://harry-airflow-dev/userprofile/user_game_label/dt=20210922/file- {serial_num}.parquet'
df = pd.read_parquet(file)
```
### Issue Description
[2021-10-03 01:00:41,553] {core.py:344} DEBUG - GET: b/{}/o/{}, ('harry-airflow-dev', 'userprofile/user_game_label/dt=20210922/file-000000000000.parquet'), None
[2021-10-03 01:00:41,601] {core.py:344} DEBUG - GET: b/{}/o/{}, ('harry-airflow-dev', 'userprofile/user_game_label/dt=20210922/file-000000000000.parquet'), None
[2021-10-03 01:00:41,627] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12613865 - 12679401
[2021-10-03 01:00:41,627] {core.py:344} DEBUG - GET: https://storage.googleapis.com/download/storage/v1/b/harry-airflow-dev/o/userprofile%2Fuser_game_label%2Fdt=20210922%2Ffile-000000000000.parquet?generation=1633194033609120&alt=media, (), {'Range': 'bytes=12613865-12679400'}
[2021-10-03 01:00:41,712] {core.py:344} DEBUG - GET: b/{}/o/{}, ('harry-airflow-dev', 'userprofile/user_game_label/dt=20210922/file-000000000000.parquet'), None
[2021-10-03 01:00:41,730] {core.py:344} DEBUG - GET: b/{}/o/{}, ('harry-airflow-dev', 'userprofile/user_game_label/dt=20210922/file-000000000000.parquet'), None
[2021-10-03 01:00:41,758] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12613865 - 12679401
[2021-10-03 01:00:41,759] {core.py:344} DEBUG - GET: https://storage.googleapis.com/download/storage/v1/b/harry-airflow-dev/o/userprofile%2Fuser_game_label%2Fdt=20210922%2Ffile-000000000000.parquet?generation=1633194033609120&alt=media, (), {'Range': 'bytes=12613865-12679400'}
[2021-10-03 01:00:41,838] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 4 - 213
[2021-10-03 01:00:41,839] {core.py:344} DEBUG - GET: https://storage.googleapis.com/download/storage/v1/b/harry-airflow-dev/o/userprofile%2Fuser_game_label%2Fdt=20210922%2Ffile-000000000000.parquet?generation=1633194033609120&alt=media, (), {'Range': 'bytes=4-5243092'}
[2021-10-03 01:00:41,913] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 284 - 93784
[2021-10-03 01:00:41,913] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 93870 - 205260
[2021-10-03 01:00:41,913] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 205367 - 234605
[2021-10-03 01:00:41,914] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 234769 - 346159
[2021-10-03 01:00:41,914] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 346269 - 375762
[2021-10-03 01:00:41,914] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 375929 - 487319
[2021-10-03 01:00:41,914] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 487430 - 517342
[2021-10-03 01:00:41,914] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 517510 - 628900
[2021-10-03 01:00:41,914] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 629015 - 659708
[2021-10-03 01:00:41,914] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 659880 - 660075
[2021-10-03 01:00:41,914] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 660221 - 660307
[2021-10-03 01:00:41,914] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 660388 - 660829
[2021-10-03 01:00:41,915] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 660978 - 661144
[2021-10-03 01:00:41,915] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 661228 - 661828
[2021-10-03 01:00:41,915] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 661978 - 662212
[2021-10-03 01:00:41,915] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 662297 - 663105
[2021-10-03 01:00:41,915] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 663259 - 663589
[2021-10-03 01:00:41,915] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 663678 - 663854
[2021-10-03 01:00:41,915] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 663964 - 664182
[2021-10-03 01:00:41,915] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 664293 - 664592
[2021-10-03 01:00:41,915] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 664707 - 665039
[2021-10-03 01:00:41,915] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 665123 - 665261
[2021-10-03 01:00:41,915] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 665376 - 776766
[2021-10-03 01:00:41,915] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 776870 - 806108
[2021-10-03 01:00:41,916] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 806269 - 917659
[2021-10-03 01:00:41,916] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 917771 - 947009
[2021-10-03 01:00:41,916] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 947178 - 947429
[2021-10-03 01:00:41,916] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 947547 - 1058937
[2021-10-03 01:00:41,916] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 1059045 - 1088538
[2021-10-03 01:00:41,916] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 1088705 - 1200095
[2021-10-03 01:00:41,916] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 1200213 - 1229682
[2021-10-03 01:00:41,916] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 1229857 - 1230217
[2021-10-03 01:00:41,916] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 1230339 - 1341729
[2021-10-03 01:00:41,917] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 1341840 - 1371697
[2021-10-03 01:00:41,917] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 1371865 - 1483255
[2021-10-03 01:00:41,917] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 1483374 - 1513174
[2021-10-03 01:00:41,917] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 1513350 - 1513805
[2021-10-03 01:00:41,917] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 1513931 - 1625321
[2021-10-03 01:00:41,917] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 1625436 - 1656000
[2021-10-03 01:00:41,917] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 1656172 - 1767562
[2021-10-03 01:00:41,917] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 1767685 - 1798196
[2021-10-03 01:00:41,918] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 1798376 - 1798471
[2021-10-03 01:00:41,918] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 1798586 - 1909976
[2021-10-03 01:00:41,918] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 1910080 - 1939229
[2021-10-03 01:00:41,918] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 1939390 - 2050780
[2021-10-03 01:00:41,918] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 2050892 - 2080041
[2021-10-03 01:00:41,918] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 2080210 - 2080305
[2021-10-03 01:00:41,918] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 2080423 - 2191813
[2021-10-03 01:00:41,918] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 2191920 - 2221069
[2021-10-03 01:00:41,918] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 2221233 - 2332623
[2021-10-03 01:00:41,919] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 2332738 - 2361887
[2021-10-03 01:00:41,919] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 2362059 - 2362154
[2021-10-03 01:00:41,919] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 2362273 - 2473663
[2021-10-03 01:00:41,919] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 2473771 - 2502920
[2021-10-03 01:00:41,919] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 2503085 - 2614475
[2021-10-03 01:00:41,919] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 2614591 - 2643740
[2021-10-03 01:00:41,919] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 2643913 - 2644008
[2021-10-03 01:00:41,919] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 2644131 - 2755521
[2021-10-03 01:00:41,919] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 2755633 - 2784782
[2021-10-03 01:00:41,919] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 2784951 - 2896341
[2021-10-03 01:00:41,920] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 2896461 - 2925610
[2021-10-03 01:00:41,920] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 2925787 - 2925882
[2021-10-03 01:00:41,920] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 2925997 - 3037387
[2021-10-03 01:00:41,920] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 3037491 - 3066640
[2021-10-03 01:00:41,920] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 3066801 - 3178191
[2021-10-03 01:00:41,920] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 3178303 - 3207452
[2021-10-03 01:00:41,920] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 3207621 - 3207716
[2021-10-03 01:00:41,920] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 3207834 - 3319224
[2021-10-03 01:00:41,920] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 3319331 - 3348480
[2021-10-03 01:00:41,921] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 3348644 - 3460034
[2021-10-03 01:00:41,921] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 3460149 - 3489298
[2021-10-03 01:00:41,921] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 3489470 - 3489565
[2021-10-03 01:00:41,921] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 3489684 - 3601074
[2021-10-03 01:00:41,921] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 3601182 - 3630331
[2021-10-03 01:00:41,921] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 3630496 - 3741886
[2021-10-03 01:00:41,921] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 3742002 - 3771151
[2021-10-03 01:00:41,921] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 3771324 - 3771419
[2021-10-03 01:00:41,921] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 3771542 - 3882932
[2021-10-03 01:00:41,922] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 3883044 - 3912193
[2021-10-03 01:00:41,922] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 3912362 - 4023752
[2021-10-03 01:00:41,922] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 4023872 - 4053021
[2021-10-03 01:00:41,922] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 4053198 - 4053293
[2021-10-03 01:00:41,922] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 4053408 - 4164798
[2021-10-03 01:00:41,922] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 4164902 - 4194051
[2021-10-03 01:00:41,922] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 4194212 - 4305602
[2021-10-03 01:00:41,922] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 4305714 - 4334863
[2021-10-03 01:00:41,922] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 4335032 - 4335127
[2021-10-03 01:00:41,923] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 4335245 - 4446635
[2021-10-03 01:00:41,923] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 4446742 - 4475891
[2021-10-03 01:00:41,923] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 4476055 - 4587445
[2021-10-03 01:00:41,923] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 4587560 - 4616709
[2021-10-03 01:00:41,923] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 4616881 - 4616989
[2021-10-03 01:00:41,923] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 4617108 - 4728498
[2021-10-03 01:00:41,923] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 4728606 - 4757776
[2021-10-03 01:00:41,923] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 4757941 - 4869331
[2021-10-03 01:00:41,923] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 4869447 - 4898617
[2021-10-03 01:00:41,924] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 4898790 - 4898912
[2021-10-03 01:00:41,924] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 4899035 - 5010425
[2021-10-03 01:00:41,924] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 5010537 - 5039730
[2021-10-03 01:00:41,924] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 5039899 - 5151289
[2021-10-03 01:00:41,924] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 5151409 - 5180579
[2021-10-03 01:00:41,924] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 5180756 - 5180851
[2021-10-03 01:00:41,924] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 5180971 - 5292361
[2021-10-03 01:00:41,925] {core.py:344} DEBUG - GET: https://storage.googleapis.com/download/storage/v1/b/harry-airflow-dev/o/userprofile%2Fuser_game_label%2Fdt=20210922%2Ffile-000000000000.parquet?generation=1633194033609120&alt=media, (), {'Range': 'bytes=5243093-10535240'}
[2021-10-03 01:00:42,008] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 5292470 - 5321619
[2021-10-03 01:00:42,008] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 5321785 - 5433175
[2021-10-03 01:00:42,008] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 5433292 - 5462441
[2021-10-03 01:00:42,008] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 5462615 - 5462710
[2021-10-03 01:00:42,008] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 5462833 - 5574223
[2021-10-03 01:00:42,009] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 5574335 - 5603484
[2021-10-03 01:00:42,009] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 5603653 - 5715043
[2021-10-03 01:00:42,009] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 5715163 - 5744312
[2021-10-03 01:00:42,009] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 5744489 - 5744597
[2021-10-03 01:00:42,009] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 5744721 - 5856111
[2021-10-03 01:00:42,009] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 5856224 - 5885394
[2021-10-03 01:00:42,009] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 5885564 - 5996954
[2021-10-03 01:00:42,009] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 5997075 - 6026224
[2021-10-03 01:00:42,009] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 6026402 - 6026573
[2021-10-03 01:00:42,010] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 6026701 - 6138091
[2021-10-03 01:00:42,010] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 6138208 - 6167584
[2021-10-03 01:00:42,010] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 6167758 - 6279148
[2021-10-03 01:00:42,010] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 6279273 - 6308550
[2021-10-03 01:00:42,010] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 6308732 - 6308827
[2021-10-03 01:00:42,010] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 6308942 - 6420332
[2021-10-03 01:00:42,010] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 6420436 - 6449585
[2021-10-03 01:00:42,010] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 6449746 - 6561136
[2021-10-03 01:00:42,010] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 6561248 - 6590397
[2021-10-03 01:00:42,011] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 6590566 - 6590661
[2021-10-03 01:00:42,011] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 6590779 - 6702169
[2021-10-03 01:00:42,011] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 6702276 - 6731425
[2021-10-03 01:00:42,011] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 6731589 - 6842979
[2021-10-03 01:00:42,011] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 6843094 - 6872243
[2021-10-03 01:00:42,011] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 6872415 - 6872510
[2021-10-03 01:00:42,011] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 6872629 - 6984019
[2021-10-03 01:00:42,011] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 6984127 - 7013276
[2021-10-03 01:00:42,011] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 7013441 - 7124831
[2021-10-03 01:00:42,012] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 7124947 - 7154096
[2021-10-03 01:00:42,012] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 7154269 - 7154364
[2021-10-03 01:00:42,012] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 7154487 - 7265877
