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https://api.github.com/repos/pandas-dev/pandas/issues/31215
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553,721,622
MDExOlB1bGxSZXF1ZXN0MzY2MDA0Mjc0
31,215
Follow-up: XLSB Support
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2020-01-22T18:38:45Z
2020-02-01T20:33:13Z
2020-01-22T20:11:24Z
CONTRIBUTOR
null
Updated min version for `pyxlsb` to 1.0.6 and removed the now unnecessary xfail for read from url. Turns out the other xfail is actually unnecessary so I've removed it. Question: is my name supposed to show up in the contributors list? - [X] closes #8540 - [X] tests added / passed - [X] passes `black pandas` -...
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553,725,253
MDExOlB1bGxSZXF1ZXN0MzY2MDA3Mjkx
31,216
(wip) BUG: replacing one column's values was changing other columns' dtypes
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2020-01-22T18:46:30Z
2020-10-10T14:14:46Z
2020-07-26T18:05:12Z
MEMBER
null
…s' dtypes - [x] closes #30512 - [x] tests added / passed - [x] passes `black pandas` - [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff` - [x] whatsnew entry
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MDExOlB1bGxSZXF1ZXN0MzY2MDE2NDQy
31,217
DOC: fixup whatsnew
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2020-01-22T19:09:30Z
2020-01-22T19:38:00Z
2020-01-22T19:37:57Z
CONTRIBUTOR
null
The lack of newline below the ipython directive may be causing issues.
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BUG: DTA/TDA setitem breaks freq on views
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2020-01-22T19:46:25Z
2020-07-10T13:58:36Z
null
MEMBER
null
DatetimeArray/TimedeltaArray `__setitem__` resets the array's freq to None, but this doesn't propagate to views: ``` dti = pd.date_range('2016-01-01', periods=5) dta = dti._data view = dta[:] assert view.freq == dta.freq == "D" dta[0] = pd.NaT assert dta.freq is None >>> view.freq <Day> ``` `view.fre...
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31,219
ENH: maybe_dispatch_to_dunder_op handle min/max
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2020-01-22T19:56:19Z
2020-09-02T23:44:08Z
2020-09-02T23:44:08Z
MEMBER
null
I'm running up against a case where I need np.maximum.reduce(period_array) to work; itd be nice if that could be handled by maybe_dispatch to call PeriodArray.max cc @jorisvandenbossche @TomAugspurger
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31,220
Index.sort_values puts missing values at the start with ascending=False
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2020-01-22T19:56:25Z
2020-09-20T20:47:21Z
2020-09-20T20:47:21Z
CONTRIBUTOR
null
#### Code Sample, a copy-pastable example if possible Index.sort_values places missing values at the start of the result with `ascending=False` ```python In [4]: pd.Index([1, np.nan, 0]).sort_values(ascending=False) Out[4]: Float64Index([nan, 1.0, 0.0], dtype='float64') In [5]: pd.Series([1, np.nan, 0]).sort...
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31,221
Backport PR #31215 on branch 1.0.x (Follow-up: XLSB Support)
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2020-01-22T20:11:35Z
2020-01-23T09:40:20Z
2020-01-22T21:08:55Z
NONE
null
Backport PR #31215: Follow-up: XLSB Support
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Empty DatetimeIndex gets converted on assignment with .loc
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2020-01-22T21:57:38Z
2020-01-23T09:52:06Z
2020-01-23T09:52:05Z
NONE
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#### Code Sample ```python from pandas import DataFrame, Series, DatetimeIndex from numpy import float64 df = DataFrame(index=DatetimeIndex([]), columns=["A", "B"]).astype({"A": float64}) df.loc[:, "A"] = Series(index=df.index, dtype=float64) type(df.index) ``` #### Output ```python pandas.core.indexe...
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31,223
GroupBy aggregation fails if DataFrame has CategoricalIndex
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2020-01-22T22:47:16Z
2020-01-28T01:57:19Z
2020-01-28T01:57:19Z
NONE
null
#### Code Sample, a copy-pastable example if possible ```python ids = pd.Categorical([0, 1, 2]) df = pd.DataFrame({ 'id': ids, 'groups': [1, 1, 2], 'value': [0, 1, 0] }).set_index('id') df.groupby('groups').agg({'value': pd.Series.nunique}) ``` #### Problem description The above works in v....
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31,224
REF/TST: collect misplaced tests
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2020-01-22T22:49:36Z
2020-01-23T17:20:01Z
2020-01-23T14:25:31Z
MEMBER
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ATM we are mixing/matching pytest vs UnitTest idioms, which is confusing for me because I have to track down both inheritance and fixtures. So I'm trying to clean this up, leading to some yak shaving.
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MDU6SXNzdWU1NTM4NDI2MDk=
31,225
Make the documentation for pandas.Series.str.replace() clearer
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2020-01-22T22:55:42Z
2020-03-06T15:25:33Z
2020-03-06T15:25:33Z
NONE
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#### Problem description The current documentation of str.replace says ```Replace occurrences of pattern/regex in the Series/Index with some other string. Equivalent to str.replace() or re.sub().```. For the novice user this suggests that base Python's str.replace() and re.sub() provide equivalent functionality. ...
