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DataFrame.rolling documentation of method='table'
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- [X] closes #40374 - [x] tests added / passed - [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
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simple misspelling fix. From "counties" to "countries" - [ ] closes #xxxx - [ ] tests added / passed - [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them - [ ] whatsnew entry
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DOC/TYP: index.take return val
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MEMBER
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xref https://github.com/pandas-dev/pandas/pull/40513#discussion_r597541594
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QST: Comments and feedback on rolling own dataframe functionality and syntax?
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- [x] I have searched the [[pandas] tag](https://stackoverflow.com/questions/tagged/pandas) on StackOverflow for similar questions. - [ ] I have asked my usage related question on [StackOverflow](https://stackoverflow.com). --- #### Question about pandas I want to roll my own dataframe functionality and syntax. Below is an example with a ternary-like operator **Example A:** Let's say I want to set ‘row_A’ equal to 5 if ‘row_B’ is 10. Right now, this has to be written like this: `df.loc[df.row_1 == ‘10’, 'row_1'] = 5 ` But I want this to work: ` df.row_A = 5 if row_B = 10 ` My question is, is it feasible possible to add / overload the functionality implied? Has anyone tried this? Example A above would just be the beginning. While subjective, I think this deals with a large class of "not quite" esoteric operations, that are in fact arcane and esoteric to execute concisely in Pandas. Note that I’m in principle happy to share / learn / complement / accept someone else's implementation too. Please let me know if this is insanity.
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CONTRIBUTOR
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For example: `Duplicate explicit target name: "user guide"` I was seeing these warnings in the dask docs build because dask pulls docstrings from pandas. I think using anonomous links like this should fix it based on https://github.com/sphinx-doc/sphinx/issues/3921
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"2021-03-23T16:36:18Z"
"2021-03-23T16:35:07Z"
MEMBER
null
The way we pass state back and forth is a bit nutty, punting on that.
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BUG: to_json failing on PyPy
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- [x] closes #39837 - [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them - [x] whatsnew entry Not sure how best to test this - confirmed this now works when run on PyPy, but since we don't test against PyPy the examples in the issue (or any other simple case) which fail on PyPy will still pass on master. Benchmarks look similar, might be minor performance improvement for the single block case: ``` before after ratio [b524462e] [b1f4bcc8] <master> <bug/is_mixed_type> 194±5ms 190±2ms 0.98 io.json.ToJSONISO.time_iso_format('columns') 208±5ms 198±6ms 0.95 io.json.ToJSONISO.time_iso_format('index') 186±4ms 173±3ms 0.93 io.json.ToJSONISO.time_iso_format('records') 193±10ms 187±3ms 0.97 io.json.ToJSONISO.time_iso_format('split') 164±4ms 165±3ms 1.00 io.json.ToJSONISO.time_iso_format('values') 115±4ms 114±3ms 0.99 io.json.ToJSONLines.time_delta_int_tstamp_lines 142±4ms 132±6ms 0.93 io.json.ToJSONLines.time_float_int_lines 140±4ms 142±4ms 1.02 io.json.ToJSONLines.time_float_int_str_lines 152±2ms 153±3ms 1.01 io.json.ToJSONLines.time_float_longint_str_lines 110±3ms 107±3ms 0.97 io.json.ToJSONLines.time_floats_with_dt_index_lines 112±3ms 104±3ms 0.93 io.json.ToJSONLines.time_floats_with_int_idex_lines 54.3M 55M 1.01 io.json.ToJSONMem.peakmem_float 55.4M 55.2M 1.00 io.json.ToJSONMem.peakmem_int 88.6±2ms 78.8±2ms 0.89 io.json.ToJSON.time_to_json('index', 'df') 70.7±2ms 61.7±2ms 0.87 io.json.ToJSON.time_to_json('values', 'df') 94.9±3ms 81.4±1ms 0.86 io.json.ToJSON.time_to_json('index', 'df_date_idx') 76.3±0.9ms 65.1±1ms 0.85 io.json.ToJSON.time_to_json('records', 'df_date_idx') ```
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REF: share external_values ArrayManager/BlockManager
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0
"2021-03-20T03:52:13Z"
"2021-03-22T14:24:10Z"
"2021-03-22T13:07:03Z"
MEMBER
null
- [ ] closes #xxxx - [ ] tests added / passed - [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them - [ ] whatsnew entry
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40,530
CI: testing wip branch on ci.
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3
"2021-03-20T10:06:07Z"
"2021-03-21T14:34:41Z"
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MEMBER
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No need to review. will be closing to clear the queue later today.
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TYP use typed version of namedtuple
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7
"2021-03-20T12:27:07Z"
"2021-08-19T11:42:38Z"
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MEMBER
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Instead of ```python OutputKey = collections.namedtuple("OutputKey", ["label", "position"]) ``` we can do ```python from typing import NamedTuple class OutputKey(NamedTuple) label position ``` The advantage is that like this we can add type hints to the various elements, such as ```python from typing import NamedTuple class OutputKey(NamedTuple) label: Hashable position: int ``` ----- See https://docs.python.org/3/library/typing.html#typing.NamedTuple for reference
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MDExOlB1bGxSZXF1ZXN0NTk3MjcyNzcx
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STYLE loosen inconsistent namespace check
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5
"2021-03-20T12:29:02Z"
"2021-04-02T16:30:17Z"
"2021-04-02T14:50:54Z"
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For context, see #40468, where the error which was fixed was arguably a false-positive. I've loosened the check so that now it only errors / replaces if: - you imported an object from somewhere in pandas `e.g. from pandas.io.formats import info` - you also accessed that object as `pd.` or `pandas.` (e.g. `pd.info` or `pandas.info`) Before, it just checked whether an object appeared both with and without the `pd.` prefix, which was too tight a check - sorry about that :flushed: I've also added line number and column offset of the inconsistency for ease of checking/fixing
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Use from __future__ import annotations (almost?) everywhere?
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14
"2021-03-20T12:45:37Z"
"2021-04-13T12:13:36Z"
"2021-04-13T12:13:36Z"
MEMBER
null
This means we can address > type hints are executed at module import time, which is not computationally free. (from https://www.python.org/dev/peps/pep-0563/), as well as use the more modern syntax of Python ---- This is easy to automate, just checking there's no downsides to putting this everywhere. Should any files (probably `__init__.py`, any others?) be excluded? cc @simonjayhawkins
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CLN: Optional[Hashable] in dict type hints
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5
"2021-03-20T14:40:45Z"
"2021-03-23T10:10:17Z"
"2021-03-23T01:33:04Z"
CONTRIBUTOR
null
Minor clean-up. ```python >>> from typing import Hashable >>> isinstance(None, Hashable) True ``` In old versions of mypy, mypy had a bug and didn't see this, but is has been fixed now. There are many instances of `Optional[Hashable]` instead of just `Hashable` in the code base, other than in these dicts. I've assumed those should be left as-is for readability and not because it's strictly needed.
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1
"2021-03-20T14:57:52Z"
"2021-03-23T17:08:08Z"
"2021-03-23T16:23:02Z"
CONTRIBUTOR
null
Typing of `first_valid_index` & `last_valid_index` + make the `how` param in internal functions a named parameter for better readability.
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REF: move shift logic from BlockManager to DataFrame
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3
"2021-03-20T15:07:43Z"
"2021-06-26T07:44:15Z"
"2021-03-23T16:47:15Z"
MEMBER
null
Partially-fixes one of the currently-disabled ArrayManager tests.
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Revert "CLN: intp_t instead of int64_t for indexers in libs funcs"
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"2021-03-20T15:19:09Z"
"2021-03-20T18:18:33Z"
"2021-03-20T18:18:30Z"
MEMBER
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Reverts pandas-dev/pandas#40475 Looks like some combination of this, #40474, #40476 are resposible for broken CI. Trying this one first.
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1
"2021-03-20T16:11:26Z"
"2021-03-22T11:58:59Z"
"2021-03-21T21:00:40Z"
CONTRIBUTOR
null
From #39501 splitting out the part to make the EA `registry` private. This will make it so that `pyright --verifytypes` accepts pandas public API.
