groupby apply failed on dataframe with DatetimeIndex #26182

goldenbull · 2019-04-22T06:40:17Z

Code Sample, a copy-pastable example if possible

# -*- coding: utf-8 -*-

import pandas as pd

def _do_calc_(_df):
    df2 = _df.copy()
    df2["vol_ma20"] = df2["volume"].rolling(20, min_periods=1).mean()
    return df2

dbars = pd.read_csv("2019.dbar_ftridx.csv.gz",
                    index_col=False,
                    encoding="utf-8-sig",
                    parse_dates=["trade_day"])
dbars = dbars.set_index("trade_day", drop=False)  # everything works fine if this line is commented
df = dbars.groupby("exchange").apply(_do_calc_)
print(len(df))

Problem description

here is the input data file:
2019.dbar_ftridx.csv.gz

this piece of code runs well with pandas 0.23, when upgraded to 0.24.2, it reports error:

Traceback (most recent call last):
  File "D:/test/groupby_bug.py", line 16, in <module>
    df = dbars.groupby("exchange").apply(_do_calc_)
  File "C:\Anaconda3\lib\site-packages\pandas\core\groupby\groupby.py", line 701, in apply
    return self._python_apply_general(f)
  File "C:\Anaconda3\lib\site-packages\pandas\core\groupby\groupby.py", line 712, in _python_apply_general
    not_indexed_same=mutated or self.mutated)
  File "C:\Anaconda3\lib\site-packages\pandas\core\groupby\generic.py", line 318, in _wrap_applied_output
    not_indexed_same=not_indexed_same)
  File "C:\Anaconda3\lib\site-packages\pandas\core\groupby\groupby.py", line 918, in _concat_objects
    sort=False)
  File "C:\Anaconda3\lib\site-packages\pandas\core\reshape\concat.py", line 228, in concat
    copy=copy, sort=sort)
  File "C:\Anaconda3\lib\site-packages\pandas\core\reshape\concat.py", line 292, in __init__
    obj._consolidate(inplace=True)
  File "C:\Anaconda3\lib\site-packages\pandas\core\generic.py", line 5156, in _consolidate
    self._consolidate_inplace()
  File "C:\Anaconda3\lib\site-packages\pandas\core\generic.py", line 5138, in _consolidate_inplace
    self._protect_consolidate(f)
  File "C:\Anaconda3\lib\site-packages\pandas\core\generic.py", line 5127, in _protect_consolidate
    result = f()
  File "C:\Anaconda3\lib\site-packages\pandas\core\generic.py", line 5136, in f
    self._data = self._data.consolidate()
  File "C:\Anaconda3\lib\site-packages\pandas\core\internals\managers.py", line 922, in consolidate
    bm = self.__class__(self.blocks, self.axes)
  File "C:\Anaconda3\lib\site-packages\pandas\core\internals\managers.py", line 114, in __init__
    self._verify_integrity()
  File "C:\Anaconda3\lib\site-packages\pandas\core\internals\managers.py", line 311, in _verify_integrity
    construction_error(tot_items, block.shape[1:], self.axes)
  File "C:\Anaconda3\lib\site-packages\pandas\core\internals\managers.py", line 1691, in construction_error
    passed, implied))
ValueError: Shape of passed values is (432, 27), indices imply (1080, 27)

If I do not call set_index() on the dataframe, it works fine. Seems there is something wrong with the DatetimeIndex?

I don't know if this error can be re-produced on your machine, I can re-produce the same error on all my machines.