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31,226
CLN: unused kwarg, poorly named obj->key
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2020-01-22T23:21:17Z
2020-01-23T17:53:27Z
2020-01-23T17:53:24Z
MEMBER
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elsehwere we use `obj = self.obj` which is either a Series or DataFrame, better to call this `key` like we do elsewhere
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31,227
WIP: TST: pass random names in tm.makeDateIndex
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2020-01-22T23:26:18Z
2021-11-20T23:21:54Z
2020-01-29T16:11:35Z
MEMBER
null
@WillAyd nearly all of the remaining test failures locally are in the json tests. can you take a look and suggest whether we just need to pass `check_names=False` I expect if we do something like this we won't want to actually randomize; that part I guess is a proof of concept for now.
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TST: parametrize tests
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MEMBER
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- [ ] closes #xxxx - [x] tests added / passed - [x] passes `black pandas` - [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff` - [ ] whatsnew entry
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(Fixes CI) Replaced set comprehension with a generator
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- [x] closes #31149 - [x] tests added / passed - [x] passes `black pandas` - [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff` - [ ] whatsnew entry
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31,230
make TDI.get_value use get_loc, fix wrong-dtype NaT
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2020-01-23T00:30:46Z
2020-01-23T17:29:18Z
2020-01-23T14:27:36Z
MEMBER
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the wrong-dtype NaT is a bug, the DTI analogue is fixed in #31163. The refactor to make get_value is get_loc is basically what we want all of them index subclasses to do (at which point we de-duplicate and possibly get rid of get_value altogether) cc @jreback
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Backport PR #31229 on branch 1.0.x ((Fixes CI) Replaced set comprehension with a generator)
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Backport PR #31229: (Fixes CI) Replaced set comprehension with a generator
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REGR: Fix IntervalIndex.map when result is object dtype
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2020-01-23T01:22:55Z
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MEMBER
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- [X] closes #31202 - [X] tests added / passed - [X] passes `black pandas` - [X] passes `git diff upstream/master -u -- "*.py" | flake8 --diff` No whatnew since this is a regression.
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DOC ENH: Move DataFrame.info from "Serialization / IO / conversion" to "Attributes and underlying data"
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2020-01-23T02:01:47Z
2020-01-26T01:15:23Z
2020-01-26T01:15:23Z
CONTRIBUTOR
null
In the [API reference for DataFrame](https://pandas.pydata.org/pandas-docs/stable/reference/frame.html), why is `DataFrame.info()` in the "Serialization / IO / conversion" section? It would make more sense to me in the "Attributes and underlying data" section, which has similar methods and attributes like `DataFrame.me...
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DOC BUG DataFrame.plot() and Series.plot() documentation missing
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2020-01-23T02:07:43Z
2020-01-23T08:48:04Z
2020-01-23T08:48:04Z
CONTRIBUTOR
null
In the [API reference for `DataFrame.plot()`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.plot.html#pandas.DataFrame.plot) and [`Series.plot()`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.plot.html#pandas.Series.plot) the documentation is missing.
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DOC BUG API Reference documentation truncated for Series.unstack(), Series.
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2020-01-23T02:15:21Z
2020-01-24T17:49:58Z
2020-01-24T17:49:58Z
CONTRIBUTOR
null
The [API Reference documentation for `Series`](https://pandas.pydata.org/pandas-docs/stable/reference/series.html) and [`DataFrame`](https://pandas.pydata.org/pandas-docs/stable/reference/frame.html) have truncated documentation strings for `Series.at_time()`, `Series.unstack()`, and `DataFrame.at_time()`. The bug appe...
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WIP/TST: add dt64tz to indices fixture
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2020-01-23T02:21:51Z
2020-04-21T23:03:13Z
2020-01-23T18:41:15Z
MEMBER
null
@TomAugspurger @jorisvandenbossche as you can see, the `__array_ufunc__` that this implements is an unholy mess. This all came from a much smaller goal: I wanted to add the "datetime-tz" key in tests.indexes.conftest. That broke a test for `np.isfinite`, so I started implementing `array_ufunc`. Then that broke oth...
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CI: Fix Assign CI not working with quotes
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2020-01-23T02:28:50Z
2020-01-25T03:19:51Z
2020-01-25T03:17:39Z
MEMBER
null
- [x] closes #29768 - [x] passes `black pandas` - [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff` Examples(all three passed) ![image](https://user-images.githubusercontent.com/47963215/72952081-a6481100-3d45-11ea-8845-338f2a2f17a4.png)
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REGR: Prevent indexes that aren't directly backed by numpy from entering libreduction code paths
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2020-01-23T02:38:37Z
2020-01-30T09:59:53Z
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MEMBER
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- [X] closes #31223 - [X] closes #31248 - [X] tests added / passed - [X] passes `black pandas` - [X] passes `git diff upstream/master -u -- "*.py" | flake8 --diff` No whatsnew since this is a regression.