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API: Allow partial failure with TypeError in agg with dict-like arguments
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"2021-03-20T16:14:30Z"
"2021-08-19T02:47:56Z"
null
MEMBER
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With `df = pd.DataFrame({'a': [1, 2], 'b': [3, 4]})`, my expectation is that: df.agg([func]) df.agg({'a': func, 'b': func}) Behave the same. However, the former allows partial failure when a TypeError is raised, whereas the latter does not. Similarly with groupby as well. While I'd like to focus this issue on just agg with list/dict-likes, comparisons for all frame/series, agg/transform, list/dict with functions that raise ValueError/TypeError combinations are below. <details><summary>Results</summary> ``` Series <class 'ValueError'> .agg with dict: raised ValueError() .agg with list: raised ValueError() .transform with dict: partial failure allowed .transform with list: partial failure allowed groupby(...).agg with dict: raised SpecificationError('nested renamer is not supported') groupby(...).agg with list: raised ValueError() groupby(...).transform with dict: raised TypeError("unhashable type: 'dict'") groupby(...).transform with list: raised TypeError("unhashable type: 'list'") Frame <class 'ValueError'> .agg with dict: raised ValueError() .agg with list: raised ValueError() .transform with dict: partial failure allowed .transform with list: partial failure allowed groupby(...).agg with dict: raised ValueError() groupby(...).agg with list: raised ValueError() groupby(...).transform with dict: raised TypeError("unhashable type: 'dict'") groupby(...).transform with list: raised TypeError("unhashable type: 'list'") Series <class 'TypeError'> .agg with dict: raised TypeError() .agg with list: partial failure allowed .transform with dict: partial failure allowed .transform with list: partial failure allowed groupby(...).agg with dict: raised SpecificationError('nested renamer is not supported') groupby(...).agg with list: raised TypeError() groupby(...).transform with dict: raised TypeError("unhashable type: 'dict'") groupby(...).transform with list: raised TypeError("unhashable type: 'list'") Frame <class 'TypeError'> .agg with dict: raised TypeError('DataFrame constructor called with incompatible data and dtype: ') .agg with list: partial failure allowed .transform with dict: partial failure allowed .transform with list: partial failure allowed groupby(...).agg with dict: raised TypeError() groupby(...).agg with list: partial failure allowed groupby(...).transform with dict: raised TypeError("unhashable type: 'dict'") groupby(...).transform with list: raised TypeError("unhashable type: 'list'") ``` </details> <details><summary>Code</summary> ``` def run_series(err_klass): def failop(x): raise err_klass def passop_agg(x): return x.sum() def passop_transform(x): return x ser = pd.Series([1, 2]) print('Series', err_klass) args = it.product((False, True), ('agg', 'transform'), (False, True)) for use_gb, method, is_list in args: obj = ser.groupby(level=0) if use_gb else ser op = passop_transform if method == 'transform' else passop_agg func = [failop, op] if is_list else {'a': failop, 'b': op} try: getattr(obj, method)(func) result = 'partial failure allowed' except Exception as err: result = f'raised {repr(err)}' print( f' {"groupby(...)" if use_gb else ""}.{method} ' f'{"with list" if is_list else "with dict"}: {result}' ) print() def run_frame(err_klass): def op_agg(x): if x.sum().sum() < 100: raise err_klass return x.sum() def op_transform(x): if x.sum().sum() < 100: raise err_klass return x df = pd.DataFrame({'a': [1, 2], 'b': [100, 200]}) print('Frame', err_klass) args = it.product((False, True), ('agg', 'transform'), (False, True)) for use_gb, method, is_list in args: obj = df.groupby(level=0) if use_gb else df op = op_transform if method == 'transform' else op_agg func = [op] if is_list else {'a': op, 'b': op} try: getattr(obj, method)(func) result = 'partial failure allowed' except Exception as err: result = f'raised {repr(err)}' print( f' {"groupby(...)" if use_gb else ""}.{method} ' f'{"with list" if is_list else "with dict"}: {result}' ) print() run_series(ValueError) run_frame(ValueError) run_series(TypeError) run_frame(TypeError) ``` </details>
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TYP: make typing DatetimeLikeScalar a Union instead of TypeVar
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"2021-03-20T16:21:51Z"
"2021-03-22T11:59:32Z"
"2021-03-21T21:01:24Z"
CONTRIBUTOR
null
In `_typing.py` change `DatetimeLikeScalar` from `TypeVar` to `Union` Allows removal of 4 `#type: ignore` lines Per split out from #39501
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40,541
Revert "PERF: increase the minimum number of elements to use numexpr for ops from 1e4 to 1e6"
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MEMBER
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Reverts pandas-dev/pandas#40502 Troubleshooting the CI
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DOC: suppress warnings from CategoricalBlock deprecation
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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.html#code-standards) for how to run them - [ ] whatsnew entry
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- [x] tests added / passed - [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them Ref: #34224. Back when transform and agg shared code, this was introduced to stop transform from having an infinite recursive loop. Now they do not, it is no longer necessary and only serves to obfusticate the error message.
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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.html#code-standards) for how to run them - [ ] whatsnew entry
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TYP: mostly core.arrays, some core.indexes
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CLN: rank_1d
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MEMBER
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Long overdue followup to #38744. Only half the diff is relevant since the changes are duplicated over the if rank_t is object... else with no_gil... structure.
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CLN: remove unreachable quantile code
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TST: `test_tooltip.py` convert to functional tests instead of class
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- [x] adds `pytest.fixture` instead of Class setup method. - [x] removes `test_tooltip_reindex` since it is already being tested by `test_tooltip_render` - [x] other tests no changes except adopting fixtures
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1
"2021-03-21T08:57:15Z"
"2021-03-23T16:24:49Z"
"2021-03-23T16:13:15Z"
CONTRIBUTOR
null
- [x] add `pytest.fixture` instead of Class setup method - [x] no test removed or added, just amended to accept new fixtures
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DOC: Fix minimum Python version in contributing docs
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7
"2021-03-21T10:16:35Z"
"2021-04-04T19:59:26Z"
"2021-04-04T19:57:20Z"
CONTRIBUTOR
null
- [x] closes #40485
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CLN: Remove unnecessary code in docs/make.py
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2
"2021-03-21T11:51:37Z"
"2021-03-23T16:12:24Z"
"2021-03-23T16:12:20Z"
CONTRIBUTOR
null
Simple cleaning in docs/make.py. `include_api = False` in the if block doesn't have any effect.
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ENH: Non-nullable extension types
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"2021-05-25T00:37:28Z"
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NONE
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As far as I can tell, all custom extension types are nullable. It would be useful to provide a way to create non-nullable extensions. One way to support this could be by setting the `na_value` attribute to `NotImplemented`. Thoughts?
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BUG: Fix behavior of replace_list with mixed types.
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"2021-06-01T13:05:04Z"
"2021-06-01T12:36:36Z"
CONTRIBUTOR
null
- [x] closes #40371 - [x] tests added / passed - [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them - [ ] whatsnew entry
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24
"2021-03-21T16:07:22Z"
"2021-05-03T19:07:13Z"
"2021-05-03T17:31:13Z"
CONTRIBUTOR
null
- [x] xref, but is first step in implementing #36893 - [x] tests added and passed - [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them - [x] whatsnew entry (in the docstring) - [ ] whatsnew entry (in the docs) This is the first step in implementing an `engine` backend to the SQL I/O functions, as discussed in #36893. This PR is simply to refactor the existing SQLAlchemy parts to make them extensible for an external engine. No new engines were added at this stage. No new tests were added, only verified that existing tests fail ("test behavior, not implementation" suggests that we don't need to test internal refactoring) Lots of the code was borrowed from the Parquet I/O implementation.
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40,557
TST: add test_ffill_with_string_column
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"2021-05-13T23:27:48Z"
"2021-05-13T23:27:45Z"
CONTRIBUTOR
null
- [x] closes #40250 - [x] tests added / passed - [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them - [ ] whatsnew entry #40250 is an issue which seems to have been fixed in master already through #39446. This PR adds a test for this issue.
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DOC: Pip environment should explain how to handle prerequisites for the `pytables` dependancy.
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"2021-03-21T20:19:08Z"
"2021-05-16T08:33:45Z"
"2021-05-16T08:33:45Z"
NONE
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#### Location of the documentation https://pandas.pydata.org/pandas-docs/stable/development/contributing.html#creating-a-python-environment-pip #### Documentation problem Requirements file fails to install if prerequisites for the pytables package are not met. As far as I can tell these instructions will fail if you don't have [HDF5](https://www.hdfgroup.org/solutions/hdf5/) installed already. This following line returns an error: ``` python -m pip install -r requirements-dev.txt ``` Click below for Windows Powershell Error trace: <details> <!