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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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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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- [ ] 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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- [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 Follow up from #43741
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REF: add indices prop to sparse
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Future prs will use this more too, so figured adding it made sense
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"2021-10-30T15:10:19Z"
"2021-10-30T15:10:04Z"
CONTRIBUTOR
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- [ ] 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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BUG: test_equals_various failing locally with incorrect name
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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 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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CONTRIBUTOR
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[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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1,013,177,803
I_kwDOAA0YD848Y93L
43,831
BUG: using 2 character seperator in pd.json_normalize
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"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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43,832
QST: About the meaning of `~` used in `dfs = dfs.loc[:, ~dfs.columns.str.contains('^Unnamed', na=False)]`.
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"2021-10-01T13:52:22Z"
"2021-10-04T04:10:05Z"
"2021-10-01T14:35:53Z"
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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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update fix ignored sort in api.py and add test
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- [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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TYP: Fix typing of frame.explode
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cc @simonjayhawkins
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ENH: rolling() for discontinuous time series data
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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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ENH: Should `pandas.CategoricalDtype` use `pandas.NA` as the sentinel value instead of `float('nan')` ?
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"2021-10-01T14:56:09Z"
"2021-10-02T00:50:02Z"
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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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ENH: `DataFrame.astype(dtype: dict)` should work in the presence of superfluous keys.
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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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BUG: Named aggregations do not work together with unnamed ones
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"2021-10-03T16:38:39Z"
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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 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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DOC: DataFrame.groupby() includes no mention of some important functionality
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"2021-10-04T15:55:49Z"
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### - [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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REF: Series.argsort should dispatch to EA.argsort
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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 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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Backport PR #43834 on branch 1.3.x (TYP: Fix typing of frame.explode)
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Backport PR #43834: TYP: Fix typing of frame.explode
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BUG: unhashable type error produced by pandas query
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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] closes #29282 - [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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CONTRIBUTOR
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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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Upcoming PR will expand maybe_dispatch_ufunc_to_dunder_op to include unary methods, so this is needed to prevent circularity.
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REF: dont use np.abs in NDFrame.__abs__
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"2021-10-01T23:21:03Z"
"2021-10-03T18:06:28Z"
"2021-10-03T17:08:40Z"
MEMBER
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Same as #43846 but for NDFrame Moves `abs` to be adjacent to `__abs__`.
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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 - [ ] whatsnew entry
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- [ ] 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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- [x] closes #40661 - [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 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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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 - [x] whatsnew entry
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[ENH] MultiIndex: astype dict
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astype multiindex with dict-like of names/int names index with pandas dtype - [ ] 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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"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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MEMBER
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- [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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TYP: make IOHandles generic
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"2021-11-14T16:38:12Z"
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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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REF: implement helpers for __array_ufunc__
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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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1,014,292,662
I_kwDOAA0YD848dOC2
43,857
ENH: Index Pandas Dtype
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null
1
"2021-10-03T07:14:22Z"
"2021-10-03T13:57:45Z"
"2021-10-03T13:57:45Z"
NONE
null
Hello, 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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1,014,398,681
I_kwDOAA0YD848dn7Z
43,858
BUG: read_parquet use a lot of memory
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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/43859
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https://github.com/pandas-dev/pandas/pull/43859
1,014,402,048
PR_kwDOAA0YD84smouV
43,859
Backport PR #43854 on branch 1.3.x (REGR: RollingGroupby.corr producing incorrect results)
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Backport PR #43854: REGR: RollingGroupby.corr producing incorrect results
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[ENH] to_orc
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Add pandas.io.orc.to_orc method definition
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Update README.md
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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 - [ ] whatsnew entry
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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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BUG/ERR: sparse array cmp methods mismatched len
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"2021-10-17T23:40:25Z"
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Hello, Is it possible to add to_orc method to pandas.DataFrame, from pyarrow 4.0.0 ? Br Nicolas
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TYP: type insert and nsmallest/largest
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"2021-10-20T19:49:17Z"
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MEMBER
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cc @simonjayhawkins Could you have a look and give some feedback if this is ok so?
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Add clarifications to the docs regarding `to_feather`
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"2021-10-07T12:58:29Z"
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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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BUG: `DataFrame.equals` returns `True` when compared elements differ in being `np.array`s
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"2021-10-13T03:10:26Z"
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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 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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BUG: Series[object].__setitem__(ndarray[M8ns]_with_matching_size)
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- [ ] 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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BUG: get_indexer_non_unique does not handle np.datetime64("NaT") and np.timedelta64("NaT")
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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 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 </details>
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Add deprecation tag for passing a string for ewm(times=...)