Expected Output

4104

Output of `pd.show_versions()`

[paste the output of pd.show_versions() here below this line]
C:\Anaconda3\python.exe D:/test/groupby_bug.py

INSTALLED VERSIONS

commit: None
python: 3.7.3.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 79 Stepping 1, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.24.2
pytest: 4.4.0
pip: 19.0.3
setuptools: 41.0.0
Cython: 0.29.7
numpy: 1.16.2
scipy: 1.2.1
pyarrow: None
xarray: None
IPython: 7.4.0
sphinx: 2.0.1
patsy: 0.5.1
dateutil: 2.8.0
pytz: 2019.1
blosc: None
bottleneck: 1.2.1
tables: 3.5.1
numexpr: 2.6.9
feather: None
matplotlib: 3.0.3
openpyxl: 2.6.2
xlrd: 1.2.0
xlwt: 1.3.0
xlsxwriter: 1.1.6
lxml.etree: 4.3.3
bs4: 4.7.1
html5lib: 1.0.1
sqlalchemy: 1.3.3
pymysql: None
psycopg2: None
jinja2: 2.10.1
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None
None

The text was updated successfully, but these errors were encountered:

WillAyd · 2019-04-22T15:49:29Z

Can you provide a code sample that is self-contained, i.e. doesn't require the external file to reproduce the issue?

goldenbull · 2019-04-23T03:15:58Z

I picked up several rows from the csv file, here is the self-contained version:

# -*- coding: utf-8 -*-

import pandas as pd
from io import StringIO


def _do_calc_(_df):
    df2 = _df.copy()
    df2["ma20"] = df2["close"].rolling(20, min_periods=1).mean()
    return df2


data = """trade_day,exchange,code,close
2019-01-02,CFFEX,ic,4074
2019-01-02,DCE,a,3408
2019-01-02,DCE,b,2970
2019-01-02,SHFE,ag,3711
2019-01-02,SHFE,al,13446
2019-01-02,SHFE,au,288
2019-01-02,CZCE,ap,10678
2019-01-02,CZCE,cf,14870
2019-01-02,CZCE,cy,23811
2019-01-02,CZCE,fg,1284
2019-01-02,INE,sc,371
2019-01-03,CFFEX,ic,4062
2019-01-03,CFFEX,if,2962
2019-01-03,CFFEX,ih,2270
2019-01-03,CFFEX,t,98
2019-01-03,CFFEX,tf,99
2019-01-03,CFFEX,ts,100
2019-01-03,DCE,a,3439
2019-01-03,DCE,b,2969
2019-01-03,DCE,bb,134
2019-01-03,DCE,c,1874
2019-01-03,DCE,cs,2340
2019-01-03,DCE,eg,5119
2019-01-03,DCE,fb,84
2019-01-03,DCE,i,501
2019-01-03,DCE,j,1934
2019-01-03,DCE,jd,3488
2019-01-03,DCE,jm,1191
2019-01-03,DCE,l,8459
2019-01-03,DCE,m,2676
2019-01-03,DCE,p,4627
2019-01-03,DCE,pp,8499
2019-01-03,DCE,v,6313
2019-01-03,DCE,y,5506
2019-01-03,SHFE,ag,3763
2019-01-03,SHFE,al,13348
2019-01-03,SHFE,au,290
2019-01-03,SHFE,bu,2628
2019-01-03,SHFE,cu,47326
2019-01-03,SHFE,fu,2396
2019-01-03,SHFE,hc,3337
2019-01-03,SHFE,ni,88385
2019-01-03,SHFE,pb,17804
2019-01-03,SHFE,rb,3429
2019-01-03,SHFE,ru,11485
2019-01-03,SHFE,sn,143901
2019-01-03,SHFE,sp,5067
2019-01-03,SHFE,wr,3560
2019-01-03,SHFE,zn,20071
2019-01-03,CZCE,ap,10476
2019-01-03,CZCE,cf,14846
2019-01-03,CZCE,cy,23679
2019-01-03,CZCE,fg,1302
2019-01-03,CZCE,jr,2853
2019-01-03,CZCE,lr,2634
2019-01-03,CZCE,ma,2439
2019-01-03,CZCE,oi,6526
2019-01-03,CZCE,pm,2268
2019-01-03,CZCE,ri,2430
2019-01-03,CZCE,rm,2142
2019-01-03,CZCE,rs,5405
2019-01-03,CZCE,sf,5735
2019-01-03,CZCE,sm,7408
2019-01-03,CZCE,sr,4678
2019-01-03,CZCE,ta,5677
2019-01-03,CZCE,wh,2411
2019-01-03,CZCE,zc,563
2019-01-03,INE,sc,385"""