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COMPAT: tzawareness behavior to be same as datetime
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2020-01-23T02:59:44Z
2020-02-14T09:00:54Z
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MEMBER
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- [x] closes #28507 - [x] tests added / passed - [x] passes `black pandas` - [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff` - [ ] whatsnew entry
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31,240
Backport PR #31211 on branch 1.0.x (BUG: Fixed upcast dtype for datetime64 in merge)
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2020-01-23T04:26:44Z
2020-01-23T09:42:21Z
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Backport PR #31211: BUG: Fixed upcast dtype for datetime64 in merge
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TST: add tzaware case to indices fixture
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2020-01-23T05:36:36Z
2020-01-24T01:07:21Z
2020-01-24T00:59:33Z
MEMBER
null
Much easier alternative to #31236.
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ENH: add use_nullable_dtypes option in read_parquet
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2020-01-23T10:51:32Z
2020-11-29T16:15:15Z
2020-11-29T16:10:19Z
MEMBER
null
xref #29752, #30929 Using some work I am doing in pyarrow (https://github.com/apache/arrow/pull/6189), we are able to provide an option in `read_parquet` to directly use new nullable dtypes instead of first using the default conversion (eg which gives floats for ints with nulls) and doing the conversion afterwards ...
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554,089,655
MDU6SXNzdWU1NTQwODk2NTU=
31,243
Potential bug in reading SAS files with CHAR (RLE) compression and many repeated characters
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10
2020-01-23T11:08:19Z
2020-12-17T06:11:56Z
null
NONE
null
Hi, I think I ran into a bug in the RLE decompression implementation. **Short description**: String fields with more than 32 repeated consecutive characters are ~be~ cropped at 32 and next fields will spill over corrupting the whole dataframe. **Example**: example.csv with fields of length 50 ``` long_st...
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31,244
Backport PR #31167 on branch 1.0.x (DOC: fix DataFrame.plot docs )
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2020-01-23T12:35:26Z
2020-01-23T15:56:21Z
2020-01-23T13:25:57Z
NONE
null
Backport PR #31167: DOC: fix DataFrame.plot docs
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554,155,669
MDU6SXNzdWU1NTQxNTU2Njk=
31,245
Verbose parameter in pandas.Series.apply
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6
2020-01-23T13:26:45Z
2020-09-22T01:30:44Z
2020-09-22T01:30:43Z
NONE
null
Hi, I think it could be really useful to add a **Verbose** parameter in the **pandas.Series.apply** function. It can take a really long time to get an output so having some kind of verbosity with something like tqdm could be really useful. Cheers,
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31,246
Backport PR #31232 on branch 1.0.x (REGR: Fix IntervalIndex.map when result is object dtype)
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2020-01-23T14:16:12Z
2020-01-23T15:56:52Z
2020-01-23T15:23:12Z
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Backport PR #31232: REGR: Fix IntervalIndex.map when result is object dtype
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31,247
ENH: Implement DataFrame.value_counts
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2020-01-23T14:39:35Z
2020-02-26T02:24:35Z
2020-02-26T02:20:44Z
MEMBER
null
- [x] closes #5377 - [x] tests added / passed - [x] passes `black pandas` - [x] whatsnew entry This is picking up where https://github.com/pandas-dev/pandas/pull/27350 left off because I think it'd be a nice feature to have. At least one thing that still needs to be done is implementing `bins` when we have only a...
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31,248
REGR: CategoricalIndex and IntervalIndex are missing _index_data attribute
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2020-01-23T14:53:42Z
2020-01-28T01:57:19Z
2020-01-28T01:57:19Z
MEMBER
null
It looks like the `_index_data` attribute wasn't added to `CategoricalIndex` or `IntervalIndex`. This leads to some regressions with `GroupBy.apply`. Not sure what the fix should be, as there isn't a singular array that directly backs the underlying values for `CategoricalIndex` or `IntervalIndex`, so the approach ...
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31,249
TST: Fix timestamp comparison test
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2020-01-23T15:52:37Z
2020-01-24T16:00:07Z
2020-01-23T23:10:18Z
CONTRIBUTOR
null
- [x] closes #31175 - [x] tests added / passed - tests/scalar/timestamp/test_timestamp.py - [x] passes `black pandas` - [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff` - [ ] whatsnew entry - Not needed for fixing a test
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31,250
pd.DataFrame.duplicated, drop_duplicates does not support column operation
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2020-01-23T16:26:06Z
2020-01-27T17:54:14Z
2020-01-27T17:54:14Z
NONE
null
I was trying to use .duplicated to find identical columns, and possibly dropping them, but realized it doesn't do columnar operations. It would be great if pd.DataFrame.duplicated or pd.DataFrame.drop_duplicates supports axis= argument. Current version 0.25.3 not supporting axis= https://pandas.pydata.org/pandas-...
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31,251
read_csv: if parse_dates dont appear in use_cols, we get a trace
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2020-01-23T16:41:05Z
2020-03-17T00:03:12Z
2020-03-17T00:03:12Z
NONE
null
#### Code Sample, a copy-pastable example if possible ```python # Your code here import pandas as pd import io content = io.StringIO(''' time,val 212.23, 32 ''') date_cols = ['time'] df = pd.read_csv( content, sep=',', usecols=['val'], dtype= { 'val': int }, parse_dates=date_c...