[2021-10-03 01:00:42,012] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 7265989 - 7295138
[2021-10-03 01:00:42,012] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 7295307 - 7406697
[2021-10-03 01:00:42,012] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 7406817 - 7435966
[2021-10-03 01:00:42,012] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 7436143 - 7436238
[2021-10-03 01:00:42,012] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 7436354 - 7547744
[2021-10-03 01:00:42,013] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 7547849 - 7576998
[2021-10-03 01:00:42,013] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 7577160 - 7688550
[2021-10-03 01:00:42,013] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 7688663 - 7717812
[2021-10-03 01:00:42,013] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 7717982 - 7718077
[2021-10-03 01:00:42,013] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 7718196 - 7829586
[2021-10-03 01:00:42,013] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 7829694 - 7858843
[2021-10-03 01:00:42,013] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 7859008 - 7970398
[2021-10-03 01:00:42,013] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 7970514 - 7999663
[2021-10-03 01:00:42,013] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 7999836 - 7999931
[2021-10-03 01:00:42,013] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 8000051 - 8111441
[2021-10-03 01:00:42,014] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 8111550 - 8140699
[2021-10-03 01:00:42,014] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 8140865 - 8252255
[2021-10-03 01:00:42,014] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 8252372 - 8281521
[2021-10-03 01:00:42,014] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 8281695 - 8281790
[2021-10-03 01:00:42,014] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 8281914 - 8393304
[2021-10-03 01:00:42,014] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 8393417 - 8422566
[2021-10-03 01:00:42,014] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 8422736 - 8534126
[2021-10-03 01:00:42,014] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 8534247 - 8563396
[2021-10-03 01:00:42,015] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 8563574 - 8563669
[2021-10-03 01:00:42,015] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 8563785 - 8675175
[2021-10-03 01:00:42,015] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 8675280 - 8704429
[2021-10-03 01:00:42,015] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 8704591 - 8815981
[2021-10-03 01:00:42,015] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 8816094 - 8845243
[2021-10-03 01:00:42,015] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 8845413 - 8845508
[2021-10-03 01:00:42,015] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 8845627 - 8957017
[2021-10-03 01:00:42,015] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 8957125 - 8986274
[2021-10-03 01:00:42,015] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 8986439 - 9097829
[2021-10-03 01:00:42,016] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 9097945 - 9127094
[2021-10-03 01:00:42,016] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 9127267 - 9127362
[2021-10-03 01:00:42,016] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 9127482 - 9238872
[2021-10-03 01:00:42,016] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 9238981 - 9268130
[2021-10-03 01:00:42,016] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 9268296 - 9379686
[2021-10-03 01:00:42,016] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 9379803 - 9408952
[2021-10-03 01:00:42,016] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 9409126 - 9409221
[2021-10-03 01:00:42,016] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 9409345 - 9520735
[2021-10-03 01:00:42,016] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 9520848 - 9549997
[2021-10-03 01:00:42,017] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 9550167 - 9661557
[2021-10-03 01:00:42,017] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 9661678 - 9690827
[2021-10-03 01:00:42,017] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 9691005 - 9691100
[2021-10-03 01:00:42,017] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 9691215 - 9802605
[2021-10-03 01:00:42,017] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 9802709 - 9831858
[2021-10-03 01:00:42,017] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 9832019 - 9943409
[2021-10-03 01:00:42,017] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 9943521 - 9972670
[2021-10-03 01:00:42,017] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 9972839 - 9972934
[2021-10-03 01:00:42,017] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 9973052 - 10084442
[2021-10-03 01:00:42,018] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10084549 - 10113698
[2021-10-03 01:00:42,018] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10113862 - 10225252
[2021-10-03 01:00:42,018] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10225367 - 10254516
[2021-10-03 01:00:42,018] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10254688 - 10254783
[2021-10-03 01:00:42,018] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10254902 - 10366292
[2021-10-03 01:00:42,018] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10366400 - 10395549
[2021-10-03 01:00:42,018] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10395714 - 10507104
[2021-10-03 01:00:42,018] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10507220 - 10536369
[2021-10-03 01:00:42,019] {core.py:344} DEBUG - GET: https://storage.googleapis.com/download/storage/v1/b/harry-airflow-dev/o/userprofile%2Fuser_game_label%2Fdt=20210922%2Ffile-000000000000.parquet?generation=1633194033609120&alt=media, (), {'Range': 'bytes=10535241-12679400'}
[2021-10-03 01:00:42,083] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10536542 - 10536637
[2021-10-03 01:00:42,083] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10536760 - 10648150
[2021-10-03 01:00:42,083] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10648262 - 10677411
[2021-10-03 01:00:42,083] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10677580 - 10788970
[2021-10-03 01:00:42,083] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10789090 - 10818239
[2021-10-03 01:00:42,084] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10818416 - 10818491
[2021-10-03 01:00:42,084] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10818577 - 10818672
[2021-10-03 01:00:42,962] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10818774 - 10818838
[2021-10-03 01:00:42,962] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10818917 - 10833542
[2021-10-03 01:00:42,963] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10833632 - 10851809
[2021-10-03 01:00:42,963] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10851919 - 10856767
[2021-10-03 01:00:42,963] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10856932 - 10875109
[2021-10-03 01:00:42,963] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10875222 - 10880070
[2021-10-03 01:00:42,963] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10880238 - 10898415
[2021-10-03 01:00:42,963] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10898529 - 10903377
[2021-10-03 01:00:42,963] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10903546 - 10921723
[2021-10-03 01:00:42,963] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10921841 - 10926689
[2021-10-03 01:00:42,963] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10926862 - 10926907
[2021-10-03 01:00:42,963] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10926982 - 10927043
[2021-10-03 01:00:42,963] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10927126 - 10927171
[2021-10-03 01:00:42,963] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10927249 - 10927310
[2021-10-03 01:00:42,963] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10927396 - 10927441
[2021-10-03 01:00:42,963] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10927520 - 10927581
[2021-10-03 01:00:42,963] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10927668 - 10927713
[2021-10-03 01:00:42,963] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10927796 - 10927857
[2021-10-03 01:00:42,964] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10927948 - 10928043
[2021-10-03 01:00:42,964] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10928156 - 10928251
[2021-10-03 01:00:42,964] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10928365 - 10928460
[2021-10-03 01:00:42,964] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10928578 - 10928623
[2021-10-03 01:00:42,964] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10928684 - 10928779
[2021-10-03 01:00:42,964] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10928897 - 10947074
[2021-10-03 01:00:42,964] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10947181 - 10952029
[2021-10-03 01:00:42,964] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10952191 - 10970368
[2021-10-03 01:00:42,964] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10970483 - 10975331
[2021-10-03 01:00:42,964] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10975501 - 10975596
[2021-10-03 01:00:42,964] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10975717 - 10993894
[2021-10-03 01:00:42,964] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10994004 - 10998852
[2021-10-03 01:00:42,964] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 10999017 - 11017194
[2021-10-03 01:00:42,964] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11017312 - 11022160
[2021-10-03 01:00:42,964] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11022333 - 11022428
[2021-10-03 01:00:42,964] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11022550 - 11040727
[2021-10-03 01:00:42,965] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11040838 - 11045686
[2021-10-03 01:00:42,965] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11045852 - 11064029
[2021-10-03 01:00:42,965] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11064148 - 11068996
[2021-10-03 01:00:42,965] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11069170 - 11069265
[2021-10-03 01:00:42,965] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11069391 - 11087568
[2021-10-03 01:00:42,965] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11087683 - 11092531
[2021-10-03 01:00:42,965] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11092701 - 11110878
[2021-10-03 01:00:42,965] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11111001 - 11115849
[2021-10-03 01:00:42,965] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11116027 - 11116122
[2021-10-03 01:00:42,965] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11116237 - 11134414
[2021-10-03 01:00:42,965] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11134518 - 11139366
[2021-10-03 01:00:42,965] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11139525 - 11157702
[2021-10-03 01:00:42,965] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11157814 - 11162662
[2021-10-03 01:00:42,965] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11162829 - 11162924
[2021-10-03 01:00:42,966] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11163042 - 11181219
[2021-10-03 01:00:42,966] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11181326 - 11186174
[2021-10-03 01:00:42,966] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11186336 - 11204513
[2021-10-03 01:00:42,966] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11204628 - 11209476
[2021-10-03 01:00:42,966] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11209646 - 11209741
[2021-10-03 01:00:42,966] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11209860 - 11228037
[2021-10-03 01:00:42,966] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11228145 - 11232993
[2021-10-03 01:00:42,966] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11233156 - 11251333
[2021-10-03 01:00:42,966] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11251449 - 11256297
[2021-10-03 01:00:42,966] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11256468 - 11256563
[2021-10-03 01:00:42,966] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11256686 - 11274863
[2021-10-03 01:00:42,966] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11274975 - 11279823
[2021-10-03 01:00:42,966] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11279990 - 11298167
[2021-10-03 01:00:42,966] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11298287 - 11303135
[2021-10-03 01:00:42,966] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11303310 - 11303405
[2021-10-03 01:00:42,967] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11303520 - 11321697
[2021-10-03 01:00:42,967] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11321801 - 11326649
[2021-10-03 01:00:42,967] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11326808 - 11344985
[2021-10-03 01:00:42,967] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11345097 - 11349945
[2021-10-03 01:00:42,967] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11350112 - 11350207
[2021-10-03 01:00:42,967] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11350325 - 11368502
[2021-10-03 01:00:42,967] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11368609 - 11373457
[2021-10-03 01:00:42,967] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11373619 - 11391796
[2021-10-03 01:00:42,967] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11391911 - 11396759
[2021-10-03 01:00:42,967] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11396929 - 11397024
[2021-10-03 01:00:42,967] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11397143 - 11415320
[2021-10-03 01:00:42,967] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11415428 - 11420276
[2021-10-03 01:00:42,967] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11420439 - 11438616
[2021-10-03 01:00:42,967] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11438732 - 11443580
[2021-10-03 01:00:42,967] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11443751 - 11443846
[2021-10-03 01:00:42,967] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11443969 - 11462146
[2021-10-03 01:00:42,967] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11462258 - 11467106
[2021-10-03 01:00:42,968] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11467273 - 11485450
[2021-10-03 01:00:42,968] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11485570 - 11490418
[2021-10-03 01:00:42,968] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11490593 - 11490688
[2021-10-03 01:00:42,968] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11490803 - 11508980
[2021-10-03 01:00:42,968] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11509084 - 11513932
[2021-10-03 01:00:42,968] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11514091 - 11532268
[2021-10-03 01:00:42,968] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11532380 - 11537228
[2021-10-03 01:00:42,968] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11537395 - 11537490
[2021-10-03 01:00:42,968] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11537608 - 11555785
[2021-10-03 01:00:42,968] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11555892 - 11560740
[2021-10-03 01:00:42,968] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11560902 - 11579079