-- do not delete the following blank line --> ```sh Collecting tables>=3.5.1 Using cached tables-3.6.1.tar.gz (4.6 MB) ERROR: Command errored out with exit status 1: command: 'C:\Users\ferga\virtualenvs\pandas-dev\Scripts\python.exe' -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'C:\\Users\\ferga\\AppData\\Local\\Temp\\pip-install-z88l7dtf\\tables_ad6031c18d884368946e8601e5e6b83a\\setup.py'"'"'; __file__='"'"'C:\\Users\\ferga\\AppData\\Local\\Temp\\pip-install-z88l7dtf\\tables_ad6031c18d884368946e8601e5e6b83a\\setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' egg_info --egg-base 'C:\Users\ferga\AppData\Local\Temp\pip-pip-egg-info-_f3hgzqo' cwd: C:\Users\ferga\AppData\Local\Temp\pip-install-z88l7dtf\tables_ad6031c18d884368946e8601e5e6b83a\ Complete output (9 lines): H5closet5cs0mu2.c C:\Users\ferga\AppData\Local\Temp\H5closet5cs0mu2.c(2): warning C4013: 'H5close' undefined; assuming extern returning int LINK : fatal error LNK1181: cannot open input file 'hdf5.lib' * Using Python 3.9.2 (tags/v3.9.2:1a79785, Feb 19 2021, 13:44:55) [MSC v.1928 64 bit (AMD64)] * USE_PKGCONFIG: False .. ERROR:: Could not find a local HDF5 installation. You may need to explicitly state where your local HDF5 headers and library can be found by setting the ``HDF5_DIR`` environment variable or by using the ``--hdf5`` command-line option. ---------------------------------------- WARNING: Discarding https://files.pythonhosted.org/packages/2b/32/847ee3f521aae6a0be380d923a736162d698586f444df1ac24b98c65025c/tables-3.6.1.tar.gz#sha256=49a972b8a7c27a8a173aeb05f67acb45fe608b64cd8e9fa667c0962a60b71b49 (from https://pypi.org/simple/tables/) (requires-python:>=3.5). Command errored out with exit status 1: python setup.py egg_info Check the logs for full command output. Downloading tables-3.5.2.tar.gz (7.8 MB) |████████████████████████████████| 7.8 MB 2.2 MB/s ERROR: Command errored out with exit status 1: command: 'C:\Users\ferga\virtualenvs\pandas-dev\Scripts\python.exe' -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'C:\\Users\\ferga\\AppData\\Local\\Temp\\pip-install-z88l7dtf\\tables_ecb0a9038fe14c25bf054f52525e8223\\setup.py'"'"'; __file__='"'"'C:\\Users\\ferga\\AppData\\Local\\Temp\\pip-install-z88l7dtf\\tables_ecb0a9038fe14c25bf054f52525e8223\\setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' egg_info --egg-base 'C:\Users\ferga\AppData\Local\Temp\pip-pip-egg-info-695w_dt8' cwd: C:\Users\ferga\AppData\Local\Temp\pip-install-z88l7dtf\tables_ecb0a9038fe14c25bf054f52525e8223\ Complete output (9 lines): H5close0vbr0smy.c C:\Users\ferga\AppData\Local\Temp\H5close0vbr0smy.c(2): warning C4013: 'H5close' undefined; assuming extern returning int LINK : fatal error LNK1181: cannot open input file 'hdf5.lib' * Using Python 3.9.2 (tags/v3.9.2:1a79785, Feb 19 2021, 13:44:55) [MSC v.1928 64 bit (AMD64)] * USE_PKGCONFIG: False .. ERROR:: Could not find a local HDF5 installation. You may need to explicitly state where your local HDF5 headers and library can be found by setting the ``HDF5_DIR`` environment variable or by using the ``--hdf5`` command-line option. ---------------------------------------- WARNING: Discarding https://files.pythonhosted.org/packages/73/51/6dabb2b94826e5db3aa2542b80f1382780b96a0cd13e0cfb637b36ede5c5/tables-3.5.2.tar.gz#sha256=b220e32262bab320aa41d33125a7851ff898be97c0de30b456247508e2cc33c2 (from https://pypi.org/simple/tables/). Command errored out with exit status 1: python setup.py egg_info Check the logs for full command output. Downloading tables-3.5.1.tar.gz (8.3 MB) |████████████████████████████████| 8.3 MB 3.3 MB/s ERROR: Command errored out with exit status 1: command: 'C:\Users\ferga\virtualenvs\pandas-dev\Scripts\python.exe' -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'C:\\Users\\ferga\\AppData\\Local\\Temp\\pip-install-z88l7dtf\\tables_cd421b0f0e7a4033b8cbd6af4ac8c022\\setup.py'"'"'; __file__='"'"'C:\\Users\\ferga\\AppData\\Local\\Temp\\pip-install-z88l7dtf\\tables_cd421b0f0e7a4033b8cbd6af4ac8c022\\setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' egg_info --egg-base 'C:\Users\ferga\AppData\Local\Temp\pip-pip-egg-info-r8d5q3it' cwd: C:\Users\ferga\AppData\Local\Temp\pip-install-z88l7dtf\tables_cd421b0f0e7a4033b8cbd6af4ac8c022\ Complete output (9 lines): H5close0scl0_1r.c C:\Users\ferga\AppData\Local\Temp\H5close0scl0_1r.c(2): warning C4013: 'H5close' undefined; assuming extern returning int LINK : fatal error LNK1181: cannot open input file 'hdf5.lib' * Using Python 3.9.2 (tags/v3.9.2:1a79785, Feb 19 2021, 13:44:55) [MSC v.1928 64 bit (AMD64)] * USE_PKGCONFIG: False .. ERROR:: Could not find a local HDF5 installation. You may need to explicitly state where your local HDF5 headers and library can be found by setting the ``HDF5_DIR`` environment variable or by using the ``--hdf5`` command-line option. ---------------------------------------- WARNING: Discarding https://files.pythonhosted.org/packages/c6/e6/38cdcdc501ff889ea1e60bd5ef61d0573f73606f4dd0169786fd991c6b70/tables-3.5.1.tar.gz#sha256=88e2f3be1f143febc8bf8a7fe49ad51fc12518d6a1ac4eb641778d93e5dc2039 (from https://pypi.org/simple/tables/). Command errored out with exit status 1: python setup.py egg_info Check the logs for full command output. ERROR: Could not find a version that satisfies the requirement tables>=3.5.1 ERROR: No matching distribution found for tables>=3.5.1 ``` </details> #### Suggested fix for documentation One or more of the following: * Explain the issue and link to [pytables documentation](http://www.pytables.org/usersguide/installation.html#prerequisites) where prerequisites are explained. * Update instructions with steps to install pytables prerequisites
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40,559
REF/PERF: deduplicate kth_smallest
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"2021-03-23T16:18:52Z"
"2021-03-23T16:10:30Z"
MEMBER
null
Ensuring a contiguous input seems to give about a 5-10% performance improvement on the existing benchmark `gil.ParallelKth`
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DOC: inconsistency in doc argument types
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"2021-06-12T11:41:01Z"
"2021-06-12T10:21:22Z"
CONTRIBUTOR
null
This is not exactly right, but we have an inconsitency in the argument specifications of using 'array_like' vs 'array-like', in argument types we should settle on one (prob 'array-like') ``` (pandas-dev) ~/pandas$ grep -r array-like --include '*.py' pandas|wc 317 2259 24072 (pandas-dev) ~/pandas$ grep -r array_like --include '*.py' pandas|wc 104 498 7414 ``` Similar to this ``` pandas/plotting/_core.py: yerr : DataFrame, Series, array-like, dict and str ```
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CLN: remove unused axis keyword from Block.where
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MEMBER
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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.html#code-standards) for how to run them - [ ] whatsnew entry
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null
- [X] closes #39987 - [X] tests added / passed - [X] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them - [X] whatsnew entry
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BUG: Fix query doesn't support equals or not equals with Python parse…
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CONTRIBUTOR
null
…r (#40436) - [X] closes #40436 - [X] tests added / passed - [X] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them - [X] whatsnew entry
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"2021-03-22T10:49:55Z"
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CONTRIBUTOR
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<!-- START pr-commits --> <!-- END pr-commits --> ## Base PullRequest default branch (https://github.com/pandas-dev/pandas/tree/master) ## Command results <details> <summary>Details: </summary> <details> <summary><em>add path</em></summary> ```Shell /home/runner/work/_actions/technote-space/create-pr-action/v2/node_modules/npm-check-updates/bin ``` </details> <details> <summary><em>pip install pre-commit</em></summary> ```Shell Collecting pre-commit Downloading pre_commit-2.11.1-py2.py3-none-any.whl (187 kB) Collecting identify>=1.0.0 Downloading identify-2.2.0-py2.py3-none-any.whl (98 kB) Collecting toml Using cached toml-0.10.2-py2.py3-none-any.whl (16 kB) Collecting cfgv>=2.0.0 Using cached cfgv-3.2.0-py2.py3-none-any.whl (7.3 kB) Collecting nodeenv>=0.11.1 Using cached nodeenv-1.5.0-py2.py3-none-any.whl (21 kB) Collecting virtualenv>=20.0.8 Downloading virtualenv-20.4.3-py2.py3-none-any.whl (7.2 MB) Collecting pyyaml>=5.1 Downloading PyYAML-5.4.1-cp39-cp39-manylinux1_x86_64.whl (630 kB) Collecting filelock<4,>=3.0.0 Using cached filelock-3.0.12-py3-none-any.whl (7.6 kB) Collecting distlib<1,>=0.3.1 Using cached distlib-0.3.1-py2.py3-none-any.whl (335 kB) Collecting six<2,>=1.9.0 Using cached six-1.15.0-py2.py3-none-any.whl (10 kB) Collecting appdirs<2,>=1.4.3 Using cached appdirs-1.4.4-py2.py3-none-any.whl (9.6 kB) Installing collected packages: six, filelock, distlib, appdirs, virtualenv, toml, pyyaml, nodeenv, identify, cfgv, pre-commit Successfully installed appdirs-1.4.4 cfgv-3.2.0 distlib-0.3.1 filelock-3.0.12 identify-2.2.0 nodeenv-1.5.0 pre-commit-2.11.1 pyyaml-5.4.1 six-1.15.0 toml-0.10.2 virtualenv-20.4.3 ``` </details> <details> <summary><em>pre-commit autoupdate || (exit 0);</em></summary> ```Shell Updating https://github.com/MarcoGorelli/absolufy-imports ... [INFO] Initializing environment for https://github.com/MarcoGorelli/absolufy-imports. already up to date. Updating https://github.com/python/black ... already up to date. 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. =====> /home/runner/.cache/pre-commit/repo14gb2ni_/.pre-commit-hooks.yaml does not exist 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. updating 5.7.0 -> 5.8.0. Updating https://github.com/asottile/pyupgrade ... [INFO] Initializing environment for https://github.com/asottile/pyupgrade. updating v2.10.0 -> v2.11.0. 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 ... already up to date. ``` </details> <details> <summary><em>pre-commit run -a || (exit 0);</em></summary> ```Shell [INFO] Initializing environment for https://github.com/cpplint/cpplint. [INFO] Initializing environment for https://gitlab.com/pycqa/flake8:flake8-comprehensions>=3.1.0. [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... absolufy-imports....................................................................................Passed black...............................................................................................Passed codespell...........................................................................................Passed Fix End of Files....................................................................................Passed Trim Trailing Whitespace............................................................................Passed cpplint.............................................................................................Passed flake8..............................................................................................Passed flake8 (cython).....................................................................................Passed flake8 (cython template)............................................................................Passed isort...............................................................................................Passed pyupgrade...........................................................................................Failed - hook id: pyupgrade - exit code: 1 - files were modified by this hook Rewriting pandas/io/pytables.py Rewriting pandas/core/internals/blocks.py Rewriting pandas/tests/io/test_sql.py Rewriting pandas/tests/io/parser/test_encoding.py Rewriting pandas/tests/io/parser/common/test_file_buffer_url.py 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 flake8-rst..........................................................................................Passed Check for use of Union[Series, DataFrame] instead of FrameOrSeriesUnion alias.......................Passed Check for inconsistent use of pandas namespace in tests.............................................Passed Check for incorrect code block or IPython directives................................................Passed Check code for instances of os.remove...............................................................Passed Check for non-standard imports......................................................................Passed Check for non-standard imports in test suite........................................................Passed Check for use of np.bool/np.object instead of np.bool_/np.object_...................................Passed Generate pip dependency from conda..................................................................Passed Validate correct capitalization among titles in documentation.......................................Passed Check for use of foo.__class__ instead of type(foo).................................................Passed Check for use of bare pytest raises.................................................................Passed Check for use of private functions across modules...................................................Passed Check for import of private attributes across modules...............................................Passed Check for use of pytest.xfail.......................................................................Passed Check for use of not concatenated strings...........................................................Passed Check for strings with wrong placed spaces..........................................................Passed Check for outdated annotation syntax and missing error codes........................................Passed ``` </details> </details> ## Changed files <details> <summary>Changed 6 files: </summary> - .pre-commit-config.yaml - pandas/core/internals/blocks.py - pandas/io/pytables.py - pandas/tests/io/parser/common/test_file_buffer_url.py - pandas/tests/io/parser/test_encoding.py - pandas/tests/io/test_sql.py </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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BUG: boolean commutativity broken with a Series with object dtype with boolean values and None (can be returned from `.str` boolean methods)