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'test_factorize_empty' test failure with custom ExtensionDtype
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2020-01-23T17:38:24Z
2020-06-07T00:39:07Z
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CONTRIBUTOR
null
One of the provided (BaseMethods) Extension tests is `test_factorize_empty`. I don't have a way of passing this test given how `factorize` works for `ExtensionArray`. ```python def test_factorize_empty(self, data): codes, uniques = pd.factorize(data[:0]) expected_codes = np.array([], dtype=np...
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31,253
Update algorithms.py
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2020-01-23T17:43:04Z
2020-02-09T22:18:34Z
2020-02-09T22:18:34Z
CONTRIBUTOR
null
Pass the dtype to `_from_sequence` in `_reconstruct_data` in order to support ExtensionArrays with ExtensionDtypes that have parameters. - [ ] closes #31252 - [ ] tests added / passed - [ ] passes `black pandas` - [ ] passes `git diff upstream/master -u -- "*.py" | flake8 --diff` - [ ] whatsnew entry
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Backport PR #31187 on branch 1.0.x (BUG: IntegerArray.astype(boolean))
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2020-01-23T19:32:25Z
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Backport PR #31187: BUG: IntegerArray.astype(boolean)
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Backport PR #31025 on branch 1.0.x (ENH: Handle extension arrays in algorithms.diff)
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2020-01-23T19:33:20Z
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Backport PR #31025: ENH: Handle extension arrays in algorithms.diff
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Regression bugs when applying GroupBy Aggregations to Categorical columns
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2020-01-23T19:25:34Z
2020-01-29T20:20:53Z
2020-01-29T20:20:53Z
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```python >>> import pandas as pd >>> ids = range(5) >>> groups = pd.Series([0, 1, 1, 2, 2]) >>> values = pd.Categorical([0, 0, 0, 0, 1]) >>> df = pd.DataFrame({ 'id': ids, 'groups': groups, 'value': values }).set_index('id') >>> df.groupby('groups').agg(pd.Series...
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BUG: DatetimeIndex.get_loc/get_value raise InvalidIndexError
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almost done with the get_value/get_loc methods
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REF: avoid calling engine for EA values
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Please help me to understand TypeError: Expected tuple, got str
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2020-01-23T20:24:25Z
2020-01-24T17:19:09Z
2020-01-23T21:19:24Z
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#### Code Sample, a copy-pastable example if possible ```python # Summarize data by schools schools_group = complete_data_pd.groupby(["school_name"]) sum_students = schools_group["student_name"].value_counts() budgets_df = schools_group["budget"].mean() per_student = budgets_df / sum_students math_mavens_group...
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DOC fix truncated documentation for Series.unstack(), Series.
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2020-01-23T20:37:29Z
2020-01-24T19:30:59Z
2020-01-24T17:49:59Z
CONTRIBUTOR
null
fixes https://github.com/pandas-dev/pandas/issues/31235 Changed "e.g. " to "e.g., " Changed "a.k.a. " to "also known as" This helps avoid the truncation caused in the docstring
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Backport PR #31159 on branch 1.0.x (ENH: Implement _from_sequence_of_strings for BooleanArray)
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Backport PR #31159: ENH: Implement _from_sequence_of_strings for BooleanArray
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31,262
PLT: Color attributes of medianprops etc are lost in df.boxplot and df.plot.boxplot
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2020-01-23T21:32:22Z
2020-07-03T16:15:11Z
2020-02-11T21:27:08Z
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- [x] closes #30346 - [x] tests added / passed - [x] passes `black pandas` - [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff` - [x] whatsnew entry Found out that not only `medianprops` info is lost, so is `whiskerprops`, `capprops` and `boxprops`, so I also added them alongside. Since this is ...
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31,263
BUG: na_logical_op with 2D inputs
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2020-01-23T22:31:18Z
2020-01-24T17:44:19Z
2020-01-24T03:53:17Z
MEMBER
null
Broken off from a branch implementing block-wise ops for op(dataframe, dataframe)
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31,264
Cannot add pandas_profiling module into SQL Server
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2020-01-23T22:36:35Z
2020-01-23T23:13:04Z
2020-01-23T23:13:04Z
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#### Code Sample, a copy-pastable example if possible ```python import sqlmlutils connection = sqlmlutils.ConnectionInfo(server="localhost", database="SQLAI") sqlmlutils.SQLPackageManager(connection).install("pandas-profiling") ``` #### Problem description I was trying to install some module (i.e. pandas_pro...