[2021-10-03 01:00:42,968] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11579194 - 11584042
[2021-10-03 01:00:42,968] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11584212 - 11584307
[2021-10-03 01:00:42,968] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11584426 - 11602603
[2021-10-03 01:00:42,968] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11602711 - 11607559
[2021-10-03 01:00:42,969] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11607722 - 11625899
[2021-10-03 01:00:42,969] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11626015 - 11630863
[2021-10-03 01:00:42,969] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11631034 - 11631129
[2021-10-03 01:00:42,969] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11631252 - 11649429
[2021-10-03 01:00:42,969] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11649541 - 11654389
[2021-10-03 01:00:42,969] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11654556 - 11672733
[2021-10-03 01:00:42,969] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11672853 - 11677701
[2021-10-03 01:00:42,969] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11677876 - 11677971
[2021-10-03 01:00:42,969] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11678091 - 11696268
[2021-10-03 01:00:42,969] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11696377 - 11701225
[2021-10-03 01:00:42,969] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11701389 - 11719566
[2021-10-03 01:00:42,969] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11719683 - 11724531
[2021-10-03 01:00:42,969] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11724703 - 11724798
[2021-10-03 01:00:42,969] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11724921 - 11743098
[2021-10-03 01:00:42,969] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11743210 - 11748058
[2021-10-03 01:00:42,969] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11748225 - 11766402
[2021-10-03 01:00:42,970] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11766522 - 11771370
[2021-10-03 01:00:42,970] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11771545 - 11771640
[2021-10-03 01:00:42,970] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11771764 - 11789941
[2021-10-03 01:00:42,970] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11790054 - 11794902
[2021-10-03 01:00:42,970] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11795070 - 11813247
[2021-10-03 01:00:42,970] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11813368 - 11818216
[2021-10-03 01:00:42,970] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11818392 - 11818487
[2021-10-03 01:00:42,970] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11818615 - 11836792
[2021-10-03 01:00:42,970] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11836909 - 11841757
[2021-10-03 01:00:42,970] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11841929 - 11860106
[2021-10-03 01:00:42,970] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11860231 - 11865079
[2021-10-03 01:00:42,970] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11865259 - 11865354
[2021-10-03 01:00:42,970] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11865469 - 11883646
[2021-10-03 01:00:42,970] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11883750 - 11888598
[2021-10-03 01:00:42,970] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11888757 - 11906934
[2021-10-03 01:00:42,970] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11907046 - 11911894
[2021-10-03 01:00:42,971] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11912061 - 11912156
[2021-10-03 01:00:42,971] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11912274 - 11930451
[2021-10-03 01:00:42,971] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11930558 - 11935406
[2021-10-03 01:00:42,971] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11935568 - 11953745
[2021-10-03 01:00:42,971] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11953860 - 11958708
[2021-10-03 01:00:42,971] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11958878 - 11958973
[2021-10-03 01:00:42,971] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11959092 - 11977269
[2021-10-03 01:00:42,971] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11977377 - 11982225
[2021-10-03 01:00:42,971] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 11982388 - 12000565
[2021-10-03 01:00:42,971] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12000681 - 12005529
[2021-10-03 01:00:42,971] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12005700 - 12005795
[2021-10-03 01:00:42,971] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12005918 - 12024095
[2021-10-03 01:00:42,971] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12024207 - 12029055
[2021-10-03 01:00:42,971] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12029222 - 12047399
[2021-10-03 01:00:42,971] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12047519 - 12052367
[2021-10-03 01:00:42,971] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12052542 - 12052637
[2021-10-03 01:00:42,972] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12052753 - 12070930
[2021-10-03 01:00:42,972] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12071035 - 12075883
[2021-10-03 01:00:42,972] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12076043 - 12094220
[2021-10-03 01:00:42,972] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12094333 - 12099181
[2021-10-03 01:00:42,972] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12099349 - 12099444
[2021-10-03 01:00:42,972] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12099563 - 12117740
[2021-10-03 01:00:42,972] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12117848 - 12122696
[2021-10-03 01:00:42,972] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12122859 - 12141036
[2021-10-03 01:00:42,972] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12141152 - 12146000
[2021-10-03 01:00:42,972] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12146171 - 12146266
[2021-10-03 01:00:42,972] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12146386 - 12164563
[2021-10-03 01:00:42,972] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12164672 - 12169520
[2021-10-03 01:00:42,972] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12169684 - 12187861
[2021-10-03 01:00:42,972] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12187978 - 12192826
[2021-10-03 01:00:42,972] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12192998 - 12193093
[2021-10-03 01:00:42,972] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12193217 - 12211394
[2021-10-03 01:00:42,973] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12211507 - 12216355
[2021-10-03 01:00:42,973] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12216523 - 12234700
[2021-10-03 01:00:42,973] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12234821 - 12239669
[2021-10-03 01:00:42,973] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12239845 - 12239940
[2021-10-03 01:00:42,973] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12240056 - 12258233
[2021-10-03 01:00:42,973] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12258338 - 12263186
[2021-10-03 01:00:42,973] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12263346 - 12281523
[2021-10-03 01:00:42,973] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12281636 - 12286484
[2021-10-03 01:00:42,973] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12286652 - 12286747
[2021-10-03 01:00:42,973] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12286866 - 12305043
[2021-10-03 01:00:42,973] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12305151 - 12309999
[2021-10-03 01:00:42,973] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12310162 - 12328339
[2021-10-03 01:00:42,973] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12328455 - 12333303
[2021-10-03 01:00:42,973] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12333474 - 12333569
[2021-10-03 01:00:42,973] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12333689 - 12351866
[2021-10-03 01:00:42,974] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12351975 - 12356823
[2021-10-03 01:00:42,974] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12356987 - 12375164
[2021-10-03 01:00:42,974] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12375281 - 12380129
[2021-10-03 01:00:42,974] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12380301 - 12380396
[2021-10-03 01:00:42,974] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12380520 - 12398697
[2021-10-03 01:00:42,974] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12398810 - 12403658
[2021-10-03 01:00:42,974] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12403826 - 12422003
[2021-10-03 01:00:42,974] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12422124 - 12426972
[2021-10-03 01:00:42,974] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12427148 - 12427243
[2021-10-03 01:00:42,974] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12427358 - 12445535
[2021-10-03 01:00:42,974] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12445639 - 12450487
[2021-10-03 01:00:42,974] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12450646 - 12468823
[2021-10-03 01:00:42,974] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12468935 - 12473783
[2021-10-03 01:00:42,974] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12473950 - 12474045
[2021-10-03 01:00:42,974] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12474163 - 12492340
[2021-10-03 01:00:42,974] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12492447 - 12497295
[2021-10-03 01:00:42,975] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12497457 - 12515634
[2021-10-03 01:00:42,975] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12515749 - 12520597
[2021-10-03 01:00:42,975] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12520767 - 12520862
[2021-10-03 01:00:42,975] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12520981 - 12539158
[2021-10-03 01:00:42,975] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12539266 - 12544114
[2021-10-03 01:00:42,975] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12544277 - 12562454
[2021-10-03 01:00:42,975] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12562570 - 12567418
[2021-10-03 01:00:42,975] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12567589 - 12567684
[2021-10-03 01:00:42,975] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12567807 - 12585984
[2021-10-03 01:00:42,975] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12586096 - 12590944
[2021-10-03 01:00:42,975] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12591111 - 12609288
[2021-10-03 01:00:42,975] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12609408 - 12614256
[2021-10-03 01:00:42,975] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12614431 - 12614506
[2021-10-03 01:00:42,975] {spec.py:1529} DEBUG - <File-like object GCSFileSystem, harry-airflow-dev/userprofile/user_game_label/dt=20210922/file-000000000000.parquet> read: 12614592 - 12614687
### Expected Behavior
It should use only 5GB for a file
### Installed Versions
<details>
Replace this line with the output of pd.show_versions()
</details>
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https://api.github.com/repos/pandas-dev/pandas/issues/43861 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/43861/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/43861/comments | https://api.github.com/repos/pandas-dev/pandas/issues/43861/events | https://github.com/pandas-dev/pandas/pull/43861 | 1,014,417,499 | PR_kwDOAA0YD84smrF8 | 43,861 | Update README.md | {
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- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
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} | 0 | "2021-10-03T15:22:19Z" | "2021-10-03T18:07:15Z" | "2021-10-03T16:53:46Z" | MEMBER | null | Fixes a perf regression from 1.2.x
```
from asv_bench.benchmarks.indexing import *
setup()
self = NumericSeriesIndexing()
self.setup(UInt64Index, "unique_monotonic_inc")
%timeit self.time_getitem_scalar(UInt64Index, "unique_monotonic_inc")
6.34 µs ± 257 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each) # <- PR
46.5 µs ± 724 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each) # <- 1.2.0
1.43 ms ± 36.9 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each) # <- master
%timeit self.time_loc_scalar(UInt64Index, "unique_monotonic_inc")
12.6 µs ± 163 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each) # <- PR
53.9 µs ± 1.1 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each) # <- 1.2.0
1.38 ms ± 5.33 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each) # <- master
%timeit self.time_loc_slice(UInt64Index, "unique_monotonic_inc")
32.5 µs ± 2.63 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each) # <- PR
75.6 µs ± 1.22 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each) # <- 1.2.0
1.41 ms ± 10.4 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each) # <- master
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} | 1 | "2021-10-03T16:19:06Z" | "2021-10-04T00:16:03Z" | "2021-10-04T00:09:53Z" | MEMBER | null | - [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [x] whatsnew entry
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Is it possible to add to_orc method to pandas.DataFrame, from pyarrow 4.0.0 ?
Br
Nicolas | {
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} | 0 | "2021-10-03T21:09:35Z" | "2021-10-20T19:49:17Z" | "2021-10-19T22:05:49Z" | MEMBER | null | cc @simonjayhawkins Could you have a look and give some feedback if this is ok so?
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} | 2 | "2021-10-03T21:20:53Z" | "2021-10-07T12:58:29Z" | "2021-10-07T12:58:25Z" | CONTRIBUTOR | null | - [X] closes https://github.com/pandas-dev/pandas/issues/28208
- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
As discussed in https://github.com/pandas-dev/pandas/issues/28208, the docs should be more precise about in which cases `to_feather()` will fail. | {
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] | open | false | null | [] | null | 1 | "2021-10-03T22:46:44Z" | "2021-10-13T03:10:26Z" | null | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [ ] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
import numpy as np
# Create a minimal DataFrame.
df = pd.DataFrame(dict(x=["a"]))
df
# x
# 0 a
# Change x to a numpy array.
df_np = df.copy()
df_np.x = [np.array(df.x)]
df_np # Display that this differs from df.
# x
# 0 [a]
df_np.equals(df)
# True
```
### Issue Description
When comparing two DataFrames, and some values are numpy arrays in one and not in another, `equals` returns `True`, despite them differing visibly.
Here's the above code in a [notebook](https://colab.research.google.com/drive/1daI7Y-XF2c7iOge8Fhlul5puBCNnExEJ?usp=sharing).
Possibly related: https://github.com/pandas-dev/pandas/issues/43008
### Expected Behavior
`df_np.equals(df)` should return `False`.
### Installed Versions
<details>
/usr/local/lib/python3.7/dist-packages/psycopg2/__init__.py:144: UserWarning: The psycopg2 wheel package will be renamed from release 2.8; in order to keep installing from binary please use "pip install psycopg2-binary" instead. For details see: <http://initd.org/psycopg/docs/install.html#binary-install-from-pypi>.