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"2021-03-22T08:13:52Z"
"2021-05-08T18:47:56Z"
null
NONE
null
- [X ] I have checked that this issue has not already been reported. **(sorry if I missed it)** - [X ] I have confirmed this bug exists on the latest version of pandas. **(present on 1.2.3)** --- **Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug. #### Code Sample, a copy-pastable example ```python # Set up import pandas as pd str_serie = pd.Series(["hello", None, "hi"]) # Note the None true_serie = pd.Series([True] * 3) print("1st case") print(str_serie.str.contains('h') | true_serie) # prints True, False, True print("2nd case") print(true_serie | str_serie.str.contains('h')) # prints True, True, True ``` #### Problem description - the commutative property of the `or` or `|` isn't respected. - in the 1st case, pandas seems to stop evaluating the boolean expression at the string comparison if it encounters a null type. #### Expected Output In both cases, the output should be `True, True, True`. If pandas were to still ignore boolean expressions after a str operation on a null type, then it should at least print some warnings about it. #### Output of ``pd.show_versions()`` <details> INSTALLED VERSIONS ------------------ commit : f2c8480af2f25efdbd803218b9d87980f416563e python : 3.9.2.final.0 python-bits : 64 OS : Windows OS-release : 10 Version : 10.0.18362 machine : AMD64 processor : Intel64 Family 6 Model 142 Stepping 12, GenuineIntel byteorder : little LC_ALL : None LANG : None LOCALE : French_Switzerland.1252 pandas : 1.2.3 numpy : 1.20.1 pytz : 2021.1 dateutil : 2.8.1 pip : 21.0.1 setuptools : 49.2.1 Cython : None pytest : 6.2.2 hypothesis : None sphinx : None blosc : None feather : None xlsxwriter : None lxml.etree : None html5lib : None pymysql : None psycopg2 : None jinja2 : 2.11.3 IPython : 7.21.0 pandas_datareader: None bs4 : None bottleneck : None fsspec : 0.8.7 fastparquet : None gcsfs : None matplotlib : 3.3.4 numexpr : None odfpy : None openpyxl : None pandas_gbq : None pyarrow : None pyxlsb : None s3fs : None scipy : 1.6.1 sqlalchemy : 1.4.0 tables : None tabulate : 0.8.9 xarray : None xlrd : None xlwt : None numba : None </details>
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BUG: StringArray.astype() raises for datetime, period, boolean & timedelta with missing values
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CONTRIBUTOR
null
- [X] I have checked that this issue has not already been reported. - [X] I have confirmed this bug exists on the latest version of pandas. - [X] (optional) I have confirmed this bug exists on the master branch of pandas. --- **Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug. #### Code Sample, a copy-pastable example ```python import pandas as pd s = pd.Series(["2020-10-10", None], dtype="string") s.astype("datetime64[ns]") # fails s = pd.Series(["1 Day", None], dtype="string") s.astype("timedelta64[ns]") # fails s = pd.Series(["1/1/2021", None], dtype="string") s.astype("period[M]") # fails s = pd.Series([True, None], dtype="string") s.astype("boolean") # fails ``` Similar issue for `timedelta64` raised by jbrockmendel in #38509. #### Problem description The behaviour looks like a bug and I'd like to help out, however the `astype` dispatching (https://github.com/pandas-dev/pandas/issues/22384) and the `_from_sequence` specifics (https://github.com/pandas-dev/pandas/issues/33254) seem to be debated issues. If you'd like I can write a PR that fixes this by: 1. implementing `_from_sequence_of_strings` in the ExtensionArrays where it hasn't been implemented: Categorical, DatetimeArray, TimedeltaArray. 2. in `StringArray.astype()` convert to ExtensionArrayDTypes using `_from_sequence_of_strings` instead of `_from_sequence`. #### Output of ``pd.show_versions()`` <details> INSTALLED VERSIONS ------------------ commit : f2c8480af2f25efdbd803218b9d87980f416563e python : 3.8.6.final.0 python-bits : 64 OS : Linux OS-release : 5.8.0-45-generic Version : #51-Ubuntu SMP Fri Feb 19 13:24:51 UTC 2021 machine : x86_64 processor : x86_64 byteorder : little LC_ALL : None LANG : en_US.UTF-8 LOCALE : en_US.UTF-8 pandas : 1.2.3 numpy : 1.19.2 pytz : 2020.5 dateutil : 2.8.1 pip : 21.0.1 setuptools : 52.0.0 Cython : None pytest : None hypothesis : None sphinx : None blosc : None feather : None xlsxwriter : None lxml.etree : None html5lib : None pymysql : None psycopg2 : 2.8.5 (dt dec pq3 ext lo64) jinja2 : None IPython : 7.19.0 pandas_datareader: None bs4 : None bottleneck : None fsspec : 0.8.7 fastparquet : None gcsfs : None matplotlib : 3.3.4 numexpr : None odfpy : None openpyxl : None pandas_gbq : None pyarrow : 3.0.0 pyxlsb : None s3fs : None scipy : 1.6.0 sqlalchemy : None tables : None tabulate : None xarray : None xlrd : None xlwt : None numba : None None </details>
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MEMBER
null
Follow-up on https://github.com/pandas-dev/pandas/pull/40527 There is no need for end-users to see this warning if an underlying library they use generates this, so using a DeprecationWarning instead of FutureWarning (as we did before with potentially noisy or internal warnings). At a later point we can change to FutureWarning.
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--- **Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug. #### Code Sample, a copy-pastable example ```python # Your code here Python 3.9.1 | packaged by conda-forge | (default, Dec 9 2020, 01:07:47) [Clang 11.0.0 ] on darwin Type "help", "copyright", "credits" or "license" for more information. >>> import pandas as pd >>> pd.__version__ '1.2.0' >>> df=pd.read_excel('full_data.xlsx') ``` #### Problem description I am not quite sure how to describe the bug, the code just got stuck when I run `pd.read_excel('full_data.xlsx')`. I found this line cost a significant amount of memories (almost `14G` but the `.xlsx` file is just `9MB`). I speculate it is result from `read_excel` now leverage `openpyxl` as default engine in `python3.9`. Loading this file in `python3.8` works fine. ``` >>> from openpyxl import load_workbook >>> wb=load_workbook('full_data.xlsx') >>> df=pd.DataFrame(wb['Sheet1'].values) ``` The above codes also leads to the same issue.
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STY: enable flake8-bugbear
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CONTRIBUTOR
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There are some cases where one of the values of a `zip()` was not used. I removed the `zip()`. If the two sequences for `zip()` have different lengths, this would change the behavior.
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CLN/DEPR: remove Block._holder, deprecated Block.is_categorical
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I'd love it if Pandas could support Databricks' Delta Lake file format (https://github.com/delta-io/delta). It's a type of versioned parquet file format that supports updates/inserts/deletions. In the past delta lake run only on spark but now there are connectors where spark is not required: https://pypi.org/project/deltalake/ https://github.com/delta-io/connectors https://github.com/delta-io/delta-rs/tree/main/python
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In practice in all the cases I'm aware of, _can_hold_na is always fixed at the EA subclass level, so we can immediately infer _can_hold_na from the dtype. But in principle ATM an EA subclass could do ``` class WeirdEA(ExtensionArray): @property def _can_hold_na(self) -> bool: return some_func(self[0]) ``` We should make _can_hold_na an attribute of `ExtensionDtype` to pre-empt this.
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- [x] closes #40518 - [x] tests added / passed - [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them - [x] whatsnew entry Built on #40546, is a relatively minor change after that.
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"2021-03-23T01:27:46Z"
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Should be covered by the test which follows it since `pd.NA` is in `nulls_fixture`
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CLN: remove unused kwarg from IntervalIndex._searchsorted_monotonic
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BUG: groupby + rolling with a non-integer window on multi-index fails-
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- [x] I have checked that this issue has not already been reported. [This](https://github.com/pandas-dev/pandas/issues/15584) seems to be a related issue, but I guess `groupby` is a complication. - [x] I have confirmed this bug exists on the latest version of pandas. - [ ] (optional) I have confirmed this bug exists on the master branch of pandas. --- #### Code Sample, a copy-pastable example ```python import pandas as pd data = pd.DataFrame( [ [1, "2020-01-01", "a", 1], [2, "2020-01-01", "a", 13], [2, "2020-01-02", "a", 4], [1, "2020-01-01", "b", 5], [1, "2020-01-02", "b", 6], [1, "2020-01-03", "c", 9], [2, "2020-01-03", "c", 11], [2, "2020-01-03", "c", 12], ], columns=["gr1", "date", "gr2", "value"], ) data["date"] = pd.to_datetime(data["date"]) data.set_index(["date", "gr1", "gr2"], inplace=True) data.sort_index(level="date", inplace=True) print(data) data.groupby(level="gr1").rolling(window="2D", level="date")["value"].max() ``` Output: ``` value date gr1 gr2 2020-01-01 1 a 1 b 5 2 a 13 2020-01-02 1 b 6 2 a 4 2020-01-03 1 c 9 2 c 11 c 12 data.groupby(level="gr1").rolling(window="2D", level="date")["value"].max() Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/usr/local/lib/python3.9/site-packages/pandas/core/groupby/groupby.py", line 1866, in rolling return RollingGroupby(self, *args, **kwargs) File "/usr/local/lib/python3.9/site-packages/pandas/core/window/rolling.py", line 752, in __init__ super().__init__(obj, *args, **kwargs) File "/usr/local/lib/python3.9/site-packages/pandas/core/window/rolling.py", line 113, in __init__ self.validate() File "/usr/local/lib/python3.9/site-packages/pandas/core/window/rolling.py", line 1921, in validate raise ValueError("window must be an integer") ValueError: window must be an integer ``` #### Problem description Non-integer rolling window seems to not be compatible with multi-index although the `level` is passed in the `rolling`. I am actually not sure if this is a Bug or design choice/design flaw. Note that the `gr2` column needs to stay in the index otherwise it will be "lost". #### Expected Output ``` value date gr1 gr2 2020-01-01 1 a 5 b 5 2 a 13 2020-01-02 1 b 6 2 a 13 2020-01-03 1 c 9 2 c 12 c 12 ``` #### Output of ``pd.show_versions()`` <details> commit : f2c8480af2f25efdbd803218b9d87980f416563e python : 3.9.2.final.0 python-bits : 64 OS : Darwin OS-release : 20.3.0 Version : Darwin Kernel Version 20.3.0: Thu Jan 21 00:06:51 PST 2021; root:xnu-7195.81.3~1/RELEASE_ARM64_T8101 machine : x86_64 processor : i386 byteorder : little LC_ALL : None LANG : None LOCALE : None.UTF-8 pandas : 1.2.3 numpy : 1.20.1 pytz : 2021.1 dateutil : 2.8.1 pip : 21.0.1 setuptools : 54.1.2 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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COMPAT: make Categorical._codes settable again
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This is a follow-up on https://github.com/pandas-dev/pandas/pull/40033, which changes the `_code` attribute of a Categorical into a property without a setter. This broke dask / fastparquet, so this PR is making it settable again. We could deprecate the setter, though, at the same time.