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Backport PR #31249 on branch 1.0.x (TST: Fix timestamp comparison test)
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Backport PR #31249: TST: Fix timestamp comparison test
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REF: do alignment before _combine_series_frame
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2020-01-24T01:55:49Z
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This will allow us to de-duplicate _construct_result calls (this does so for _comp_method_FRAME) and ultimately move all of the alignment into _align_method_FRAME
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Backport PR #31036 on branch 1.0.x (BUG: AssertionError on Series.append(DataFrame) fix #30975 )
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2020-01-24T03:38:02Z
2020-01-24T04:34:47Z
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Backport PR #31036: BUG: AssertionError on Series.append(DataFrame) fix #30975
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BUG: passing TDA and wrong freq to TimedeltaIndex
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Caught while working towards making TimedeltaArray._simple_new more strict about its inputs. - [ ] closes #xxxx - [x] tests added / passed - [x] passes `black pandas` - [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff` - [ ] whatsnew entry
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31,269
ENH: allow 'pad', 'backfill' and 'cumcount' in groupby.transform
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2020-01-24T04:59:08Z
2020-06-03T23:28:11Z
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#### Summary Currently on master, `groupby.transform` with ``func`` equals one of `('fillna', 'pad', 'backfill', 'ffill', etc.)` yields wrong results (See #30918). With updates from PR (#31101), the incorrect outputs are fixed. However, when ``func`` is one of `('pad', 'backfill', 'cumcout')`, `groupby.transform` t...
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ENH: Move "corrwith" from transformation_kernels to reduction_kernels in groupby.base
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2020-01-24T05:08:26Z
2020-03-12T04:47:13Z
2020-03-12T04:47:13Z
MEMBER
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#### Code Sample ```python >>> import pandas as pd >>> pd.__version__ '1.0.0rc0+183.g4da554f75' >>> df = pd.DataFrame( ... { ... "A": [1, 1, 1, 1], ... "B": [0, 1, 2, 3] ... } ... ) >>> df A B 0 1 0 1 1 1 2 1 2 3 1 3 >>> df.groupby("A").corrwith(df) # Clearly co...
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https://api.github.com/repos/pandas-dev/pandas/issues/31271
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31,271
BUG: DataFrame.floordiv(ser, axis=0) not matching column-wise bheavior
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2020-01-24T05:30:30Z
2020-01-26T00:55:47Z
2020-01-26T00:37:02Z
MEMBER
null
We're pretty close to being able to combine _combine_frame and _combine_match_index (and hopefully get rid of them both before long)
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31,272
Dropped columns still available for filtering
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2020-01-24T06:17:57Z
2020-01-24T06:21:27Z
2020-01-24T06:20:43Z
NONE
null
#### Code Sample ```python3 import pandas as pd df = pd.DataFrame(data={'foo': [0, 1], 'bar': ["a", "b"]}) df.drop(columns=["bar"])[df["bar"] == "a"] ``` #### Problem description The code sample above should result in an error like the following: ``` KeyError: 'bar' ``` However, it does not but instead...
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31,273
ENH: make the mask optional in the nullable masked ExtensionArrays
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2020-01-24T07:50:08Z
2020-01-24T07:51:18Z
2020-01-24T07:51:18Z
MEMBER
null
Our nullable, mask-based ExtensionArrays (currently integer and boolean, inheriting from MaskedArray) have a `_data` and `_mask` numpy arrays stored under the hood. A relatively straight-forward optimization is probably to allow the `_mask` to be None, for the case that there are no missing values. (to be checked ...
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31,274
Performance issue when using pivot_table with multiple columns out of which at least one is of type 'category'
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2020-01-24T08:21:46Z
2020-01-24T15:03:12Z
2020-01-24T15:03:06Z
NONE
null
This issue was initially reported as #19622, which was then marked as a duplicate of #15217 and closed since then. However, this issue is still reproducible with the most recent version 0.25.3 To reproduce, copy-paste the following code and run: ```python import pandas as pd import numpy as np import time n...
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31,275
Backport PR #31037: PERF: improve access of .array
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2020-01-24T08:32:43Z
2020-01-24T09:06:39Z
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MEMBER
null
https://github.com/pandas-dev/pandas/pull/31037
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31,276
pandas.Series.str.replace giving irrelavent results
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2
2020-01-24T08:50:52Z
2020-01-24T13:49:50Z
2020-01-24T13:49:43Z
NONE
null
The following is my code: ```python import pandas as pd a = ['16', '66', '66', '42', '17', '55', '66b', '17', '48', '66', '48', '75', '76', '6a', '80', '57', '66', '13', '17', '31', '66', '6c', '17', '65b', '17', '39', '17', '66.0', '80.0', '6.0', '66.0', '21.0', '31.0', '7.0', '8.0'] df = pd...
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31,277
ASV: add benchmarks for Series.array and extract_array
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2020-01-24T09:14:35Z
2020-01-24T13:11:28Z
2020-01-24T13:09:50Z
MEMBER
null
Just thought it would be useful to have a benchmark for `.array` (now the performance regression of https://github.com/pandas-dev/pandas/pull/31037 was caught indirectly through an indexing benchmark)
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31,278
BUG: 27453 right merge order
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2020-01-24T12:08:57Z
2020-03-26T12:49:31Z
2020-03-26T12:45:39Z
MEMBER
null
Resurrection of #27762 I fixed the NameError in the test, and also changed the example given in the whatsnew entry (I couldn't see a difference between the outputs of 0.25.x and 1.0.0 in the original) - [x] closes #27453 - [x] tests added / passed - [x] passes `black pandas` - [x] passes `git diff upstream/mas...