""")
INSTALLED VERSIONS
------------------
commit : 73c68257545b5f8530b7044f56647bd2db92e2ba
python : 3.7.12.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.104+
Version : #1 SMP Sat Jun 5 09:50:34 PDT 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.3.3
numpy : 1.19.5
pytz : 2018.9
dateutil : 2.8.2
pip : 21.1.3
setuptools : 57.4.0
Cython : 0.29.24
pytest : 3.6.4
hypothesis : None
sphinx : 1.8.5
blosc : None
feather : 0.4.1
xlsxwriter : None
lxml.etree : 4.2.6
html5lib : 1.0.1
pymysql : None
psycopg2 : 2.7.6.1 (dt dec pq3 ext lo64)
jinja2 : 2.11.3
IPython : 5.5.0
pandas_datareader: 0.9.0
bs4 : 4.6.3
bottleneck : 1.3.2
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.2.2
numexpr : 2.7.3
odfpy : None
openpyxl : 2.5.9
pandas_gbq : 0.13.3
pyarrow : 3.0.0
pyxlsb : None
s3fs : None
scipy : 1.4.1
sqlalchemy : 1.4.25
tables : 3.4.4
tabulate : 0.8.9
xarray : 0.18.2
xlrd : 1.1.0
xlwt : 1.3.0
numba : 0.51.2
</details>
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- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [x] whatsnew entry
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} | 1 | "2021-10-04T02:20:16Z" | "2021-10-18T19:41:21Z" | "2021-10-18T19:41:21Z" | MEMBER | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import numpy as np
from pandas import Index
import pandas._testing as tm
index = Index(
np.array(
[
"2021-10-02",
np.datetime64("NaT"),
np.timedelta64("NaT"),
np.datetime64("NaT"),
],
dtype=object,
)
)
# pass as index to prevent target from being casted to DatetimeIndex
indexer, missing = index.get_indexer_non_unique(
Index([np.datetime64("NaT")], dtype=object)
)
expected_indexer = np.array([1, 3], dtype=np.intp)
tm.assert_numpy_array_equal(indexer, expected_indexer)
```
### Issue Description
`Index.get_indexer_non_unique()` does not handle when multiple `np.datetime64("NaT")` or `np.timedelta64("NaT")` are present. Extension of #35498
### Expected Behavior
See Reproducible Example
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 24ccae703185e6961af65d76494906840ea19dcb
python : 3.8.10.final.0
python-bits : 64
OS : Darwin
OS-release : 20.6.0
Version : Darwin Kernel Version 20.6.0: Mon Aug 30 06:12:21 PDT 2021; root:xnu-7195.141.6~3/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.2.0.dev0+4209.g24ccae7031
numpy : 1.20.3
pytz : 2021.1
dateutil : 2.8.1
pip : 21.1.2
setuptools : 49.6.0.post20210108
Cython : 0.29.23
pytest : 6.2.4
hypothesis : 6.13.14
sphinx : 3.5.4
blosc : None
feather : None
xlsxwriter : 1.4.3
lxml.etree : 4.6.3
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 2.11.3
IPython : 7.24.1
pandas_datareader: None
bs4 : 4.9.3
bottleneck : 1.3.2
fsspec : 2021.05.0
fastparquet : 0.6.3
gcsfs : 2021.05.0
matplotlib : 3.4.2
numexpr : 2.7.3
odfpy : None
openpyxl : 3.0.7
pandas_gbq : None
pyarrow : 4.0.0
pyxlsb : None
s3fs : 2021.05.0
scipy : 1.6.3
sqlalchemy : 1.4.17
tables : 3.6.1
tabulate : 0.8.9
xarray : 0.18.2
xlrd : 2.0.1
xlwt : 1.3.0
numba : 0.53.1
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} | 12 | "2021-10-04T02:35:02Z" | "2021-10-18T19:54:59Z" | "2021-10-18T19:41:22Z" | MEMBER | null | - [x] closes #43869
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [x] whatsnew entry
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1. `DataFrame.iterrows` does not preserve types. There are lots of users reporting issues related to this. Even though the behavior is documented, why do we want to have a method that get used a lot but keep surprising users? I bet most users won't read the doc thoroughly until they get bitten by the issue.
2. `DataFrame.iterrows` is much slower than other ways of iterating over rows of a DataFrame anyway.
#### Describe the solution you'd like
Deprecate `DataFrame.iterrows`.
#### API breaking implications
[this should provide a description of how this feature will affect the API]
`DataFrame.iterrows` will be deprecated in future.
#### Describe alternatives you've considered
Maybe rename `iterrows` to a better name as suggested in the issue https://github.com/pandas-dev/pandas/issues/43245?
#### Additional context
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] | open | false | null | [] | null | 0 | "2021-10-04T08:54:47Z" | "2021-10-04T20:52:59Z" | null | NONE | null | #### Is your feature request related to a problem?
My feature request is not related to a problem per se, but it can help users to spot type bugs and is not visually noisy.
I wish there could be a way to change the Pandas `str` and `html` representation to show the dtypes of columns below the headers (like R's `tibble` or Julia's `DataFrame`).
#### Describe the solution you'd like
I imagine that the solution would involve setting an option, e.g. `pd.set_option("display_dtypes", True)`.
#### API breaking implications
As far as I understand, adding such option wouldn't break the API.
#### Describe alternatives you've considered
I could try to write something in this direction, but honestly I don't even know where to find the relevant source code to start. If someone could point me the direction I would be happy to try it out.
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- [X] I have read the [installation guide](https://pandas.pydata.org/pandas-docs/stable/getting_started/install.html#installing-pandas).
### Platform
win-64
### Installation Method
conda install
### pandas Version
latest master
### Python Version
n/a
### Installation Logs
<details>
$ conda env create -f environment.yml
Collecting package metadata (repodata.json): done
Solving environment: /
</details>
* Full disclosure: this is not a `pandas` issue per se, this is a `conda` issue. However, I see two ways to solve this issue for anyone trying to build `pandas` locally:
1. Use `mamba` instead of `conda` to create dev environment. `mamba` has a much faster SAT solver compared to `conda`.
2. (Probably, preferred) Pin package version numbers _for each platform_ in https://github.com/pandas-dev/pandas/blob/c03cc2245538e3a2c182f6eb15cfb143897a9503/environment.yml.
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} | 10 | "2021-10-04T11:05:41Z" | "2021-10-27T15:44:54Z" | null | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
import numpy as np
# any loop
for _ in range(1000)
df = pd.DataFrame({str(c): np.random.random_sample(size=100_000) for c in range(10)})
df.to_json() # same regardless orient or using file
```
### Issue Description
It looks like a memory leak when calling `to_json` introduced in version 1.1.0. It seems it prevents the dataframe to be correctly garbage collected. Here's a memory profile Pandas 1.1.0 compared to the previous version 1.0.5:

I have the same trends either on Windows 10, Linux Ubuntu, python 3.7, 3.8 & 3.9.
This leak is still there on latest Pandas version 1.3.3 and is proportional to the size of the dataframe. I've tried direct calls to `del` and `gc.collect()` but it doesn't change anything.
It's specific to `to_json` method. I haven't observed leak with other formats such as CSV.
I don't know if it makes sense or help, here's an output using tracemalloc from this code:
```
def foo():
df = pd.DataFrame({str(c): np.random.random_sample(size=100_000) for c in range(5)})
df.to_json()
if __name__ == "__main__":
tracemalloc.start(50)
foo()
snapshot = tracemalloc.take_snapshot()
top_stats = snapshot.statistics('traceback')
# pick the biggest memory block
stat = top_stats[0]
print("%s memory blocks: %.1f KiB" % (stat.count, stat.size / 1024))
for line in stat.traceback.format():
print(line)
```
with Pandas 1.1.0 or 1.3.3:
```
5 memory blocks: 782.5 KiB
File "main.py"
foo()
File "main.py"
df.to_json()
File ".\ven37\lib\site-packages\pandas\core\generic.py", line 2571
storage_options=storage_options,
File ".\ven37\lib\site-packages\pandas\io\json\_json.py", line 122
indent=indent,
File ".\ven37\lib\site-packages\pandas\io\json\_json.py", line 183
indent=self.indent,
File ".\ven37\lib\site-packages\pandas\core\indexes\base.py", line 4367
return self._data
File ".\ven37\lib\site-packages\pandas\core\indexes\range.py", line 186
return np.arange(self.start, self.stop, self.step, dtype=np.int64)
```
whereas 1.0.5 produces this:
```
9 memory blocks: 1.6 KiB
File "main.py"
foo()
File "main.py"
df.to_json()
File ".\ven37\lib\site-packages\pandas\core\generic.py", line 2364
indent=indent,
File ".\ven37\lib\site-packages\pandas\io\json\_json.py", line 85
indent=indent,
File ".\ven37\lib\site-packages\pandas\io\json\_json.py", line 145
self.indent,
File ".\ven37\lib\site-packages\pandas\io\json\_json.py", line 245
indent,
File ".\ven37\lib\site-packages\pandas\io\json\_json.py", line 167
indent=indent,
```
### Expected Behavior
No leak expected, similar to version 1.0.5
### Installed Versions
**Versions with leak:**
master -----------------
commit : 65998341034861527517756e6dd134dafea2b766
python : 3.8.5.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19041
machine : AMD64
processor : Intel64 Family 6 Model 158 Stepping 13, GenuineIntel
pandas : 1.4.0.dev0+833.g6599834103
numpy : 1.21.2
pytz : 2021.1
dateutil : 2.8.2
...
1.3.3 ------------------
commit : 73c68257545b5f8530b7044f56647bd2db92e2ba
python : 3.7.6.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19041
machine : AMD64
processor : Intel64 Family 6 Model 158 Stepping 13, GenuineIntel
pandas : 1.3.3
numpy : 1.21.2
...
1.1.0 ------------------
commit : d9fff2792bf16178d4e450fe7384244e50635733
pandas : 1.1.0
numpy : 1.21.2
...
**Versions without leak:**
commit : None
pandas : 1.0.5
numpy : 1.21.2
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- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
ps.read_sql("query", con)
```
### Issue Description
I am trying to read a stored procedure by using pandas.read_sql method in Python by using the pyodbc driver. The issue I have is when Pandas reads data, it converts int columns to float which have Null values in it.
### Expected Behavior
import pandas as pd
ps.read_sql("query", con)
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 73c68257545b5f8530b7044f56647bd2db92e2ba
python : 3.8.10.final.0
python-bits : 64
OS : Linux
OS-release : 5.11.0-37-generic
Version : #41~20.04.2-Ubuntu SMP Fri Sep 24 09:06:38 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.3.3
numpy : 1.21.2
pytz : 2021.1
dateutil : 2.8.2
pip : 20.0.2
setuptools : 44.0.0
Cython : None
pytest : 6.2.5
hypothesis : None
sphinx : 4.2.0
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.1
IPython : 7.27.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : 1.4.23
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
>>> import pandas as pd
</details>
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-error occurs due to different versions of pandas
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] | open | false | null | [] | null | 1 | "2021-10-04T16:52:12Z" | "2021-11-04T00:03:15Z" | null | NONE | null |
- [x] closes #43839
- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
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] | open | false | null | [] | null | 4 | "2021-10-04T17:34:47Z" | "2021-10-07T06:25:43Z" | null | NONE | null | #### Is your feature request related to a problem?
For dataframes, Pandas currently only supports per-column quantiles; that is, given `df[['c', 'a']].quantile(...)`, Pandas will compute the individual quantiles for columns `c` and `a`:
```python
>>> df = pd.DataFrame({'a': [1, 0, 11, 12, 2], 'b': [1, 2, 3, 4, 5], 'c': [0, 1, 5, 2, 3]})
>>> df[['c', 'a']].quantile([0, 0.5, 1])
c a
0.0 0.0 0.0
0.5 2.0 2.0
1.0 5.0 12.0
```
It would be nice if Pandas also supported multi-column quantiles; that is, given `df[['c', 'a']].quantiles(...)`, Pandas would compute the quantiles for the dataframe sorted by _all_ columns. This is currently implemented by cuDF's dataframe:
```python
In [11]: gdf = cudf.DataFrame({"a": [1, 1, 1, 1, 1], "b": [5, 4, 3, 2, 1]})
In [12]: gdf[["a", "b"]].quantiles([0, 0.5, 1])
Out[12]:
a b
0.0 1 1
0.5 1 3
1.0 1 5
```
#### Describe the solution you'd like
I imagine the addition of multi-column quantiles support could happen in two ways:
1. the addition of a default kwarg to `DataFrame.quantile` to specify whether or not we want multi-column quantiles
2. the addition of a new method to compute multi-column quantiles independent from the logic of `quantile`
In either case, my preference here would be to have this functionality accessible via `DataFrame.quantiles`, to maintain consistency with cuDF.