dbars = pd.read_csv(StringIO(data), index_col=False, parse_dates=["trade_day"])
dbars = dbars.set_index("trade_day", drop=False)  # everything works fine if this line is commented
df = dbars.groupby("exchange").apply(_do_calc_)
print(len(df))

goldenbull · 2019-09-24T09:07:46Z

any update? seems not fixed in v0.25.1

goldenbull · 2020-02-02T13:45:59Z

seems fixed in 1.0.0 👍

jreback · 2020-02-02T13:53:15Z

would take a validation test with the above example (or if u can pinpoint an existing test which replicates)

simonjayhawkins · 2020-04-04T19:48:00Z

seems fixed in 1.0.0 👍

This was fixed in #28662

7c9042a is the first new commit
commit 7c9042a
Author: Daniel Saxton [email protected]
Date: Wed Jan 1 10:21:27 2020 -0600

BUG: Fix groupby.apply (#28662)

simonjayhawkins · 2020-04-04T21:49:24Z

the code sample above gives the following traceback with 0.25.3 (expand details)

>>> import pandas as pd
>>> from io import StringIO
>>>
>>>
>>> def _do_calc_(_df):
...     df2 = _df.copy()
...     df2["ma20"] = df2["close"].rolling(20, min_periods=1).mean()
...     return df2
...
>>>
>>> data = """trade_day,exchange,code,close
... 2019-01-02,CFFEX,ic,4074
... 2019-01-02,DCE,a,3408
... 2019-01-02,DCE,b,2970
... 2019-01-02,SHFE,ag,3711
... 2019-01-02,SHFE,al,13446
... 2019-01-02,SHFE,au,288
... 2019-01-02,CZCE,ap,10678
... 2019-01-02,CZCE,cf,14870
... 2019-01-02,CZCE,cy,23811
... 2019-01-02,CZCE,fg,1284
... 2019-01-02,INE,sc,371
... 2019-01-03,CFFEX,ic,4062
... 2019-01-03,CFFEX,if,2962
... 2019-01-03,CFFEX,ih,2270
... 2019-01-03,CFFEX,t,98
... 2019-01-03,CFFEX,tf,99
... 2019-01-03,CFFEX,ts,100
... 2019-01-03,DCE,a,3439
... 2019-01-03,DCE,b,2969
... 2019-01-03,DCE,bb,134
... 2019-01-03,DCE,c,1874
... 2019-01-03,DCE,cs,2340
... 2019-01-03,DCE,eg,5119
... 2019-01-03,DCE,fb,84
... 2019-01-03,DCE,i,501
... 2019-01-03,DCE,j,1934
... 2019-01-03,DCE,jd,3488
... 2019-01-03,DCE,jm,1191
... 2019-01-03,DCE,l,8459
... 2019-01-03,DCE,m,2676
... 2019-01-03,DCE,p,4627
... 2019-01-03,DCE,pp,8499
... 2019-01-03,DCE,v,6313
... 2019-01-03,DCE,y,5506
... 2019-01-03,SHFE,ag,3763
... 2019-01-03,SHFE,al,13348
... 2019-01-03,SHFE,au,290
... 2019-01-03,SHFE,bu,2628
... 2019-01-03,SHFE,cu,47326
... 2019-01-03,SHFE,fu,2396
... 2019-01-03,SHFE,hc,3337
... 2019-01-03,SHFE,ni,88385
... 2019-01-03,SHFE,pb,17804
... 2019-01-03,SHFE,rb,3429
... 2019-01-03,SHFE,ru,11485
... 2019-01-03,SHFE,sn,143901
... 2019-01-03,SHFE,sp,5067
... 2019-01-03,SHFE,wr,3560
... 2019-01-03,SHFE,zn,20071
... 2019-01-03,CZCE,ap,10476
... 2019-01-03,CZCE,cf,14846
... 2019-01-03,CZCE,cy,23679
... 2019-01-03,CZCE,fg,1302
... 2019-01-03,CZCE,jr,2853
... 2019-01-03,CZCE,lr,2634
... 2019-01-03,CZCE,ma,2439
... 2019-01-03,CZCE,oi,6526
... 2019-01-03,CZCE,pm,2268
... 2019-01-03,CZCE,ri,2430
... 2019-01-03,CZCE,rm,2142
... 2019-01-03,CZCE,rs,5405
... 2019-01-03,CZCE,sf,5735
... 2019-01-03,CZCE,sm,7408
... 2019-01-03,CZCE,sr,4678
... 2019-01-03,CZCE,ta,5677
... 2019-01-03,CZCE,wh,2411
... 2019-01-03,CZCE,zc,563
... 2019-01-03,INE,sc,385"""
>>>
>>> dbars = pd.read_csv(StringIO(data), index_col=False, parse_dates=["trade_day"])
>>> dbars = dbars.set_index(
...     "trade_day", drop=False
... )  # everything works fine if this line is commented
>>> df = dbars.groupby("exchange").apply(_do_calc_)
Traceback (most recent call last):
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\groupby\groupby.py", line 725, in apply
    result = self._python_apply_general(f)
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\groupby\groupby.py", line 745, in _python_apply_general
    keys, values, not_indexed_same=mutated or self.mutated
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\groupby\generic.py", line 372, in _wrap_applied_output
    return self._concat_objects(keys, values, not_indexed_same=not_indexed_same)
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\groupby\groupby.py", line 973, in _concat_objects
    sort=False,
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\reshape\concat.py", line 258, in concat
    return op.get_result()
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\reshape\concat.py", line 473, in get_result
    mgrs_indexers, self.new_axes, concat_axis=self.axis, copy=self.copy
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\internals\managers.py", line 2059, in concatenate_block_managers
    return BlockManager(blocks, axes)
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\internals\managers.py", line 143, in __init__
    self._verify_integrity()
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\internals\managers.py", line 345, in _verify_integrity
    construction_error(tot_items, block.shape[1:], self.axes)
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\internals\managers.py", line 1719, in construction_error
    "Shape of passed values is {0}, indices imply {1}".format(passed, implied)
ValueError: Shape of passed values is (68, 5), indices imply (90, 5)