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31,279
DOC: move convert_dtypes whatsnew to 1.0
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2020-01-24T13:45:32Z
2020-01-24T16:00:05Z
2020-01-24T14:29:06Z
CONTRIBUTOR
null
- [ ] closes #xxxx - [ ] tests added / passed - [ ] passes `black pandas` - [ ] passes `git diff upstream/master -u -- "*.py" | flake8 --diff` - [x] whatsnew entry - moved whatsnew entry from 1.1 to 1.0 Per comment here from @jreback: https://github.com/pandas-dev/pandas/pull/30929#issuecomment-577989924
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31,280
Fixes non-existent doc/source/api.rst issue
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2020-01-24T13:57:14Z
2020-01-25T06:00:03Z
2020-01-25T04:28:33Z
CONTRIBUTOR
null
Modified the path doc/source/api.rst
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CI: update azure VM image
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2020-01-24T14:00:44Z
2020-01-25T15:37:59Z
2020-01-25T15:37:59Z
CONTRIBUTOR
null
Email from Azure support > On March 23, 2020, we’ll be removing the following Azure Pipelines hosted images: > > * Windows Server 2012R2 with Visual Studio 2015, a.k.a vs2015-win2012r2 > * macOS X High Sierra 10.13, a.k.a macOS-10.13 > * Windows Server Core 1803, a.k.a win1803 > If you use YAML pipelines, upd...
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Backport PR #30929: ENH: Implement convert_dtypes'
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TYP: Type annotations in pandas/io/sas/sas_constants.py
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2020-01-24T15:12:41Z
2020-01-24T20:13:44Z
2020-01-24T19:06:31Z
MEMBER
null
- [ ] closes #xxxx - [ ] tests added / passed - [x] passes `black pandas` - [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff` - [ ] whatsnew entry
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Can't replace tz-aware with None
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2020-01-24T15:27:30Z
2020-01-24T15:29:31Z
2020-01-24T15:29:31Z
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#### Code Sample, a copy-pastable example if possible ```python import pandas as pd value_a = pd.Timestamp("20130102", tz="US/Eastern") value_b = pd.Timestamp("20130102", tz="US/Eastern") df = pd.DataFrame({"A": [value_a], "B": [value_b]}) df.replace(to_replace={value_a: None}).dtypes.drop("A") ``` #### Pro...
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added shuffle method to DataFrame
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2020-01-26T11:04:44Z
2020-01-26T09:52:21Z
NONE
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- [ ] closes #xxxx - [x] tests added / passed - [x] passes `black pandas` - [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff` - [ ] whatsnew entry I have added a shuffle method to pd.DataFrame, as writing df.sample(frac=1) is not intuitive. The method just calls df.sample with 1 line of code. T...
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Unexpected behaviour of `Series.rolling.corr` when using a `Timedelta` based window.
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2020-01-24T16:32:26Z
2020-12-28T00:03:23Z
2020-12-28T00:03:23Z
NONE
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#### Code Sample, a copy-pastable example if possible ```python import numpy as np import pandas as pd def f(x, y, window): return x.rolling(window).corr(y) def g(x, y, window): return x.rolling(window).apply(lambda x: x.corr(y), raw=False) if __name__ == "__main__": N = 20 n = 10 ...
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Allow .dt.month_name() and .dt.day_name() to return ordered categorical
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2020-01-24T21:42:15Z
2020-01-24T18:38:37Z
NONE
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#### Code Sample, a copy-pastable example if possible ```python import pandas as pd import numpy as np # A data frame with a date column dates = pd.date_range("2010-01-01", "2020-01-01", freq="1D").tolist() groups = ["first", "second", "third"] df = pd.DataFrame({ "date": dates * len(groups), "grou...
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REF: combine all alignment into _align_method_FRAME
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2020-01-24T17:22:04Z
2020-01-31T04:23:10Z
2020-01-31T03:36:34Z
MEMBER
null
This puts us within striking distance of de-duplicating _flex_comp_method_FRAME and _comp_method_FRAME, with _arith_method_FRAME not far behind
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Incorrect result in GroupBy.cov when some results have 1 observation
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2020-01-24T17:26:08Z
2020-01-24T17:27:33Z
2020-01-24T17:27:21Z
CONTRIBUTOR
null
If a user has configured warnings from NumPy to raise, and performs a `groupby.cov` when one or more groups has a single operation, then they'll get the wrong result. ```python In [1]: import warnings In [2]: warnings.filterwarnings("error", category=RuntimeWarning) In [3]: import pandas as pd; import num...
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BUG: Handle IntegerArray in pd.cut
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2020-01-24T18:18:11Z
2020-01-28T12:41:00Z
2020-01-28T01:52:09Z
CONTRIBUTOR
null
xref https://github.com/pandas-dev/pandas/issues/30944. I think this doesn't close it, since only the pd.cut compoment is fixed. cc @jorisvandenbossche @jreback. The changes here attempt to be extremely conservative, since we're backporting stuff. I'm trying to not change behavior for anything other than IntegerAr...
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31,291
is_iterator doctest incorrect for list
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2020-01-24T18:20:56Z
2020-01-26T01:38:02Z
2020-01-26T01:38:02Z
MEMBER
null
The docstring and doctest say that lists are considered iterators, but `isiterator([1, 2, 3])` (one of the docstring examples) returns False (which I think is a more useful behavior. Is this doctest not run?