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BUG: Pandas 1.2 the clip method does not support Float64Dtype with pd.NA
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"2021-04-30T20:49:50Z"
"2021-04-30T20:49:50Z"
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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 of pandas. - [x] (optional) I have confirmed this bug exists on the master branch of pandas. --- **Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug. #### Code Sample, a copy-pastable example ```python series = pd.Series([pd.NA, 1.0, 2.5], dtype=pd.Float64Dtype()) series.clip(upper=2.0) ``` #### Problem description Pandas 1.2 cannot handle pd.NA values when the series has a Float64Dtype. When running the code snipped above, the following error occurs: Traceback (most recent call last): File "<input>", line 1, in <module> File "C:\Users\XXX\AppData\Local\pypoetry\Cache\virtualenvs\XXX-w19Rd76b-py3.9\lib\site-packages\pandas\core\generic.py", line 7711, in clip return self._clip_with_scalar(lower, upper, inplace=inplace) File "C:\Users\XXX\AppData\Local\pypoetry\Cache\virtualenvs\XXX-w19Rd76b-py3.9\lib\site-packages\pandas\core\generic.py", line 7562, in _clip_with_scalar subset = self.to_numpy() <= upper File "pandas\_libs\missing.pyx", line 360, in pandas._libs.missing.NAType.__bool__ TypeError: boolean value of NA is ambiguous #### Expected Output pd.Series([pd.NA, 1.0, 2.0], dtype=pd.Float64Dtype) #### Output of ``pd.show_versions()`` <details> INSTALLED VERSIONS ------------------ commit : f2c8480af2f25efdbd803218b9d87980f416563e python : 3.9.1.final.0 python-bits : 64 OS : Windows OS-release : 10 Version : 10.0.19041 machine : AMD64 processor : Intel64 Family 6 Model 85 Stepping 4, GenuineIntel byteorder : little LC_ALL : None LANG : None LOCALE : English_United States.1252 pandas : 1.2.3 numpy : 1.20.1 pytz : 2021.1 dateutil : 2.8.1 pip : 21.0.1 setuptools : 52.0.0 Cython : None pytest : 6.2.2 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 : 3.0.7 pandas_gbq : None pyarrow : None pyxlsb : None s3fs : None scipy : 1.6.1 sqlalchemy : 1.4.2 tables : None tabulate : None xarray : None xlrd : 1.2.0 xlwt : None numba : None </details>
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COMPAT: add back dummy CategoricalBlock class
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"2021-03-23T16:29:28Z"
"2021-03-23T16:08:02Z"
MEMBER
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See https://github.com/pandas-dev/pandas/issues/40226#issuecomment-804903010 @jbrockmendel this is unfortunate, but short term I think we need to keep the CategoricalBlock class. I am not directly sure what would be the best way to actually deprecate this.
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BUG: read_csv - comment argument does not behave as expected
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#### Code Sample, a copy-pastable example Giving the sample file: ```text #empty a,b,c 1,2,3 2,2,3 3,3,3 ``` I want to skip text line starting with character '3': ```python pd.read_csv(filepath, sep=',', comment='3', header=1) ``` #### Problem description In the resulting dataframe the line starting with char '3' is skipped, but also other occurrences of '3' are replaced by nan's. ```text a b c 0 1 2 nan 1 2 2 nan ``` #### Expected Output I expect only record starting with the comment char is missing. ```text a b c 0 1 2 3 1 2 2 3 ``` #### Output of ``pd.show_versions()`` <details> INSTALLED VERSIONS ------------------ commit : f2c8480af2f25efdbd803218b9d87980f416563e python : 3.8.3.final.0 python-bits : 64 OS : Linux OS-release : 4.15.0-136-generic Version : #140-Ubuntu SMP Thu Jan 28 05:20:47 UTC 2021 machine : x86_64 processor : x86_64 byteorder : little LC_ALL : None LANG : en_US.UTF-8 LOCALE : en_US.UTF-8 pandas : 1.2.3 numpy : 1.19.0 pytz : 2020.5 dateutil : 2.8.1 pip : 21.0.1 setuptools : 53.0.0 Cython : None pytest : None hypothesis : None sphinx : None blosc : None feather : None xlsxwriter : None lxml.etree : None html5lib : None pymysql : None psycopg2 : 2.8.6 (dt dec pq3 ext lo64) jinja2 : None IPython : None pandas_datareader: None bs4 : None bottleneck : None fsspec : None fastparquet : None gcsfs : None matplotlib : 3.3.4 numexpr : None odfpy : None openpyxl : 3.0.6 pandas_gbq : None pyarrow : None pyxlsb : None s3fs : None scipy : 1.6.0 sqlalchemy : 1.3.23 tables : None tabulate : None xarray : None xlrd : 2.0.1 xlwt : None numba : 0.50.0 </details>
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REF: deduplicate group min/max
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2
"2021-03-23T14:48:05Z"
"2021-03-23T20:31:10Z"
"2021-03-23T20:29:08Z"
MEMBER
null
ASVs look unaffected: <details> ``` before after ratio [05a0e98a] [16d06e22] <master> <ref/deduplicate_grp_min_max> 33.0±3ms 33.3±1ms 1.01 gil.ParallelGroupbyMethods.time_loop(2, 'max') 32.2±0.4ms 34.5±3ms 1.07 gil.ParallelGroupbyMethods.time_loop(2, 'min') 64.1±1ms 65.6±0.5ms 1.02 gil.ParallelGroupbyMethods.time_loop(4, 'max') 65.3±3ms 65.5±1ms 1.00 gil.ParallelGroupbyMethods.time_loop(4, 'min') 20.2±2ms 20.2±0.8ms 1.00 gil.ParallelGroupbyMethods.time_parallel(2, 'max') 21.3±1ms 20.1±0.8ms 0.95 gil.ParallelGroupbyMethods.time_parallel(2, 'min') 25.1±0.7ms 25.3±0.5ms 1.01 gil.ParallelGroupbyMethods.time_parallel(4, 'max') 25.0±0.4ms 26.5±2ms 1.06 gil.ParallelGroupbyMethods.time_parallel(4, 'min') 125±50ms 104±1ms ~0.83 groupby.GroupByCythonAgg.time_frame_agg('float64', 'max') 105±2ms 107±2ms 1.02 groupby.GroupByCythonAgg.time_frame_agg('float64', 'min') ``` </details>
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40,585
BUG: Groupby.any(skipna=True)
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1
"2021-03-23T14:51:17Z"
"2021-04-13T17:12:16Z"
"2021-04-13T17:12:16Z"
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 of pandas. - [ ] (optional) I have confirmed this bug exists on the master branch of pandas. --- **Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug. #### Code Sample, a copy-pastable example ```python import pandas as pd def test_groupby_any(): df = pd.DataFrame( { "ids": ["id1", "id1", "id2", "id2"], "A": [True, False, pd.NA, True] } ).astype({"ids": pd.StringDtype(), "A": pd.BooleanDtype()}) result = df.groupby("ids").any(skipna=True) expected = pd.DataFrame( { "A": [True, True] }, index=pd.Series(["id1", "id2"], name="ids") ) pd.testing.assert_frame_equal(expected, result) ``` #### Problem description When running df.groupby(field_to_group_on).any(skipna=True) it should be expected that pd.NA values are neglected for the .any() method. However the output is this: self = <BooleanArray> [True, False, <NA>, True] Length: 4, dtype: boolean dtype = dtype('bool'), copy = True def astype(self, dtype, copy: bool = True) -> ArrayLike: """ Cast to a NumPy array or ExtensionArray with 'dtype'. Parameters ---------- dtype : str or dtype Typecode or data-type to which the array is cast. copy : bool, default True Whether to copy the data, even if not necessary. If False, a copy is made only if the old dtype does not match the new dtype. Returns ------- ndarray or ExtensionArray NumPy ndarray, BooleanArray or IntegerArray with 'dtype' for its dtype. Raises ------ TypeError if incompatible type with an BooleanDtype, equivalent of same_kind casting """ from pandas.core.arrays.string_ import StringDtype dtype = pandas_dtype(dtype) if isinstance(dtype, BooleanDtype): values, mask = coerce_to_array(self, copy=copy) if not copy: return self else: return BooleanArray(values, mask, copy=False) elif isinstance(dtype, StringDtype): return dtype.construct_array_type()._from_sequence(self, copy=False) if is_bool_dtype(dtype): # astype_nansafe converts np.nan to True if self._hasna: > raise ValueError("cannot convert float NaN to bool") E ValueError: cannot convert float NaN to bool #### Expected Output ``` expected = pd.DataFrame( { "A": [True, True] }, index=pd.Series(["id1", "id2"], name="ids") ) ``` #### Output of ``pd.show_versions()`` <details> INSTALLED VERSIONS ------------------ commit : f2c8480af2f25efdbd803218b9d87980f416563e python : 3.9.1.final.0 python-bits : 64 OS : Windows OS-release : 10 Version : 10.0.19041 machine : AMD64 processor : Intel64 Family 6 Model 85 Stepping 4, GenuineIntel byteorder : little LC_ALL : None LANG : None LOCALE : English_United States.1252 pandas : 1.2.3 numpy : 1.20.1 pytz : 2021.1 dateutil : 2.8.1 pip : 21.0.1 setuptools : 52.0.0 Cython : None pytest : 6.2.2 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 : 3.0.7 pandas_gbq : None pyarrow : None pyxlsb : None s3fs : None scipy : 1.6.1 sqlalchemy : 1.4.2 tables : None tabulate : None xarray : None xlrd : 1.2.0 xlwt : None numba : None </details>
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838,812,483
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40,586
PERF: Define Block.__init__ in cython
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4
"2021-03-23T14:53:20Z"
"2021-03-23T21:13:58Z"
"2021-03-23T20:28:33Z"
MEMBER
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Shaves about 10% off the benchmark discussed in https://github.com/pandas-dev/pandas/pull/40171#issuecomment-790219422
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BUG: Occasional "tokenizing data error" when reading in large files with read_csv()
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I sometimes receive a `Error tokenizing data. C error: ...` for tables that can normally be read with `read_csv()` without any problems. Find attached the .csv file [sample.tar.gz](https://github.com/pandas-dev/pandas/files/6190356/sample.tar.gz) for which I can reproduce the problem. ```python import pandas as pd path = "sample.csv" pd.read_csv(path, sep=";", header=[0,1]) ``` This raises the following exception: ```lang-text ParserError: Error tokenizing data. C error: Expected 15 fields in line 983050, saw 23 ``` The tables I try to read have 23 columns, as declared correctly in the file header. However, the files contain corrupted lines (very few, <0.01% of all lines), where the data of 8 columns are omitted. For those lines, 8 delimiters are missing. I'm working with about 100 different files containing 1M to 20M lines. All files suffer from the same kind of ill-formatted lines. `read_csv()` graciously handles those lines most of the time. Only for the file provided above, it raises an exception. I can avoid the exception as follows: - Delete a couple of unrelated (healthy) lines at the beginning of the document - By setting `engine="python"` (slow) - By setting `low_memory=False` - By setting `error_bad_lines=False` (drops a couple of lines) In summary, I think `read_csv()` behaves inconsistently if running with `low-memory=True` and C-engine. I first thought that the problem is related to issue #11166, but I'm not sure 100%. [sample.tar.gz](https://github.com/pandas-dev/pandas/files/6190356/sample.tar.gz) I'm running python3.8 and pandas 1.2.3. See details below. #### Expected Output No exception for file `sample.csv`, regardless of the settings for `engine` and `low_memory`. #### System <details> ```lang-text INSTALLED VERSIONS ------------------ commit : f2c8480af2f25efdbd803218b9d87980f416563e python : 3.8.0.final.0 python-bits : 64 OS : Darwin OS-release : 18.7.0 Version : Darwin Kernel Version 18.7.0: Fri Oct 30 12:37:06 PDT 2020; root:xnu-4903.278.44.0.2~1/RELEASE_X86_64 machine : x86_64 processor : i386 byteorder : little LC_ALL : None LANG : en_US.UTF-8 LOCALE : None.UTF-8 pandas : 1.2.3 numpy : 1.20.1 pytz : 2019.3 dateutil : 2.8.1 pip : 20.3.3 setuptools : 54.1.2 Cython : None pytest : 6.2.1 hypothesis : None sphinx : None blosc : None feather : None xlsxwriter : None lxml.etree : None html5lib : None pymysql : None psycopg2 : None jinja2 : None IPython : 7.13.0 pandas_datareader: None bs4 : 4.9.3 bottleneck : None fsspec : 0.8.5 fastparquet : None gcsfs : None matplotlib : 3.3.3 numexpr : 2.7.1 odfpy : None openpyxl : 3.0.5 pandas_gbq : None pyarrow : 1.0.0 pyxlsb : None s3fs : None scipy : 1.3.2 sqlalchemy : None tables : 3.6.1 tabulate : None xarray : None xlrd : None xlwt : None numba : None ``` </details>
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Index=False is not working in to_parquet command
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import pandas as pd df = pd.DataFrame(data={'col1': [1, 2], 'col2': [3, 4]}) df.to_parquet('df.parquet',compression=None, index=False) pd.read_parquet('df.parquet') I am running this code and it shows index. I set index as False.