#### API breaking implications
I can't think of any breakages this would cause, as long as any direct changes to `quantile` ensure that the original behavior is maintained by default.
#### Describe alternatives you've considered
This could be accomplished by sorting the dataframe by all columns and then indexing based on manually computed quantiles, but I imagine there's a more performant way to do this.
#### Additional context
If this functionality were added, along with a multi-columnar `searchsorted`, it would enable Dask dataframes to compute `sort_values` with multiple sort-by columns, using an algorithm roughly similar to [that of dask-cudf](https://github.com/rapidsai/cudf/blob/ffb3814089c9a0c3c332d9a36714ab853a48ca9d/python/dask_cudf/dask_cudf/sorting.py#L208-L254).
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} | 4 | "2021-10-04T17:43:40Z" | "2021-10-06T08:20:23Z" | "2021-10-06T01:07:57Z" | CONTRIBUTOR | null | I've just been [helping someone](https://stackoverflow.com/questions/69352179/package-streamlit-app-and-run-executable-on-windows) for whom the helpful error message appears to have obscured the real cause of the problem. Specifically, Jinja2 is present, but one of *its* dependencies is not. So the error message saying "Missing optional dependency: 'Jinja2'..." is rather confusing.
Automatic exception chaining is really great for things like this - you can provide a more descriptive error message while still having the original exception details available for inspection. I'd argue that it should only be disabled (`raise ... from None`) if you're absolutely sure that there will be no useful information in the original exception. | {
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} | 0 | "2021-10-04T19:16:57Z" | "2021-10-05T01:40:00Z" | "2021-10-05T00:32:09Z" | MEMBER | null | - [ ] closes #xxxx
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [x] whatsnew entry
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} | 5 | "2021-10-04T19:17:03Z" | "2021-10-16T14:35:19Z" | "2021-10-16T14:35:19Z" | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [ ] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [ ] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
df = pd.DataFrame({
"animal": ["dog", "duck", "horse", "penguin", "kangaroo"],
"legs": [4, 2, 4, 2, 2],
"class": ["mammal", "bird", "mammal", "bird", "mammal"]
})
df.set_index(["class", "animal"], inplace=True)
sorted1 = df.sort_index(level=(0, 1), ascending=[True, False])
sorted2 = df.sort_index(level=(0, 1), ascending=(True, False))
```
### Issue Description
In the above example, the `sort_index` method on DataFrame object does not sort MultiIndex properly when the `ascending` parameter is passed as tuple. The `sorted2.index` should be sorted in ascending order for level 0 (`class`) and descending order for level 1 (`animal`). However, this is not the case and level 1 is also ascending:
```python
>>> print(sorted2.index)
MultiIndex([( 'bird', 'duck'),
( 'bird', 'penguin'),
('mammal', 'dog'),
('mammal', 'horse'),
('mammal', 'kangaroo')],
names=['class', 'animal'])
```
When the `ascending` parameter is list than the `sort_index` method works as expected such that level 0 is ascending and level 1 is descending:
```python
>>> print(sorted1.index)
MultiIndex([( 'bird', 'penguin'),
( 'bird', 'duck'),
('mammal', 'kangaroo'),
('mammal', 'horse'),
('mammal', 'dog')],
names=['class', 'animal'])
```
### Expected Behavior
I would expect `sorted1.index` and `sorted2.index` to be equal (i.e., include a test case with `assert sorted1.index == sorted2.index` that passes).
### Installed Versions
INSTALLED VERSIONS
------------------
commit : b5958ee1999e9aead1938c0bba2b674378807b3d
python : 3.6.9.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.0-84-generic
Version : #94~18.04.1-Ubuntu SMP Thu Aug 26 23:17:46 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.1.5
numpy : 1.19.5
pytz : 2021.3
dateutil : 2.8.2
pip : 21.2.4
setuptools : 58.2.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : 7.16.1
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
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xlwt : None
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] | open | false | null | [] | null | 0 | "2021-10-04T19:37:55Z" | "2021-10-13T02:24:47Z" | null | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this issue exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [ ] I have confirmed this issue exists on the master branch of pandas.
### Reproducible Example
We are currently materializing `RangeIndex` which is already monotonically increasing when `sort=False`.
```python
>>> import pandas as pd
>>> pd.__version__
'1.3.3'
>>> idx1 = pd.RangeIndex(0, 10)
>>> idx2 = pd.RangeIndex(0, 5)
>>> idx1.union(idx2)
RangeIndex(start=0, stop=10, step=1)
>>> idx1.union(idx2, sort=False)
Int64Index([0, 1, 2, 3, 4, 5, 6, 7, 8, 9], dtype='int64')
```
This behavior was introduced in this PR: https://github.com/pandas-dev/pandas/pull/25788
From the PR description, it seems to be a conscious decision, but for performance reasons we should ideally be checking the result of the `union` if it is monotonically increasing/decreasing and then decide to sort or not based on `sort` parameter. This alleviates materialization and thus memory pressure too.
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 73c68257545b5f8530b7044f56647bd2db92e2ba
python : 3.9.6.final.0
python-bits : 64
OS : Darwin
OS-release : 20.6.0
Version : Darwin Kernel Version 20.6.0: Mon Aug 30 06:12:21 PDT 2021; root:xnu-7195.141.6~3/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : None
LOCALE : en_US.UTF-8
pandas : 1.3.3
numpy : 1.21.2
pytz : 2021.1
dateutil : 2.8.2
pip : 21.2.4
setuptools : 57.4.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 5.0.0
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
### Prior Performance
_No response_ | {
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] | open | false | null | [] | null | 6 | "2021-10-05T03:28:38Z" | "2021-10-08T12:18:23Z" | null | MEMBER | null | Currently, `engine="numba"` is enabled for `rolling` reduction functions (e.g. mean). I am making efforts to enable numba execution for `groupby` and regular `DataFrame/Series` reduction functions as well.
For `rolling`, the `engine` keyword is currently defined on the reduction functions e.g.
```
df.rolling(2).mean(engine="numba", engine_kwargs={...})
df.groupby(key).mean(engine="numba", engine_kwargs={...}) # planned
df.mean(engine="numba", engine_kwargs={...}) # planned
```
https://github.com/pandas-dev/pandas/pull/43731#discussion_r715931881 suggested possibly putting engine in the "constructor" e.g.
```
df.rolling(2, engine="numba", engine_kwargs={...}).mean()
df.groupby(key, engine="numba", engine_kwargs={...}).mean()
DataFrame(..., engine="numba", engine_kwargs={...}.mean() ?
```
Pros of "in the constructor"
1. Less verbose e.g.
```
roll = df.rolling(2, engine="numba", engine_kwargs={...})
roll.mean() # numba
roll.median() # numba
roll.unsupported_agg() # raise NotImplementedError
```
Cons of "in the constructor"
1. Less flexibility in switching engines (probably minor) e.g.
```
gb = df.groupby(key, engine="numba", engine_kwargs={...})
gb.mean() # numba
# Reconstruct to switch engines
gb = df.groupby(key, engine="cython")
gb.cython_only_agg() # cython
```
2. Increased complexity with "chained constructors" e.g.
```
gb_roll = df.groupby(key, engine="numba").rolling(2, engine="numba").mean()
```
I prefer having `engine` in the reduction function, but opening this issue to solicit thoughts. | {
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} | 1 | "2021-10-05T04:07:46Z" | "2021-10-10T21:50:06Z" | "2021-10-10T21:39:08Z" | MEMBER | null | - [ ] closes #xxxx
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
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} | 3 | "2021-10-05T11:58:00Z" | "2021-10-06T13:29:09Z" | "2021-10-06T13:29:09Z" | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this issue exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this issue exists on the master branch of pandas.
### Reproducible Example
I'm a pytest dev that's been looking to speed up collection time, using pandas as a benchmark. I thought you'd be interested to know that there is a case which is slow (~1s) just because it does something heavy at the module scope:
https://github.com/pandas-dev/pandas/blob/65998341034861527517756e6dd134dafea2b766/pandas/tests/test_algos.py#L1800-L1805
These arrays are heavy to create, better to make it lazy by wrapping in a lambda or just split to two separate tests.
There's also something slow in the pandas/tests/reshape/merge/test_merge.py module but I'm not sure what.
### Installed Versions
```
INSTALLED VERSIONS
------------------
commit : 65998341034861527517756e6dd134dafea2b766
python : 3.9.7.final.0
python-bits : 64
OS : Linux
OS-release : 5.14.6-arch1-1
Version : #1 SMP PREEMPT Sat, 18 Sep 2021 16:19:35 +0000
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.4.0.dev0+833.g6599834103
numpy : 1.21.2
pytz : 2021.3
dateutil : 2.8.2
pip : 21.2.4
setuptools : 58.0.4
Cython : 0.29.24
pytest : 6.3.0.dev745+g483f239d0
hypothesis : 6.23.1
sphinx : None
blosc : None
feather : None
xlsxwriter : 3.0.1
lxml.etree : 4.6.3
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 3.0.1
IPython : None
pandas_datareader: None
bs4 : 4.10.0
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.4.3
numexpr : 2.7.3
odfpy : None
openpyxl : 3.0.9
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.7.1
sqlalchemy : None
tables : 3.6.1
tabulate : 0.8.9
xarray : None
xlrd : 2.0.1
xlwt : 1.3.0
numba : None
```
### Prior Performance
_No response_ | {
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https://api.github.com/repos/pandas-dev/pandas/issues/43889 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/43889/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/43889/comments | https://api.github.com/repos/pandas-dev/pandas/issues/43889/events | https://github.com/pandas-dev/pandas/issues/43889 | 1,016,363,586 | I_kwDOAA0YD848lHpC | 43,889 | ENH: `axis=None` option for statistical methods: `.min`, `.max`, `.median`, and so on | {
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] | open | false | null | [] | null | 1 | "2021-10-05T13:56:20Z" | "2021-10-21T21:30:05Z" | null | NONE | null | I am a long time user of pandas, thank you for all your hard work.
#### Is your feature request related to a problem?
It would be useful to be able to do `df.min(axis=None)` rather than `df.values.min(axis=None)` to get the mimum over the whole DataFrame. The same goes for `max` and so on. I expected this to work since this is how `any` and `all` work.
#### Describe the solution you'd like
I'd like the default argument for `axis` to be `0` and then change the behaviour of `None` to do both axes, like numpy does. This would be then be consistent with `.all` and `.any`.
Maybe changing behaviour of `axis=None` would be an issue, if so, maybe this would require the less desirable `axis="both"`.
#### API breaking implications
This would make the API more consitent, but would also be a breaking change.