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"2021-10-04T12:07:41Z"
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Missed as part of https://github.com/pandas-dev/pandas/pull/43265
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ENH: Deprecate DataFrame.iterrows
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#### Is your feature request related to a problem? 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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ENH: Add option to display dtypes below column headers
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#### 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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BUILD: conda unable to solve for a dev env using environment.yml in finite time
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CONTRIBUTOR
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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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### - [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: ![mem_prof](https://user-images.githubusercontent.com/52132110/135826330-9c5f11b3-d600-472f-924c-9755a86f30de.png) 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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BUG: Pandas converts int to float while reading from database if column has Null in it
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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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-added unittest for issue #43599 -error occurs due to different versions of pandas
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- [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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ENH: Add support for multi-column quantiles of DataFrame
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#### 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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BUG: retain EA dtypes in DataFrame __pos__, __neg__
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MEMBER
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- [ ] 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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BUG: sort_index method ignores ascending parameter of type tuple
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"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 xlrd : None xlwt : None numba : None
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PERF: `Index.union` is materializing even when it is not needed when `sort=False`
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"2021-10-13T02:24:47Z"
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### - [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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API/DISC: engine="numba" (computational API) location in reductions functions or constructors
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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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BUG: pd.array preserve PandasArray
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- [ ] 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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PERF: Slow import-time expression slowing down test collection
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### - [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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ENH: `axis=None` option for statistical methods: `.min`, `.max`, `.median`, and so on
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"2021-10-21T21:30:05Z"
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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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CI: Move Python 3.10 workflows to Posix Matrix File
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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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BUG: Groupby with categorical multiIndex and timedelta returns incorrect type.
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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 numexpr : 2.7.3 odfpy : None openpyxl : None pandas_gbq : None pyarrow : None pyxlsb : None s3fs : None scipy : 1.7.1 sqlalchemy : 1.3.24 tables : 3.6.1 tabulate : 0.8.9 xarray : 0.19.0 xlrd : 2.0.1 xlwt : None numba : 0.54.0
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I_kwDOAA0YD848l0Au
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BUG: DateOffset with nanoseconds does not apply to Timestamp
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"2021-10-05T16:44:01Z"
"2021-10-16T14:43:22Z"
null
NONE
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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 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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Annotates `indexers/utils.py` functions that don't return anything with `None`
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"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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ENH: Add custom descriptors (such as dtype, nunique, etc.) to Styler output
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CONTRIBUTOR
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- [x] closes: #43875 ![Screen Shot 2021-10-24 at 08 52 28](https://user-images.githubusercontent.com/24256554/138583994-6a8debd6-6b8a-4fbb-a697-536b5a6b3590.png) <details> <summary>Former example...</summary> ![Screen Shot 2021-10-05 at 23 37 31](https://user-images.githubusercontent.com/24256554/136106494-c770db25-5598-4a6b-8708-1d2654eac8e1.png) </details>
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REF: remove _get_attributes_dict
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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 - [ ] whatsnew entry
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BUG: bug in DataFrame.groupby(Grouper) triggers a ValueError exception in cython generate_bins_dt64() code
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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 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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BUG: DataFrame arithmetic with subclass where constructor is not the subclass itself
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- [x] closes #43201 - [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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- [x] closes #43888
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"2021-10-06T18:36:02Z"
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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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"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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"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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ENH: Feature Request for Ungroup Method for Grouped Data Frames
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"2021-10-13T04:01:08Z"
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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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BUG: cannot write xml with nullable dtypes
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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 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 </details>
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Very little user-facing here, AFAICT just the iadd/isub bug in DTA/TDA
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#### Is your feature request related to a problem? 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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BUG: `.loc[]` on Series with MultiIndex raises "ValueError: Too many indices" if one level is a tuple
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"2021-10-15T18:15:44Z"
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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 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 </details>
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BUG: Using `df.groupby(..).rolling(..)` on non-monotonic timestamp column does not raise an exception
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"2021-10-17T22:35:35Z"
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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 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 ``` </details>
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TST: Skip leaky test on Python 3.10
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- [ ] 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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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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BUG: typing.get_type_hints fails on DataFrame
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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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BUG: `pd.testing.assert_frame_equal` does not propagate precision to interval dtype
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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 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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TST/REF: collect/de-dup index tests
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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 - [ ] whatsnew entry
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TST : add test for groupby aggregation dtype
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"2021-10-29T21:59:00Z"
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CONTRIBUTOR
null
- [ ] closes #32793 - [ ] 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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BENCH: indexing_engines
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MEMBER
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With this I think we cover all the main paths through IndexEngine.get_loc
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BUG: np.isinf, np.isfinite, np.isnan with DTI[dt64tz]
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TST/REF: fixturize
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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 - [ ] whatsnew entry
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Prelim for EA-backed Index.
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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 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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Test is unchanged, just moved to a class that isn't itself subclassed
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