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BUG: converters of dtype is ignored in read_csv if related to index column
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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 of pandas. --- #### Code Sample, a copy-pastable example **test.txt file** : 5 6 7 8 9 10 ```python # Your code here import pandas as pd print(pd.__version__) print("Case 1: no converters or dtype. ") a = pd.read_csv("test.txt", sep="\t", index_col=["Index"], names=["Index", "Length"]) print(a["Length"]) print(a.index) print("Case 2: converters option") a = pd.read_csv("test.t", sep="\t", index_col=["Index"], names=["Index", "Length"], converters={"Index": str, "Length": str}) print(a["Length"]) print(a.index) print("Case 3: dtype option") a = pd.read_csv("test.t", sep="\t", index_col=["Index"], names=["Index", "Length"], dtype={"Index": str, "Length": str}) print(a["Length"]) print(a.index) ``` #### Problem description Output of code above: Case 1: no converters or dtype. Index 5 6 7 8 9 10 Name: Length, dtype: int64 Int64Index([5, 7, 9], dtype='int64', name='Index') Case 2: converters option Index 5 6 7 8 9 10 Name: Length, dtype: object **Int64Index([5, 7, 9], dtype='int64', name='Index')** Case 3: dtype option Index 5 6 7 8 9 10 Name: Length, dtype: object **Int64Index([5, 7, 9], dtype='int64', name='Index')** Converters and dtype are not applied to index column when reading file via pd.read_csv . In all three cases type of index elements remains **int** . Other columns are converted as expected. #### Expected Output In "Case 2" and "Case 3" type of index elements expected to be **str**. #### Output of ``pd.show_versions()`` <details> INSTALLED VERSIONS ------------------ commit : f2c8480af2f25efdbd803218b9d87980f416563e python : 3.8.5.final.0 python-bits : 64 OS : Linux OS-release : 4.15.0-54-generic Version : #58-Ubuntu SMP Mon Jun 24 10:55:24 UTC 2019 machine : x86_64 processor : x86_64 byteorder : little LC_ALL : None LANG : en_US.UTF-8 LOCALE : en_US.UTF-8 pandas : 1.2.3 numpy : 1.19.2 pytz : 2020.1 dateutil : 2.8.1 pip : 20.2.4 setuptools : 50.3.1.post20201107 Cython : 0.29.21 pytest : 6.1.1 hypothesis : None sphinx : 3.2.1 blosc : None feather : None xlsxwriter : 1.3.7 lxml.etree : 4.6.1 html5lib : 1.1 pymysql : None psycopg2 : None jinja2 : 2.11.2 IPython : 7.19.0 pandas_datareader: None bs4 : 4.9.3 bottleneck : 1.3.2 fsspec : 0.8.3 fastparquet : None gcsfs : None matplotlib : 3.3.2 numexpr : 2.7.1 odfpy : None openpyxl : 3.0.5 pandas_gbq : None pyarrow : None pyxlsb : None s3fs : None scipy : 1.5.2 sqlalchemy : 1.3.20 tables : 3.6.1 tabulate : None xarray : None xlrd : 1.2.0 xlwt : 1.3.0 numba : 0.51.2 </details>
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Backport PR #40525 on branch 1.2.x (BUG: to_json failing on PyPy)
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Backport PR #40525: BUG: to_json failing on PyPy
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QST: Related to working of `as_index` in pandas groupby
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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). --- #### Question about pandas ``` import pandas as pd import numpy as np df = pd.DataFrame(np.random.randint(0,10,size=(10, 4)), columns=list('ABCD')) df.A = df.agg('City_{0[A]}'.format, axis=1) df.index = (df.index)*int(np.random.randint(6,23)**0.5)+int(np.random.randint(2,23)) ``` **This is my df:**  A | B | C | D -- | -- | -- | -- City_2 | 3 | 7 | 3 City_0 | 4 | 8 | 9 City_1 | 1 | 2 | 1 City_5 | 5 | 0 | 9 City_5 | 1 | 6 | 0 City_0 | 3 | 8 | 6 City_7 | 2 | 6 | 6 City_1 | 6 | 0 | 2 City_8 | 6 | 2 | 4 City_2 | 2 | 5 | 6 If I do `df.groupby([df.index//5,df.A], as_index=True).mean()` or `df.groupby([df.index//5,df.A]).mean()` **Result:** | | | B | C | D | |--:|-------:|--:|--:|--:| | | A | | | | | 1 | City_2 | 3 | 7 | 3 | | 2 | City_0 | 4 | 8 | 9 | | 3 | City_1 | 1 | 2 | 1 | | | City_5 | 5 | 0 | 9 | | 4 | City_0 | 3 | 8 | 6 | | | City_5 | 1 | 6 | 0 | | 5 | City_7 | 2 | 6 | 6 | | 6 | City_1 | 6 | 0 | 2 | | | City_8 | 6 | 2 | 4 | | 7 | City_2 | 2 | 5 | 6 | So If do `.reset_index()` I will get this (that index with no column name will get name as `level_0` ):   level_0 | A | B | C | D -- | -- | -- | -- | -- 1 | City_2 | 3 | 7 | 3 2 | City_0 | 4 | 8 | 9 3 | City_1 | 1 | 2 | 1 3 | City_5 | 5 | 0 | 9 4 | City_0 | 3 | 8 | 6 4 | City_5 | 1 | 6 | 0 5 | City_7 | 2 | 6 | 6 6 | City_1 | 6 | 0 | 2 6 | City_8 | 6 | 2 | 4 7 | City_2 | 2 | 5 | 6 The same is not with the `as_index=False` `df.groupby([df.index//5,df.A], as_index=False).mean()` will give me  A | B | C | D -- | -- | -- | -- City_2 | 3 | 7 | 3 City_0 | 4 | 8 | 9 City_1 | 1 | 2 | 1 City_5 | 5 | 0 | 9 City_0 | 3 | 8 | 6 City_5 | 1 | 6 | 0 City_7 | 2 | 6 | 6 City_1 | 6 | 0 | 2 City_8 | 6 | 2 | 4 City_2 | 2 | 5 | 6 I will lose the `groupby index info`. **My question:** shouldn't be `as_index=False` give `df.index//5` column also. Or `as_index` is designed to work like this only.