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CI: Updated version of macos image
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2020-01-24T18:22:05Z
2020-01-30T12:42:20Z
2020-01-25T15:37:59Z
MEMBER
null
- [x] closes #31281 - [ ] tests added / passed - [ ] passes `black pandas` - [ ] passes `git diff upstream/master -u -- "*.py" | flake8 --diff` - [ ] whatsnew entry
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ENH: investigate using a bitarray as the mask in the nullable/masked ExtensionArrays
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2020-01-24T19:35:20Z
2020-04-28T06:03:02Z
null
MEMBER
null
Currently, our nullable / masked extension arrays (boolean, integer, for now) are using a numpy boolean array as their `_mask` to keep track of missing values. A potential route for improving memory and performance would be using a bitarray instead of a boolean numpy array (which is a byte per value). This should re...
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31,294
PERF: optimize is_scalar, is_iterator
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2020-01-24T19:58:26Z
2020-05-11T13:56:13Z
2020-01-26T00:34:33Z
MEMBER
null
While working on #30349 I noticed that `is_scalar` is pretty slow for non-scalar args, turns out we can get a 9-19x improvement for listlike cases, 5-10x improvement for Decimal/Period/DateOffset/Interval, with small improvements in nearly every other case while we're at it (the fractions.Fraction object is the only on...
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DOC: correct examples for "is_iterator"
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2020-01-24T20:34:49Z
2020-01-30T13:39:48Z
2020-01-30T13:39:34Z
MEMBER
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- [x] closes #31291 - [x] tests added / passed - [ ] passes `black pandas` - [ ] passes `git diff upstream/master -u -- "*.py" | flake8 --diff` - [ ] whatsnew entry
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PERF: do DataFrame.op(series, axis=0) blockwise
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2020-01-24T22:57:15Z
2020-03-08T16:28:25Z
2020-03-08T16:07:04Z
MEMBER
null
Also fixes the same bug as #31271 (with the same test ported), so if this is accepted that will be closeable. ~2000x speedups for very-wide mixed-dtype cases. ``` arr = np.arange(10**6).reshape(100, -1) df = pd.DataFrame(arr) df["C"] = 1.0 ser = df[0] In [11]: %timeit df.eq(ser, axis=0) 1.58 s ± 20 ms...
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REF: pass str_rep through arithmetic ops more consistently
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2020-01-24T23:11:03Z
2020-02-23T17:13:37Z
2020-02-23T16:18:50Z
MEMBER
null
This doesn't get all of the places where we fail to pass str_rep, still working out a couple of places where passing it breaks tests.
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Aggregate with categorical variables but without groupby
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2020-01-25T01:10:47Z
2020-09-05T19:11:16Z
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#### Code Sample, a copy-pastable example if possible ```python import pandas as pd df = pd.DataFrame( {"col_1" : [1, 2, 3, 4, 5], "col_2" : [3, 5, 3, 4, 9], "col_3" : ["cat", "dog", "dog", "cat", "cat"], "col_4" : ["feline", "canine", "canine", "feline",...
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DEPR: disallow series[[slice(...)]]
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2020-01-25T01:52:15Z
2020-02-09T17:08:54Z
2020-02-09T17:08:54Z
MEMBER
null
One of the more convoluted parts of `Series.__getitem__` is for handling single-entry lists that contain a slice, where we end up just returning `self[key[0]]`. We have two tests that hit this path, but it isn't clear to me why this should be supported.
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PERF: avoid copies if possible in fill_binop
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4
2020-01-25T02:01:57Z
2020-01-25T16:28:10Z
2020-01-25T16:20:21Z
MEMBER
null
This has a small perf bump, but more importantly is necessary for the blockwise frame-with-frame PR that is coming up. ``` import pandas as pd from pandas.core.ops import * arr = np.arange(10**6) df = pd.DataFrame({"A": arr}) ser = df["A"] %timeit result = df.add(df, fill_value=4) 7.77 ms ± 20.4 µs per lo...
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MDExOlB1bGxSZXF1ZXN0MzY3MDc5NjA3
31,301
CLN: remove _set_subtyp
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4
2020-01-25T02:37:01Z
2020-01-25T16:04:55Z
2020-01-25T16:01:40Z
MEMBER
null
its not used anywhere, apparently legacy leftover
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MDU6SXNzdWU1NTUwMzI2NTM=
31,302
ENH: Change default behavior of rolling.count to be consistent with others
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2020-01-25T02:41:42Z
2020-10-02T20:35:11Z
2020-10-02T20:35:11Z
MEMBER
null
Following on discussion happened in #30923, we may want to change the default behavior of `rolling.count` with regards to its parameter ``min_periods``, so it is consistent with all other similar APIs such as `rolling.mean` and `rolling.sum`. #### Code Sample With the updates from #30923 ```python >>> import nump...