#### Describe alternatives you've considered
Writing `df.values.min(None)`. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/43890 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/43890/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/43890/comments | https://api.github.com/repos/pandas-dev/pandas/issues/43890/events | https://github.com/pandas-dev/pandas/issues/43890 | 1,016,391,995 | I_kwDOAA0YD848lOk7 | 43,890 | CI: Move Python 3.10 workflows to Posix Matrix File | {
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] | open | false | null | [] | null | 0 | "2021-10-05T14:21:12Z" | "2021-10-05T14:23:44Z" | null | MEMBER | null | Python 3.10 just released yesterday and Github Actions has added python 3.10 to their env. We should try to move Python 3.10 there ASAP after we fix #41935
We should also make a .yml file as soon as conda-forge supports python 3.10.( I expect that to probably happen sometime in the next week). | {
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https://api.github.com/repos/pandas-dev/pandas/issues/43891 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/43891/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/43891/comments | https://api.github.com/repos/pandas-dev/pandas/issues/43891/events | https://github.com/pandas-dev/pandas/issues/43891 | 1,016,515,628 | I_kwDOAA0YD848lsws | 43,891 | BUG: Groupby with categorical multiIndex and timedelta returns incorrect type. | {
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] | open | false | null | [] | null | 0 | "2021-10-05T16:12:36Z" | "2021-10-13T03:24:16Z" | null | NONE | null | Groupby (`observed=False`) with a categorical multiIndex and integer data values returns zero for categories that do no appear in the data, as seen in the first example (there are no wild parrots).
``` python
import pandas as pd
animals = ['Falcon', 'Parrot']
types = ['Captive', 'Wild']
df = pd.DataFrame({
'animal': pd.Categorical(['Falcon', 'Falcon', 'Parrot', 'Parrot'],
categories=animals),
'type': pd.Categorical(['Captive', 'Wild', 'Captive', 'Captive'],
categories=types),
'time': [1, 2, 3, 4]
})
df.set_index(['animal', 'type'], inplace=True)
df.groupby(level=['animal', 'type'], observed=False).sum()
```
| index | time |
|------------------------|-----|
| ('Falcon', 'Captive') | 1 |
| ('Falcon', 'Wild') | 2 |
| ('Parrot', 'Captive') | 7 |
| ('Parrot', 'Wild') | 0 |
But when using `Timedelta` data values an `int` is returned, instead of a Timedelta.
``` python
import pandas as pd
animals = ['Falcon', 'Parrot']
types = ['Captive', 'Wild']
df = pd.DataFrame({
'animal': pd.Categorical(['Falcon', 'Falcon', 'Parrot', 'Parrot'],
categories=animals),
'type': pd.Categorical(['Captive', 'Wild', 'Captive', 'Captive'],
categories=types),
'time': [1, 2, 3, 4]
})
# Convert time to time delta.
df['time'] = pd.to_timedelta(df['time'])
df.set_index(['animal', 'type'], inplace=True)
df.groupby(level=['animal', 'type'], observed=False).sum()
```
Error:
```
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
/tmp/ipykernel_106514/2243147148.py in <module>
14 df['time'] = pd.to_timedelta(df['time'])
15 df.set_index(['animal', 'type'], inplace=True)
---> 16 df.groupby(level=['animal', 'type'], observed=False).sum()
~/.local/share/virtualenvs/dv-eRvxryI1/lib/python3.9/site-packages/pandas/core/groupby/groupby.py in sum(self, numeric_only, min_count)
1851 )
1852
-> 1853 return self._reindex_output(result, fill_value=0)
1854
1855 @final
~/.local/share/virtualenvs/dv-eRvxryI1/lib/python3.9/site-packages/pandas/core/groupby/groupby.py in _reindex_output(self, output, fill_value)
3169 "fill_value": fill_value,
3170 }
-> 3171 return output.reindex(**d)
3172
3173 # GH 13204
~/.local/share/virtualenvs/dv-eRvxryI1/lib/python3.9/site-packages/pandas/util/_decorators.py in wrapper(*args, **kwargs)
322 @wraps(func)
323 def wrapper(*args, **kwargs) -> Callable[..., Any]:
--> 324 return func(*args, **kwargs)
325
326 kind = inspect.Parameter.POSITIONAL_OR_KEYWORD
~/.local/share/virtualenvs/dv-eRvxryI1/lib/python3.9/site-packages/pandas/core/frame.py in reindex(self, *args, **kwargs)
4770 kwargs.pop("axis", None)
4771 kwargs.pop("labels", None)
-> 4772 return super().reindex(**kwargs)
4773
4774 @deprecate_nonkeyword_arguments(version=None, allowed_args=["self", "labels"])
~/.local/share/virtualenvs/dv-eRvxryI1/lib/python3.9/site-packages/pandas/core/generic.py in reindex(self, *args, **kwargs)
4816
4817 # perform the reindex on the axes
-> 4818 return self._reindex_axes(
4819 axes, level, limit, tolerance, method, fill_value, copy
4820 ).__finalize__(self, method="reindex")
~/.local/share/virtualenvs/dv-eRvxryI1/lib/python3.9/site-packages/pandas/core/frame.py in _reindex_axes(self, axes, level, limit, tolerance, method, fill_value, copy)
4595 index = axes["index"]
4596 if index is not None:
-> 4597 frame = frame._reindex_index(
4598 index, method, copy, level, fill_value, limit, tolerance
4599 )
~/.local/share/virtualenvs/dv-eRvxryI1/lib/python3.9/site-packages/pandas/core/frame.py in _reindex_index(self, new_index, method, copy, level, fill_value, limit, tolerance)
4614 new_index, method=method, level=level, limit=limit, tolerance=tolerance
4615 )
-> 4616 return self._reindex_with_indexers(
4617 {0: [new_index, indexer]},
4618 copy=copy,
~/.local/share/virtualenvs/dv-eRvxryI1/lib/python3.9/site-packages/pandas/core/generic.py in _reindex_with_indexers(self, reindexers, fill_value, copy, allow_dups)
4881
4882 # TODO: speed up on homogeneous DataFrame objects
-> 4883 new_data = new_data.reindex_indexer(
4884 index,
4885 indexer,
~/.local/share/virtualenvs/dv-eRvxryI1/lib/python3.9/site-packages/pandas/core/internals/managers.py in reindex_indexer(self, new_axis, indexer, axis, fill_value, allow_dups, copy, consolidate, only_slice)
678 )
679 else:
--> 680 new_blocks = [
681 blk.take_nd(
682 indexer,
~/.local/share/virtualenvs/dv-eRvxryI1/lib/python3.9/site-packages/pandas/core/internals/managers.py in <listcomp>(.0)
679 else:
680 new_blocks = [
--> 681 blk.take_nd(
682 indexer,
683 axis=1,
~/.local/share/virtualenvs/dv-eRvxryI1/lib/python3.9/site-packages/pandas/core/internals/blocks.py in take_nd(self, indexer, axis, new_mgr_locs, fill_value)
1143 allow_fill = True
1144
-> 1145 new_values = algos.take_nd(
1146 values, indexer, axis=axis, allow_fill=allow_fill, fill_value=fill_value
1147 )
~/.local/share/virtualenvs/dv-eRvxryI1/lib/python3.9/site-packages/pandas/core/array_algos/take.py in take_nd(arr, indexer, axis, fill_value, allow_fill)
99 # i.e. DatetimeArray, TimedeltaArray
100 arr = cast("NDArrayBackedExtensionArray", arr)
--> 101 return arr.take(
102 indexer, fill_value=fill_value, allow_fill=allow_fill, axis=axis
103 )
~/.local/share/virtualenvs/dv-eRvxryI1/lib/python3.9/site-packages/pandas/core/arrays/_mixins.py in take(self, indices, allow_fill, fill_value, axis)
95 ) -> NDArrayBackedExtensionArrayT:
96 if allow_fill:
---> 97 fill_value = self._validate_scalar(fill_value)
98
99 new_data = take(
~/.local/share/virtualenvs/dv-eRvxryI1/lib/python3.9/site-packages/pandas/core/arrays/datetimelike.py in _validate_scalar(self, value, allow_listlike, setitem, unbox)
643 else:
644 msg = self._validation_error_message(value, allow_listlike)
--> 645 raise TypeError(msg)
646
647 if not unbox:
TypeError: value should be a 'Timedelta' or 'NaT'. Got 'int' instead.
```
pd.show_versions()
INSTALLED VERSIONS
------------------
commit : 73c68257545b5f8530b7044f56647bd2db92e2ba
python : 3.9.2.final.0
python-bits : 64
OS : Linux
OS-release : 5.10.0-8-amd64
Version : #1 SMP Debian 5.10.46-5 (2021-09-23)
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : en_GB.UTF-8
LOCALE : en_GB.UTF-8
pandas : 1.3.3
numpy : 1.19.5
pytz : 2021.3
dateutil : 2.8.2
pip : 21.2.4
setuptools : 58.1.0
Cython : 0.29.24
pytest : 6.2.5
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.6.3
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.2
IPython : 7.28.0
pandas_datareader: None
bs4 : 4.10.0
bottleneck : 1.3.2
fsspec : 2021.10.0
fastparquet : None
gcsfs : None
matplotlib : 3.4.3
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} | 2 | "2021-10-05T16:44:01Z" | "2021-10-16T14:43:22Z" | null | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [ ] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
from pandas.tseries.offsets import DateOffset
from pandas import Timedelta, Timestamp
# With Timedelta this works as expected:
Timestamp(0) + Timedelta(nanoseconds=1, microseconds=1)
# >>> Timestamp('1970-01-01 00:00:00.000001001')
Timestamp(0) + DateOffset(nanoseconds=1, microseconds=1)
# >>> Timestamp('1970-01-01 00:00:00.000001')
(Timestamp(0) + DateOffset(nanoseconds=1, microseconds=1)).nanosecond
# >>> 0
```
### Issue Description
The nanoseconds component DateOffset's does not appear to affect Timestamps when adding them.
Possibly related issue. https://github.com/pandas-dev/pandas/issues/36589
### Expected Behavior
I expect this to be the same behavior as pd.Timedelta as illustrated above.
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 73c68257545b5f8530b7044f56647bd2db92e2ba
python : 3.9.7.final.0
python-bits : 64
OS : Linux
OS-release : 5.10.46-4rodete4-amd64
Version : #1 SMP Debian 5.10.46-4rodete4 (2021-09-06)
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.3.3
numpy : 1.21.1
pytz : 2021.1
dateutil : 2.8.2
pip : 20.3.4
setuptools : 57.4.0
Cython : 0.29.24
pytest : 6.2.5
hypothesis : 6.23.1
sphinx : 4.1.2
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.1
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
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} | 1 | "2021-10-05T21:27:43Z" | "2021-10-06T01:10:07Z" | "2021-10-06T01:10:03Z" | CONTRIBUTOR | null | - [ ] does not close any issue, change is too trivial
- [ ] tests are not required for this
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] nothing new
Related https://github.com/python/mypy/pull/11273
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- [x] closes: #43875

<details>
<summary>Former example...</summary>

</details>
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- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
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] | open | false | null | [] | null | 0 | "2021-10-05T23:22:11Z" | "2021-10-13T03:25:44Z" | null | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [x] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
import numpy as np
index=pd.date_range('2019-12-31T00:10:00', '2020-01-31T00:10:00', freq='1T')
df = pd.DataFrame(np.zeros(len(index)), index=index)
grouper = pd.Grouper(freq='2D', closed='right')
sampled = df.groupby(grouper).sum()
```
### Issue Description
The _**groupby()**_ call creates a new Resampler object which builds the bins calling the _**_get_times_bins()**_ function.
This function detects the first/last entries using the origin and the close semantic and calls the **_date_range()_** helper to get the bins intervals which, in our example, are the following:
```
DatetimeIndex(['2019-12-31',` '2020-01-02', '2020-01-04', '2020-01-06',
'2020-01-08', '2020-01-10', '2020-01-12', '2020-01-14',
'2020-01-16', '2020-01-18', '2020-01-20', '2020-01-22',
'2020-01-24', '2020-01-26', '2020-01-28', '2020-01-30',
'2020-02-01'],
dtype='datetime64[ns]', freq='2D')
```
at this point the function calls into **_self._adjust_bin_edges(self, binner, ax_values)_** passing the bins and the actual source values.