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REGR: where not copying on no-op
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- [x] closes #39595 - [x] tests added / passed - [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them - [x] whatsnew entry
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Adds a test for loc on sparse dataframes. - [x] closes #34687 - [x] tests added / passed - [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
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BUG: Installation of the build dependencies fails
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Following https://pandas.pydata.org/pandas-docs/stable/development/contributing.html#creating-a-python-environment-pip to create dev environemnt However, some failure pops up ``` ERROR: Command errored out with exit status 1: command: /Users/kaiqidong/pyvenv/pandas-dev/bin/python -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'/private/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/pip-install-a1dqlo0f/fastparquet_1298cd7d34ec45bc9cadbaacbc22c22c/setup.py'"'"'; __file__='"'"'/private/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/pip-install-a1dqlo0f/fastparquet_1298cd7d34ec45bc9cadbaacbc22c22c/setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' egg_info --egg-base /private/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/pip-pip-egg-info-rsz4xmwi cwd: /private/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/pip-install-a1dqlo0f/fastparquet_1298cd7d34ec45bc9cadbaacbc22c22c/ Complete output (95 lines): Processing numpy/random/_bounded_integers.pxd.in Processing numpy/random/_philox.pyx Traceback (most recent call last): File "/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/easy_install-v2l4o5n8/numpy-1.20.1/tools/cythonize.py", line 59, in process_pyx from Cython.Compiler.Version import version as cython_version ModuleNotFoundError: No module named 'Cython' During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/easy_install-v2l4o5n8/numpy-1.20.1/tools/cythonize.py", line 235, in <module> main() File "/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/easy_install-v2l4o5n8/numpy-1.20.1/tools/cythonize.py", line 231, in main find_process_files(root_dir) File "/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/easy_install-v2l4o5n8/numpy-1.20.1/tools/cythonize.py", line 222, in find_process_files process(root_dir, fromfile, tofile, function, hash_db) File "/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/easy_install-v2l4o5n8/numpy-1.20.1/tools/cythonize.py", line 188, in process processor_function(fromfile, tofile) File "/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/easy_install-v2l4o5n8/numpy-1.20.1/tools/cythonize.py", line 64, in process_pyx raise OSError('Cython needs to be installed in Python as a module') OSError: Cython needs to be installed in Python as a module Running from numpy source directory. /var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/easy_install-v2l4o5n8/numpy-1.20.1/setup.py:485: UserWarning: Unrecognized setuptools command, proceeding with generating Cython sources and expanding templates run_build = parse_setuppy_commands() Traceback (most recent call last): File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/sandbox.py", line 154, in save_modules yield saved File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/sandbox.py", line 195, in setup_context yield File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/sandbox.py", line 250, in run_setup _execfile(setup_script, ns) File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/sandbox.py", line 45, in _execfile exec(code, globals, locals) File "/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/easy_install-v2l4o5n8/numpy-1.20.1/setup.py", line 513, in <module> File "/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/easy_install-v2l4o5n8/numpy-1.20.1/setup.py", line 493, in setup_package File "/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/easy_install-v2l4o5n8/numpy-1.20.1/setup.py", line 290, in generate_cython RuntimeError: Running cythonize failed! During handling of the above exception, another exception occurred: Traceback (most recent call last): File "<string>", line 1, in <module> File "/private/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/pip-install-a1dqlo0f/fastparquet_1298cd7d34ec45bc9cadbaacbc22c22c/setup.py", line 52, in <module> setup( File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/__init__.py", line 144, in setup _install_setup_requires(attrs) File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/__init__.py", line 139, in _install_setup_requires dist.fetch_build_eggs(dist.setup_requires) File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/dist.py", line 716, in fetch_build_eggs resolved_dists = pkg_resources.working_set.resolve( File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/pkg_resources/__init__.py", line 780, in resolve dist = best[req.key] = env.best_match( File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/pkg_resources/__init__.py", line 1065, in best_match return self.obtain(req, installer) File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/pkg_resources/__init__.py", line 1077, in obtain return installer(requirement) File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/dist.py", line 786, in fetch_build_egg return cmd.easy_install(req) File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/command/easy_install.py", line 679, in easy_install return self.install_item(spec, dist.location, tmpdir, deps) File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/command/easy_install.py", line 705, in install_item dists = self.install_eggs(spec, download, tmpdir) File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/command/easy_install.py", line 890, in install_eggs return self.build_and_install(setup_script, setup_base) File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/command/easy_install.py", line 1158, in build_and_install self.run_setup(setup_script, setup_base, args) File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/command/easy_install.py", line 1144, in run_setup run_setup(setup_script, args) File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/sandbox.py", line 253, in run_setup raise File "/Library/Developer/CommandLineTools/Library/Frameworks/Python3.framework/Versions/3.8/lib/python3.8/contextlib.py", line 131, in __exit__ self.gen.throw(type, value, traceback) File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/sandbox.py", line 195, in setup_context yield File "/Library/Developer/CommandLineTools/Library/Frameworks/Python3.framework/Versions/3.8/lib/python3.8/contextlib.py", line 131, in __exit__ self.gen.throw(type, value, traceback) File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/sandbox.py", line 166, in save_modules saved_exc.resume() File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/sandbox.py", line 141, in resume six.reraise(type, exc, self._tb) File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/_vendor/six.py", line 685, in reraise raise value.with_traceback(tb) File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/sandbox.py", line 154, in save_modules yield saved File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/sandbox.py", line 195, in setup_context yield File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/sandbox.py", line 250, in run_setup _execfile(setup_script, ns) File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/sandbox.py", line 45, in _execfile exec(code, globals, locals) File "/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/easy_install-v2l4o5n8/numpy-1.20.1/setup.py", line 513, in <module> File "/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/easy_install-v2l4o5n8/numpy-1.20.1/setup.py", line 493, in setup_package File "/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/easy_install-v2l4o5n8/numpy-1.20.1/setup.py", line 290, in generate_cython RuntimeError: Running cythonize failed! Cythonizing sources ---------------------------------------- WARNING: Discarding https://files.pythonhosted.org/packages/58/49/dccb790fa17ab3fbf84a6b848050083c7a1899e9586000e34e3e4fbf5538/fastparquet-0.3.2.tar.gz#sha256=d81dcec444f4c4829234b9baac57c7125b8fbe9119c2eca2dee922650db49205 (from https://pypi.org/simple/fastparquet/) (requires-python:>=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*,). Command errored out with exit status 1: python setup.py egg_info Check the logs for full command output. ERROR: Could not find a version that satisfies the requirement fastparquet>=0.3.2 ERROR: No matching distribution found for fastparquet>=0.3.2 ```
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839,111,448
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40,596
ENH: add `decimal` and `thousands` args to `Styler.format()`
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1
"2021-03-23T20:51:09Z"
"2021-04-21T06:09:13Z"
"2021-04-20T23:01:03Z"
CONTRIBUTOR
null
A PR for Europeans: ![Screen Shot 2021-03-23 at 21 40 19](https://user-images.githubusercontent.com/24256554/112216306-a1b90a00-8c21-11eb-9d2b-c281154b4b46.png)
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40,597
DOC: Update _shallow_copy docstring
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2
"2021-03-23T21:26:46Z"
"2021-03-30T13:15:08Z"
"2021-03-30T13:15:08Z"
NONE
null
added extended param definition - [ ] closes #xxxx - [ ] tests added / passed - [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them - [ ] whatsnew entry
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DOC: update guideline for installation development environment using pip
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1
"2021-03-23T21:26:51Z"
"2021-03-24T23:13:39Z"
"2021-03-24T23:13:35Z"
MEMBER
null
- [x] closes #40595 - [ ] tests added / passed - [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them - [ ] whatsnew entry
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REF: deduplicate group cummin/max
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"2021-03-25T00:04:15Z"
"2021-03-24T23:37:42Z"
MEMBER
null
After #40584, may as well do this one too.
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DOC: _guess_time_format_for_array method desc
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Method description added for the method - [ ] closes #xxxx - [ ] tests added / passed - [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them - [ ] whatsnew entry
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CLN libjoin int64->intp
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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.html#code-standards) for how to run them - [ ] whatsnew entry
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ENH: Categorical.empty
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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.html#code-standards) for how to run them - [ ] whatsnew entry xref #39776 xref https://github.com/dask/fastparquet/issues/576#issuecomment-805220721
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March 2021 Docs Meeting
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- [Thursday, March 25th 9-10am US Eastern Time](https://everytimezone.com/s/d95276ff) - [Zoom link](https://nyu.zoom.us/j/98201283174?pwd=d0VoUy9GTDRlVVZ0cCtTK0s4NnlBZz09) - [Agenda/notes](https://docs.google.com/document/d/1JoiqTdK6gi5W1QiTWrqtTV-rNmIqU3xROgHY5iT4J5g/edit#heading=h.98uhh75g3r7w) --- A time to talk about pandas documentation. [Agenda/notes doc](https://docs.google.com/document/d/1JoiqTdK6gi5W1QiTWrqtTV-rNmIqU3xROgHY5iT4J5g/edit#heading=h.1obsyhexqytc) — feel free to add things in advance. All are welcome. Thanks! @pandas-dev/pandas-core @pandas-dev/pandas-triage @pandas-dev/pydata-sphinx-theme @pandas-dev/pandas-docs
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REGR: replace with multivalued regex raising
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"2021-03-24T02:29:31Z"
"2021-03-26T11:24:25Z"
"2021-03-25T01:51:54Z"
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null
- [x] closes #39338 - [x] tests added / passed - [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them - [x] whatsnew entry Issue comes from the first pair in the `regex` arg hitting the simple replace path, which causes the `ObjectBlock` to be split. From here, the mask indexing will be wrong, but that will not cause an error unless a later pair hits `_replace_regex`, which actually uses the mask.
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BUG: color list passed in as list/array/series of colors only picks up first color.
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"2021-08-19T02:53:04Z"
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So I found this issue was fixed in 2017 and 2019 respectively, however I think it's back. I spent half the day trying to figure out what I was doing wrong until I stumbled upon this thread/report: https://github.com/pandas-dev/pandas/issues/16822 And it seems like the bug may have crawled its way back in? Sorry if I should not have opened a new bug report however you mentioned opening a new bug report for the 2019 reports of this bug so I figured I would report that it might be back as well. - [x ] I have checked that this issue has not already been reported. - [x ] I have confirmed this bug exists on the latest version of pandas. - [x ] (optional) I have confirmed this bug exists on the master branch of pandas. --- **Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug. #### Code Sample, a copy-pastable example ```python fullColors = list(itertools.repeat('#3FD21C',10)) + list(itertools.repeat('#ED5851',25)) df.plot(kind='bar', logy='sym', color=fullColors) plt.show() ``` #### Problem description So I have a dataframe with 1 data column and an index column, the dataframe has 50 values/rows in it and when i pass in a list of 50 colors I would expect those colors get matched up with each bar (or in my case half the bars are one color and half another) however only the first color passed in gets used to color all of the bars. #### Expected Output A bar graph with multiple colored bars rather than just 1 color #### Output of ``pd.show_versions()`` INSTALLED VERSIONS ------------------ commit : f2c8480af2f25efdbd803218b9d87980f416563e python : 3.8.8.final.0 python-bits : 64 OS : Windows OS-release : 10 Version : 10.0.19041 machine : AMD64 processor : Intel64 Family 6 Model 142 Stepping 11, GenuineIntel byteorder : little LC_ALL : None LANG : None LOCALE : English_United States.1252 pandas : 1.2.3 numpy : 1.18.5 pytz : 2021.1 dateutil : 2.8.1 pip : 21.0.1 setuptools : 52.0.0.post20210125 Cython : None pytest : None hypothesis : None sphinx : None blosc : None feather : None xlsxwriter : 1.3.7 lxml.etree : None html5lib : None pymysql : None psycopg2 : None jinja2 : 2.11.2 IPython : 7.21.0 pandas_datareader: None bs4 : None bottleneck : None fsspec : None fastparquet : None gcsfs : None matplotlib : 3.3.4 numexpr : None odfpy : None openpyxl : None pandas_gbq : None pyarrow : None pyxlsb : None s3fs : None scipy : 1.6.1 sqlalchemy : 1.3.18 tables : None tabulate : None xarray : None xlrd : None xlwt : None numba : None None </details>
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DEPR: deprecate setting Categorical._codes
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"2021-03-24T07:30:45Z"
"2021-05-12T13:52:59Z"
"2021-05-12T13:52:59Z"
MEMBER
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Needed follow-up on https://github.com/pandas-dev/pandas/pull/40580 (and https://github.com/pandas-dev/pandas/pull/40033), we should deprecate the setter of the `Categorical._codes` property.