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31,303
applymap fails in presence of nan values and function returning None
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1
2020-01-25T02:41:59Z
2020-01-26T03:44:45Z
2020-01-26T02:58:40Z
NONE
null
Is this the proper behavior? ```python df = pd.DataFrame([{'a': np.nan}, {'a': 3.5}]) def convert_cell(x): if isinstance(x, float): if math.isnan(x): return None else: return round(x) else: return x df.applymap(convert_cell) # gives # a...
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31,304
REF: define _get_slice_axis in correct classes
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2020-01-25T04:36:10Z
2020-01-26T00:46:49Z
2020-01-26T00:40:31Z
MEMBER
null
Since ix has been removed, a bunch of _NDFrameIndexer methods are defined in now-weird places. This fixes the one that confused me today.
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MDExOlB1bGxSZXF1ZXN0MzY3MDg3NDgz
31,305
POC: use typing.final
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2020-01-25T04:49:23Z
2020-02-28T00:18:52Z
2020-01-31T01:02:02Z
MEMBER
null
When working on index/indexing code I frequently find myself checking whether a method is overriden in subclasses. `@typing.final` marks a method as not-overriden in a way that mypy can check (py38+). This imports typing.final in py38+ and makes a dummy otherwise. We'd need to make sure the CI runs mypy in py38.
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MDU6SXNzdWU1NTUwNTMxMDA=
31,306
NaT values cannot be compared with tz-aware datetime objects
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2020-01-25T07:10:18Z
2020-01-26T02:10:56Z
2020-01-26T01:08:24Z
CONTRIBUTOR
null
#### Code Sample, a copy-pastable example if possible ```python import pandas import datetime a = pandas.DataFrame({'b': [pandas.NaT]}) a.b > datetime.datetime.now(datetime.timezone.utc) ``` Output: ``` Traceback (most recent call last): File "<stdin>", line 1, in <module> File ".../pandas/core/ops...
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31,307
Add test for multiindex json
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2020-01-25T12:42:39Z
2020-01-31T09:03:28Z
2020-01-25T16:19:06Z
CONTRIBUTOR
null
- [x] related to #31028 and adds test for #27618 - [x] tests added / passed - [x] passes `black pandas`
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31,308
pd.concat inconsistent with non-unique index
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2020-01-25T14:10:14Z
2021-07-27T05:19:13Z
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CONTRIBUTOR
null
#### Code Sample, a copy-pastable example if possible Following works: ```py df4 = pd.DataFrame([['bird', 'polly'], ['monkey', 'george'], ['a', 'b']], columns=['animal', 'name']) df1 = pd.DataFrame([['a', 1], ['b', 2]], columns=['letter', 'number']) df4.index = [0, 1, ...
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31,309
Backport PR #31292 on branch 1.0.x (CI: Updated version of macos image)
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2020-01-25T15:38:35Z
2020-01-25T16:08:09Z
2020-01-25T16:08:09Z
NONE
null
Backport PR #31292: CI: Updated version of macos image
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555,103,636
MDU6SXNzdWU1NTUxMDM2MzY=
31,310
CI: xfail sparse warning
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0
2020-01-25T16:17:07Z
2020-01-26T00:26:04Z
2020-01-26T00:26:04Z
CONTRIBUTOR
null
this is failing builds occasionally. not sure if its a deeper problem. can just xfail for now and investigate. https://travis-ci.org/pandas-dev/pandas/jobs/641752516 ``` =================================== FAILURES =================================== __________________________ test_legacy_sparse_warning _______...
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555,113,010
MDExOlB1bGxSZXF1ZXN0MzY3MTM2NTk2
31,311
xfail sparse warning; closes #31310
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2020-01-25T17:36:58Z
2020-01-26T00:26:20Z
2020-01-26T00:26:02Z
CONTRIBUTOR
null
xref #31310
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555,118,834
MDExOlB1bGxSZXF1ZXN0MzY3MTQwNTMz
31,312
BUG: MultiIndex intersection with sort=False does not preserve order
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2020-01-25T18:25:24Z
2020-02-12T16:04:32Z
2020-02-12T16:04:23Z
CONTRIBUTOR
null
- [x] closes #31325 - [x] tests added / passed - [x] passes `black pandas` - [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff` - [ ] whatsnew entry The intersection of 2 `MultiIndex` with `sort=False` does not preserve the order, whereas `Index. intersection()` does. This behavior does not seem ...
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31,313
Series logical operations with nullable Boolean data type
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1
2020-01-25T22:14:51Z
2020-01-25T22:26:00Z
2020-01-25T22:26:00Z
MEMBER
null
Should the `Series` logical operations also follow three-valued logic when using the nullable boolean data type? For example I would expect the two cases below to return `pd.NA`: ```python import pandas as pd pd.Series([True, None], dtype="boolean").all() # True pd.Series([False, None], dtype="boolean").any(...
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555,147,771
MDExOlB1bGxSZXF1ZXN0MzY3MTYxMzk2
31,314
REF: DatetimeIndex.get_value wrap DTI.get_loc
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2020-01-25T22:33:42Z
2020-01-26T00:38:36Z
2020-01-26T00:23:57Z
MEMBER
null
After this, DTI.get_value is identical to TDI.get_value. Separate PR to get PeriodIndex to match too, then de-duplicate.
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