```
def _adjust_bin_edges(self, binner, ax_values):
# Some hacks for > daily data, see #1471, #1458, #1483
if self.freq != "D" and is_superperiod(self.freq, "D"):
if self.closed == "right":
# GH 21459, GH 9119: Adjust the bins relative to the wall time
bin_edges = binner.tz_localize(None)
bin_edges = bin_edges + timedelta(1) - Nano(1)
bin_edges = bin_edges.tz_localize(binner.tz).asi8
else:
bin_edges = binner.asi8
# intraday values on last day
if bin_edges[-2] > ax_values.max():
bin_edges = bin_edges[:-1]
binner = binner[:-1]
else:
bin_edges = binner.asi8
return binner, bin_edges
```
which seems to have some old spaghetti-code which tries to fix old issues...
if the frequency is not a single Day (???) (like in our example **freq='2D'**) and **_is_superperiod()_** function (which seems broken given that it checks only the base/role frequency instead of the whole one: aka it can't detect that 2D is not a superperiod of D or that 48H is semantically the same as 2D.. etc...) returns True the code enters this code segment which adds to every bin interval a whole day without the last nanosecond transforming the first entry into something like this:
```
DatetimeIndex(['2019-12-31 23:59:59.999999999',
'2020-01-02 23:59:59.999999999',
'2020-01-04 23:59:59.999999999',
...
...
'2020-02-01 23:59:59.999999999'],
dtype='datetime64[ns]', freq='2D')
```
which is totally nonsense given that the code later calls the generic cython **_lib.generate_bins_dt64()_** which compares the actual entries starting from **_'2019-12-31T00:10:00'_** to the first bin entry which is now a new 'edged' value **_'2019-12-31 23:59:59.999999999'_**. This in turn triggers the first sanity check since the first bin value is in the future in respect to the first value:
```
@cython.boundscheck(False)
@cython.wraparound(False)
def generate_bins_dt64(ndarray[int64_t] values, const int64_t[:] binner,
object closed='left', bint hasnans=False):
...
...
# check binner fits data
if values[0] < binner[0]:
raise ValueError("Values falls before first bin")
```
### Expected Behavior
The groupby() function should return without any exception.
### Installed Versions
<details>
>>> pd.show_versions()
INSTALLED VERSIONS
------------------
commit : 73c68257545b5f8530b7044f56647bd2db92e2ba
python : 3.8.8.final.0
python-bits : 64
OS : Linux
OS-release : 4.15.0-140-generic
Version : #144~16.04.1-Ubuntu SMP Fri Mar 19 21:24:12 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.3.3
numpy : 1.21.2
pytz : 2021.1
dateutil : 2.8.1
pip : 21.0.1
setuptools : 54.2.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.3
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
>>>
</details>
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} | 1 | "2021-10-06T02:25:43Z" | "2021-10-06T18:36:02Z" | "2021-10-06T18:32:42Z" | MEMBER | null | This implements `ExtensionArray.__array_ufunc__` with minimal behavior changes (xref https://github.com/numpy/numpy/issues/20044 cc @shoyer). The only real behavior change is that np.abs, np.positive, np.negative wrap TimedeltaArray instead of returning ndarray[td64]
After this comes `Index.__array_ufunc__` | {
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https://api.github.com/repos/pandas-dev/pandas/issues/43900 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/43900/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/43900/comments | https://api.github.com/repos/pandas-dev/pandas/issues/43900/events | https://github.com/pandas-dev/pandas/pull/43900 | 1,017,603,845 | PR_kwDOAA0YD84sw3i7 | 43,900 | ENH: Add support for more placeholders in `guess_datetime_format` | {
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} | 4 | "2021-10-06T06:41:39Z" | "2021-10-25T19:43:58Z" | "2021-10-17T23:03:16Z" | CONTRIBUTOR | null | Add support for day of week and meridiem placeholders and any
combination of placeholders supported by `strftime` that do not
correspond to a datetime attribute.
- [x] closes #43901
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [x] whatsnew entry
I'm not sure if this fix actually qualifies as a bug fix and not and enhancement. Before, `guess_datetime_format` would output a somewhat invalid format string that included literal content from the parsed datetime such as "Tue" or "AM".
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} | 0 | "2021-10-06T15:45:19Z" | "2021-10-17T23:03:16Z" | "2021-10-17T23:03:16Z" | CONTRIBUTOR | null | #### Is your feature request related to a problem?
We recently realized that `pandas.core.tools.datetimes.guess_datetime_format` outputs an incorrect format string `"Tue %d %b %Y %H:%M:%S AM"` for the datetime `"Tue 24 Aug 2021 01:30:48 AM"`, which otherwise is parseable by `dateutil.parser.parse`.
#### Describe the solution you'd like
Since `"Tue 24 Aug 2021 01:30:48 AM"` is parseable by `dateutil.parser.parse` and `guess_datetime_format` is based on that function, it seems reasonable that `guess_datetime_format` should produce a correct format string when given this example datetime.
#### API breaking implications
I believe modifying `guess_datetime_format` to support more formats placeholders should be a backwards compatible change.
#### Describe alternatives you've considered
Not sure that there are any.
#### Additional context
```python
from pandas.core.tools.datetimes import guess_datetime_format
# actual
assert guess_datetime_format("Tue 24 Aug 2021 01:30:48 AM") == "Tue %d %b %Y %H:%M:%S AM"
# expected
assert guess_datetime_format("Tue 24 Aug 2021 01:30:48 AM") == "%a %d %b %Y %H:%M:%S %p"
```
I already have a PR up for this here: #43900 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/43902 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/43902/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/43902/comments | https://api.github.com/repos/pandas-dev/pandas/issues/43902/events | https://github.com/pandas-dev/pandas/issues/43902 | 1,018,924,975 | I_kwDOAA0YD848u4-v | 43,902 | ENH: Feature Request for Ungroup Method for Grouped Data Frames | {
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] | open | false | null | [] | null | 3 | "2021-10-06T18:23:46Z" | "2021-10-13T04:01:08Z" | null | NONE | null | Hi, thanks for your work developing `pandas`. I'd like to request a feature to add an ungroup() method for grouped data frames. It's related to this [StackOverflow](https://stackoverflow.com/questions/20122521/is-there-an-ungroup-by-operation-opposite-to-groupby-in-pandas/66879388#66879388) where I've developed a hack to extract using the `.obj` to pull out the original data frame from the grouped data frame.
However, it would be helpful to have a method developed, which would do the extraction to prevent users from depending on my hack.
``` python
>>> dat_1 = df.groupby("category_2")
>>> dat_1
<pandas.core.groupby.generic.DataFrameGroupBy object at 0x7fce78b3dd00>
>>> dat_1.obj
order_date category_2 value
1 2011-02-01 Cross Country Race 324400.0
2 2011-03-01 Cross Country Race 142000.0
3 2011-04-01 Cross Country Race 498580.0
4 2011-05-01 Cross Country Race 220310.0
5 2011-06-01 Cross Country Race 364420.0
.. ... ... ...
535 2015-08-01 Triathalon 39200.0
536 2015-09-01 Triathalon 75600.0
537 2015-10-01 Triathalon 58600.0
538 2015-11-01 Triathalon 70050.0
539 2015-12-01 Triathalon 38600.0
[531 rows x 3 columns]
```
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https://api.github.com/repos/pandas-dev/pandas/issues/43903 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/43903/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/43903/comments | https://api.github.com/repos/pandas-dev/pandas/issues/43903/events | https://github.com/pandas-dev/pandas/issues/43903 | 1,019,235,313 | I_kwDOAA0YD848wEvx | 43,903 | BUG: cannot write xml with nullable dtypes | {
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] | open | false | null | [] | null | 1 | "2021-10-06T21:09:13Z" | "2021-11-20T17:20:38Z" | null | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import logging
import numpy as np
import pandas as pd
import pytest
logger = logging.getLogger("test")
class XmlTest:
def test_to_xml_dtypes(self):
dtypes = [
pd.StringDtype(),
pd.BooleanDtype(),
pd.Float64Dtype(),
pd.Float32Dtype(),
pd.Int64Dtype(),
pd.UInt64Dtype(),
pd.Int32Dtype(),
pd.UInt32Dtype(),
pd.Int16Dtype(),
pd.UInt16Dtype(),
pd.Int8Dtype(),
pd.UInt8Dtype(),
pd.StringDtype(),
]
data = [
pd.Series({"abc": 1, "xyz": pd.NA}),
pd.Series({"abc": pd.NA, "xyz": 0}),
]
failed = {}
for dtype in dtypes:
df = pd.DataFrame(data).astype(dtype)
try:
df.to_xml()
except TypeError as e:
logger.error(dtype, exc_info=True)
failed[str(dtype)] = str(e)
assert failed == [], f"Failed on dtypes: {failed}"
if __name__ == "__main__":
pytest.main()
```
### Issue Description
`to_xml` fails with nullable dtypes provided by Pandas like `Float64Dtype`. Example from a test run in CI; it fails on Ubuntu too.
### Expected Behavior
Output valid xml that can be read with `read_xml` to get approximately the same DataFrame.
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : f00ed8f47020034e752baf0250483053340971b0
python : 3.9.5.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19042
machine : AMD64
processor : Intel64 Family 6 Model 165 Stepping 2, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252
pandas : 1.3.0
numpy : 1.21.2
pytz : 2021.1
dateutil : 2.8.1
pip : 21.1.1
setuptools : 52.0.0.post20210125
Cython : None
pytest : 6.2.4
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.6.3
html5lib : 1.1
pymysql : 1.0.2
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : 4.9.3
bottleneck : None
fsspec : 2021.07.0
fastparquet : None
gcsfs : None
matplotlib : 3.4.2
numexpr : None
odfpy : None
openpyxl : 3.0.7
pandas_gbq : None
pyarrow : 5.0.0
pyxlsb : 1.0.8
s3fs : None
scipy : 1.7.0
sqlalchemy : None
tables : None
tabulate : 0.8.9
xarray : None
xlrd : 2.0.1
xlwt : None
numba : None
None
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- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
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Pandas currently only supports `searchsorted` for series:
```python
>>> ser = pd.Series([1, 2, 3])
>>> ser.searchsorted([0, 4])
array([0, 3])
```
It would be nice if it were also supported for dataframes, returning indices to maintain order in a lexicographically sorted dataframe. This is supported by cuDF:
```python
>>> df = cudf.DataFrame({"a" :[1, 1, 1, 2, 2, 2], "b": list(range(6))})
>>> values = cudf.DataFrame({"a": [1, 1, 2, 2], "b": [1, 2, 4, 6]})
>>> df.searchsorted(values, side="right")
array([2, 3, 5, 6], dtype=int32)
```
#### Describe the solution you'd like
The addition of a `searchsorted(value, ...)` method to `pandas.DataFrame`, returning the indices to places the elements of `values` to maintain order in a dataframe lexicographically sorted by _all_ columns.
#### API breaking implications
None that I can think of.
#### Describe alternatives you've considered
This could probably be accomplished by converting the dataframe and values to a series of tuples and then using `Series.searchsorted`, but I imagine there's a more performant way to do this.
#### Additional context
If this functionality were added, along with a multi-columnar `quantiles` (https://github.com/pandas-dev/pandas/issues/43881), it would enable Dask dataframes to compute `sort_values` with multiple sort-by columns, using an algorithm roughly similar to [that of dask-cudf](https://github.com/rapidsai/cudf/blob/ffb3814089c9a0c3c332d9a36714ab853a48ca9d/python/dask_cudf/dask_cudf/sorting.py#L208-L254).