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why my plotnine cant be applied? this is that error, how to solved that? ImportError: cannot import name 'FrameOrSeriesUnion' from 'pandas._typing' (C:\Users\ASUS\Anaconda3\lib\site-packages\pandas\_typing.py)
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BUG: join/merge of DataFrame does not keep order of index
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"2021-08-25T21:11:03Z"
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- [x] I have checked that this issue has not already been reported. The issue may be related to issue #34133 - [x] I have confirmed this bug exists on the latest version of pandas. --- #### Code Sample, a copy-pastable example ```python import pandas idx_single = pandas.RangeIndex(10) idx_double = pandas.Index(idx_single.tolist() + idx_single.tolist()) # idx_double df1 = pandas.DataFrame(index=idx_double) df2 = pandas.DataFrame(index=idx_single, data=1, columns=["one", "two"]) print(df1.index) print(df1.join(df2, how="left", sort=False).index) print(df1.merge(df2, how="left", right_index=True, left_index=True, sort=False).index) ``` #### Problem description The index of the joined (or merged) dataframe is not the same as the left hand dataframe even though sort=False. ``` Int64Index([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9], dtype='int64') Int64Index([0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7, 7, 8, 8, 9, 9], dtype='int64') Int64Index([0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7, 7, 8, 8, 9, 9], dtype='int64') ``` #### Expected Output I would expect the index of the joined/merged dataframe to be the same as the left hand dataframe. ``` Int64Index([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9], dtype='int64') Int64Index([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9], dtype='int64') Int64Index([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9], dtype='int64') ``` #### Output of ``pd.show_versions()`` <details> INSTALLED VERSIONS ------------------ commit : f2c8480af2f25efdbd803218b9d87980f416563e python : 3.9.0.final.0 python-bits : 64 OS : Windows OS-release : 10 Version : 10.0.18362 machine : AMD64 processor : Intel64 Family 6 Model 142 Stepping 10, GenuineIntel byteorder : little LC_ALL : None LANG : en_US.UTF-8 LOCALE : French_Belgium.1252 pandas : 1.2.3 numpy : 1.20.1 pytz : 2021.1 dateutil : 2.8.1 pip : 21.0.1 setuptools : 49.2.0 </details>
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40,609
PERF: increase the minimum number of elements to use numexpr for ops from 1e4 to 1e6
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4
"2021-03-24T08:42:22Z"
"2021-03-24T14:10:22Z"
"2021-03-24T14:08:52Z"
MEMBER
null
Closes #40500, see that issue for the analysis of speedup vs size. Another take of https://github.com/pandas-dev/pandas/pull/40502, but hopefully now without crashing the tests because of increased memory use.
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40,610
DOC: When to Use PandasArray vs ExtensionArray
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"2021-03-24T14:39:21Z"
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I was wondering if anyone could point me to the doc stating when a `PandasArray` should be used over an `ExtensionArray` when extending the Pandas API? I could not find anything about this.
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Can't install Pandas on Mac M1
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Environment Mac M1 Python 3.8.2 created using Xcode Command Line Tools for M1 Macs On trying to install pandas, it failed and it returns very long erorr message starts as below (py382tf) mgd@MGD ~ % pip install pandas Collecting pandas Using cached https://files.pythonhosted.org/packages/8a/6f/7fcef020b5b305862cacf376183eaa0f907f2fa42f0b687b2a9a2c6cda4d/pandas-1.2.3.tar.gz Installing build dependencies ... error ERROR: Command errored out with exit status 1: command: /Users/mgd/py382tf/bin/python3 /Users/mgd/py382tf/lib/python3.8/site-packages/pip install --ignore-installed --no-user --prefix /private/var/folders/px/zqhcsbbx4yxfmhc7927tnfj00000gn/T/pip-build-env-orb4vxpv/overlay --no-warn-script-location --no-binary :none: --only-binary :none: -i https://pypi.org/simple -- setuptools wheel 'Cython>=0.29.21,<3' 'numpy==1.16.5; python_version=='"'"'3.7'"'"' and platform_system!='"'"'AIX'"'"'' 'numpy==1.17.3; python_version=='"'"'3.8'"'"' and platform_system!='"'"'AIX'"'"'' 'numpy==1.16.5; python_version=='"'"'3.7'"'"' and platform_system=='"'"'AIX'"'"'' 'numpy==1.17.3; python_version=='"'"'3.8'"'"' and platform_system=='"'"'AIX'"'"'' 'numpy; python_version>='"'"'3.9'"'"'' cwd: None Complete output (4451 lines): Ignoring numpy: markers 'python_version == "3.7" and platform_system != "AIX"' don't match your environment Ignoring numpy: markers 'python_version == "3.7" and platform_system == "AIX"' don't match your environment Ignoring numpy: markers 'python_version == "3.8" and platform_system == "AIX"' don't match your environment Ignoring numpy: markers 'python_version >= "3.9"' don't match your environment Collecting setuptools Using cached https://files.pythonhosted.org/packages/9e/d4/b99a960314121a003e9f39c61dfde01a1010bb47661e193a7722f7f32d52/setuptools-54.2.0-py3-none-any.whl Collecting wheel Using cached https://files.pythonhosted.org/packages/65/63/39d04c74222770ed1589c0eaba06c05891801219272420b40311cd60c880/wheel-0.36.2-py2.py3-none-any.whl Collecting Cython<3,>=0.29.21 Using cached https://files.pythonhosted.org/packages/9e/98/bff39b3acaebbc6102be71797f655bbe60738f7339db4ad7bd0772c08daf/Cython-0.29.22-py2.py3-none-any.whl Collecting numpy==1.17.3 Using cached https://files.pythonhosted.org/packages/b6/d6/be8f975f5322336f62371c9abeb936d592c98c047ad63035f1b38ae08efe/numpy-1.17.3.zip Installing collected packages: setuptools, wheel, Cython, numpy Running setup.py install for numpy: started Running setup.py install for numpy: finished with status 'error' ERROR: Command errored out with exit status 1: command: /Users/mgd/py382tf/bin/python3 -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'/private/var/folders/px/zqhcsbbx4yxfmhc7927tnfj00000gn/T/pip-install-x_x_2bsb/numpy/setup.py'"'"'; __file__='"'"'/private/var/folders/px/zqhcsbbx4yxfmhc7927tnfj00000gn/T/pip-install-x_x_2bsb/numpy/setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' install --record /private/var/folders/px/zqhcsbbx4yxfmhc7927tnfj00000gn/T/pip-record-73r6zlw4/install-record.txt --single-version-externally-managed --prefix /private/var/folders/px/zqhcsbbx4yxfmhc7927tnfj00000gn/T/pip-build-env-orb4vxpv/overlay --compile --install-headers /Users/mgd/py382tf/include/site/python3.8/numpy cwd: /private/var/folders/px/zqhcsbbx4yxfmhc7927tnfj00000gn/T/pip-install-x_x_2bsb/numpy/ Complete output (4428 lines): Running from numpy source directory. Note: if you need reliable uninstall behavior, then install with pip instead of using `setup.py install`: - `pip install .` (from a git repo or downloaded source release) - `pip install numpy` (last NumPy release on PyPi) blas_opt_info: blas_mkl_info: customize UnixCCompiler libraries mkl_rt not found in ['/Users/mgd/py382tf/lib', '/usr/lib'] NOT AVAILABLE blis_info: customize UnixCCompiler libraries blis not found in ['/Users/mgd/py382tf/lib', '/usr/lib'] NOT AVAILABLE openblas_info: customize UnixCCompiler customize UnixCCompiler libraries openblas not found in ['/Users/mgd/py382tf/lib', '/usr/lib'] NOT AVAILABLE atlas_3_10_blas_threads_info: Setting PTATLAS=ATLAS customize UnixCCompiler libraries tatlas not found in ['/Users/mgd/py382tf/lib', '/usr/lib'] NOT AVAILABLE atlas_3_10_blas_info: customize UnixCCompiler libraries satlas not found in ['/Users/mgd/py382tf/lib', '/usr/lib'] NOT AVAILABLE atlas_blas_threads_info: Setting PTATLAS=ATLAS customize UnixCCompiler libraries ptf77blas,ptcblas,atlas not found in ['/Users/mgd/py382tf/lib', '/usr/lib'] NOT AVAILABLE atlas_blas_info: customize UnixCCompiler libraries f77blas,cblas,atlas not found in ['/Users/mgd/py382tf/lib', '/usr/lib'] NOT AVAILABLE accelerate_info: customize UnixCCompiler libraries accelerate not found in ['/Users/mgd/py382tf/lib', '/usr/lib'] Library accelerate was not found. Ignoring customize UnixCCompiler libraries veclib not found in ['/Users/mgd/py382tf/lib', '/usr/lib'] Library veclib was not found. Ignoring
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TYP: get_indexer
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"2021-04-19T19:00:57Z"
"2021-04-19T18:54:32Z"
MEMBER
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@simonjayhawkins im at a loss on why im getting a mypy complaint: ``` error: Overloaded function signatures 1 and 2 overlap with incompatible return types [misc] ``` AFAICT they should be compatible. Am I missing something obvious?
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Add capability to upsample with .resample().ffill() using time series on either axis
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"2021-03-24T16:13:21Z"
"2021-08-19T02:56:32Z"
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It would be good to have the capability to upsample using `.resample()` and forward fill using `.ffill()` on either axis. It seems to be blocked by the Assertion Error here, but I can' see a clear reason. https://github.com/pandas-dev/pandas/blob/a20c169f8aee9c272953be43d89dfa82be5e186b/pandas/core/resample.py#L1153 ```python # Code to reproduce. import pandas as pd dt_idx = pd.period_range(start='2021-01-01', freq='M', periods=3).to_timestamp() # Transpose to have time series on columns df = pd.DataFrame(range(3), index=dt_idx).T resampled = df.resample('W-Mon', axis=1).ffill() ``` There is a workaround below so this is issue is low priority. ```python # Current workaround. import pandas as pd dt_idx = pd.period_range(start='2021-01-01', freq='M', periods=3).to_timestamp() # Transpose to have time series on columns df = pd.DataFrame(range(3), index=dt_idx).T resampled = df.resample('W-Mon', axis=1).first().ffill(axis=1) ```
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REF: remove DatetimeBlock, TimeDeltaBlock
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sits on top of #40456
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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.html#code-standards) for how to run them - [ ] whatsnew entry
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By not mixing IntervalMixin into IntervalIndex, mypy also starts taking it more seriously.
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"2021-03-25T01:53:18Z"
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