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} | 2 | "2021-10-07T06:27:37Z" | "2021-10-15T18:15:44Z" | "2021-10-15T18:15:20Z" | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [ ] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
print(pd.__version__)
idx = pd.MultiIndex.from_tuples([(i, 1, (1, 1)) for i in range(5)])
print(pd.Series(range(5), index=idx).loc[(1, 1, (1, 1))])
```
### Issue Description
A Series with a MultiIndex where one level is a tuple cannot be indexed with `.loc[]`. Instead it raises `ValueError: Too many indices`:
```
~/src/pandas $ python test.py
1.3.3
Traceback (most recent call last):
File "test.py", line 6, in <module>
print(pd.Series(range(5), index=idx).loc[(1, 1, (1, 1))])
File "/home/andrea/src/pandas/venv/lib/python3.8/site-packages/pandas/core/indexing.py", line 925, in __getitem__
return self._getitem_tuple(key)
File "/home/andrea/src/pandas/venv/lib/python3.8/site-packages/pandas/core/indexing.py", line 1100, in _getitem_tuple
return self._getitem_lowerdim(tup)
File "/home/andrea/src/pandas/venv/lib/python3.8/site-packages/pandas/core/indexing.py", line 822, in _getitem_lowerdim
return self._getitem_nested_tuple(tup)
File "/home/andrea/src/pandas/venv/lib/python3.8/site-packages/pandas/core/indexing.py", line 881, in _getitem_nested_tuple
raise ValueError("Too many indices")
ValueError: Too many indices
```
### Expected Behavior
Up to v1.2.5 indexing works as expected to select the data:
```bash
~/src/pandas $ python test.py
1.2.5
1
```
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 73c68257545b5f8530b7044f56647bd2db92e2ba
python : 3.8.11.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.0-81-generic
Version : #91~18.04.1-Ubuntu SMP Fri Jul 23 13:36:29 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_SG.UTF-8
LOCALE : en_SG.UTF-8
pandas : 1.3.3
numpy : 1.21.2
pytz : 2021.3
dateutil : 2.8.2
pip : 21.1.1
setuptools : 56.0.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
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} | 1 | "2021-10-07T09:11:53Z" | "2021-10-17T22:35:35Z" | null | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [ ] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
shuffled = [3, 0, 1, 2]
sec = 1_000_000_000
df = pd.DataFrame([{'t': pd.Timestamp(2 * x * sec), 'x': x+1, 'c': 42} for x in shuffled])
# t x c
# 0 1970-01-01 00:00:06 4 42
# 1 1970-01-01 00:00:00 1 42
# 2 1970-01-01 00:00:02 2 42
# 3 1970-01-01 00:00:04 3 42
# Following row raises an Exception (as expected):
df.rolling(on='t', window='3s').x.sum()
# Following code should raise the same exception, but instead it gives meaningless results:
df.groupby('c').rolling(on='t', window='3s').x.sum()
# c t
# 42 1970-01-01 00:00:06 4.0
# 1970-01-01 00:00:00 1.0
# 1970-01-01 00:00:02 3.0
# 1970-01-01 00:00:04 6.0
```
### Issue Description
When calling `df.groupby(..).rolling(on='...', ...)` on some `Timestamp` column (with timedelta window) which is not sorted, pandas gives some meaningless results.
### Expected Behavior
An exception should be raised, as is the case when we call `df.rolling(on=...)` (without the `groupby`) on non-monotonic column
### Installed Versions
<details>
```
INSTALLED VERSIONS
------------------
commit : 73c68257545b5f8530b7044f56647bd2db92e2ba
python : 3.8.10.final.0
python-bits : 64
OS : Linux
OS-release : 5.11.0-37-generic
Version : #41~20.04.2-Ubuntu SMP Fri Sep 24 09:06:38 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.3.3
numpy : 1.21.2
pytz : 2021.1
dateutil : 2.8.2
pip : 21.2.3
setuptools : 45.2.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.5.0
html5lib : 1.0.1
pymysql : None
psycopg2 : None
jinja2 : 2.10.1
IPython : 7.13.0
pandas_datareader: None
bs4 : 4.8.2
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.7.1
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : 2.0.1
xlwt : None
numba : None
```
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} | 10 | "2021-10-07T14:02:11Z" | "2021-11-11T01:38:23Z" | "2021-10-09T00:18:23Z" | MEMBER | null | - [ ] xref #41935 (we should close after updating MacPython)
- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
This test seems to be leaking on Python 3.10, causing subsequent tests to fail with a cryptic and flaky error. Let's skip it.
This unblocks official Python 3.10 support.
I am not fixing the test since my first attempt at fixing the leakiness failed and I don't understand and don't have time to fix the problem.
If this works, we can revert #41990. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/43911 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/43911/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/43911/comments | https://api.github.com/repos/pandas-dev/pandas/issues/43911/events | https://github.com/pandas-dev/pandas/issues/43911 | 1,020,133,475 | I_kwDOAA0YD848zgBj | 43,911 | BUG: groupby().fillna does not return groupby key with the output | {
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- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [ ] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import numpy as np
import pandas as pd
df = pd.DataFrame({'group': ['A', 'A', 'A', 'B', 'B', 'B'], 'v': [4, 5, np.nan, 1, np.nan, 2 ]})
df2 = df.groupby(by=['group']).fillna(method='bfill')
```
### Issue Description
The variable `group` is completely missing from the output - it is neither a column of `df2` nor part of its index.
### Expected Behavior
Expected behavior would be to include the `group` variable either as a column or an index of the output dataframe. This was actually the behavior in previous versions of pandas.
### Installed Versions
INSTALLED VERSIONS
------------------
commit : 73c68257545b5f8530b7044f56647bd2db92e2ba
python : 3.8.8.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.17134
machine : AMD64
processor : Intel64 Family 6 Model 142 Stepping 10, GenuineIntel
byteorder : little
LC_ALL : None
LANG : en
LOCALE : English_United States.1252
pandas : 1.3.3
numpy : 1.20.3
pytz : 2021.1
dateutil : 2.8.2
pip : 21.0.1
setuptools : 58.0.4
Cython : 0.29.24
pytest : 6.2.4
hypothesis : None
sphinx : 4.2.0
blosc : None
feather : None
xlsxwriter : 3.0.1
lxml.etree : 4.6.3
html5lib : 1.1
pymysql : None
psycopg2 : 2.8.6 (dt dec pq3 ext lo64)
jinja2 : 2.11.3
IPython : 7.27.0
pandas_datareader: None
bs4 : 4.10.0
bottleneck : 1.3.2
fsspec : 2021.08.1
fastparquet : None
gcsfs : None
matplotlib : 3.4.2
numexpr : 2.7.3
odfpy : None
openpyxl : 3.0.9
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.7.1
sqlalchemy : 1.4.22
tables : 3.6.1
tabulate : None
xarray : None
xlrd : 2.0.1
xlwt : 1.3.0
numba : 0.53.1
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- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [x] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
from typing import get_type_hints
import pandas as pd
get_type_hints(pd.DataFrame)
```
### Issue Description
The example raises the following error:
```python
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/ben.fogelson/.pyenv/versions/3.9.7/lib/python3.9/typing.py", line 1437, in get_type_hints
value = _eval_type(value, base_globals, localns)
File "/Users/ben.fogelson/.pyenv/versions/3.9.7/lib/python3.9/typing.py", line 290, in _eval_type
return t._evaluate(globalns, localns, recursive_guard)
File "/Users/ben.fogelson/.pyenv/versions/3.9.7/lib/python3.9/typing.py", line 551, in _evaluate
eval(self.__forward_code__, globalns, localns),
File "<string>", line 1, in <module>
TypeError: unsupported operand type(s) for |: 'types.GenericAlias' and 'NoneType'
```
This error is still raised even if `from __future__ import annotations` is added at the beginning of the example.
### Expected Behavior
Expected to get type hints for `pd.DataFrame`.
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 73c68257545b5f8530b7044f56647bd2db92e2ba
python : 3.9.7.final.0
python-bits : 64
OS : Darwin
OS-release : 20.6.0
Version : Darwin Kernel Version 20.6.0: Mon Aug 30 06:12:21 PDT 2021; root:xnu-7195.141.6~3/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.3.3
numpy : 1.21.2
pytz : 2021.3
dateutil : 2.8.2
pip : 21.2.4
setuptools : 57.4.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
>>>
</details>
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} | 1 | "2021-10-07T16:46:10Z" | "2021-10-09T15:10:08Z" | null | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
df1 = pd.DataFrame()
df1[0] = pd.arrays.IntervalArray.from_tuples([(1.0, 2.0)])
df2 = pd.DataFrame()
df2[0] = pd.arrays.IntervalArray.from_tuples([(1.0000000000001, 2.0)])
# Using very large tolerances do not propagate to the interval dtype, since this assert fails:
pd.testing.assert_frame_equal(df1, df2, check_exact=False, rtol=10., atol=10.)
```
### Issue Description
It seems that `pd.testing.assert_frame_equal` does not propagate chosen tolerances for `interval` dtype comparison.
### Expected Behavior
df1 = pd.DataFrame()
df1[0] = pd.arrays.IntervalArray.from_tuples([(1.0, 2.0)])
df2 = pd.DataFrame()
df2[0] = pd.arrays.IntervalArray.from_tuples([(1.0000000000001, 2.0)])
# This test should pass...
pd.testing.assert_frame_equal(df1, df2, check_exact=False, rtol=10., atol=10.)
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 2cb96529396d93b46abab7bbc73a208e708c642e
python : 3.8.8.final.0
python-bits : 64
OS : Darwin
OS-release : 20.5.0
Version : Darwin Kernel Version 20.5.0: Sat May 8 05:10:33 PDT 2021; root:xnu-7195.121.3~9/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : fr_FR.UTF-8
LOCALE : fr_FR.UTF-8
pandas : 1.2.4
numpy : 1.20.1
pytz : 2021.1
dateutil : 2.8.1
pip : 21.0.1
setuptools : 52.0.0.post20210125
Cython : 0.29.23
pytest : 6.2.3
hypothesis : None
sphinx : 4.0.1
blosc : None
feather : None
xlsxwriter : 1.3.8
lxml.etree : 4.6.3
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 2.11.3
IPython : 7.22.0
pandas_datareader: None
bs4 : 4.9.3
bottleneck : 1.3.2
fsspec : 0.9.0
fastparquet : None
gcsfs : None
matplotlib : 3.3.4
numexpr : 2.7.3
odfpy : None
openpyxl : 3.0.7
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.6.2
sqlalchemy : 1.4.7
tables : 3.6.1
tabulate : None
xarray : None
xlrd : 2.0.1
xlwt : 1.3.0
numba : 0.53.1
</details>
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- [ ] tests added / passed
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} | 2 | "2021-10-07T20:44:32Z" | "2021-10-29T21:59:00Z" | "2021-10-29T21:58:56Z" | CONTRIBUTOR | null | - [ ] closes #32793
- [ ] tests added / passed
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} | 0 | "2021-10-07T20:54:24Z" | "2021-10-08T00:52:36Z" | "2021-10-07T23:54:28Z" | MEMBER | null | With this I think we cover all the main paths through IndexEngine.get_loc | {
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} | 0 | "2021-10-08T03:11:15Z" | "2021-10-09T00:17:40Z" | "2021-10-09T00:17:40Z" | MEMBER | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
idx = pd.NumericIndex([1.0, 2.0, 3.0] dtype='int32')
result = idx.insert(1, 4.0)
assert result.dtype == idx.dtype # <- nope!
```
```
### Issue Description
cc @topper-123
### Expected Behavior
Should preserve type and dtype
### Installed Versions
<details>
Replace this line with the output of pd.show_versions()
</details>
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} | 0 | "2021-10-08T03:14:41Z" | "2021-10-08T16:36:18Z" | "2021-10-08T12:31:13Z" | MEMBER | null | Test is unchanged, just moved to a class that isn't itself subclassed | {
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