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\groupby\groupby.py", line 737, in apply
    return self._python_apply_general(f)
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\groupby\groupby.py", line 745, in _python_apply_general
    keys, values, not_indexed_same=mutated or self.mutated
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\groupby\generic.py", line 372, in _wrap_applied_output
    return self._concat_objects(keys, values, not_indexed_same=not_indexed_same)
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\groupby\groupby.py", line 973, in _concat_objects
    sort=False,
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\reshape\concat.py", line 258, in concat
    return op.get_result()
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\reshape\concat.py", line 473, in get_result
    mgrs_indexers, self.new_axes, concat_axis=self.axis, copy=self.copy
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\internals\managers.py", line 2059, in concatenate_block_managers
    return BlockManager(blocks, axes)
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\internals\managers.py", line 143, in __init__
    self._verify_integrity()
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\internals\managers.py", line 345, in _verify_integrity
    construction_error(tot_items, block.shape[1:], self.axes)
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\internals\managers.py", line 1719, in construction_error
    "Shape of passed values is {0}, indices imply {1}".format(passed, implied)
ValueError: Shape of passed values is (68, 4), indices imply (90, 4)
>>>

The following snippet follows the same path

>>> df = pd.DataFrame(
...     {"foo": list("ababb"), "bar": range(5)},
...     index=pd.DatetimeIndex(
...         ["1/1/2000", "1/1/2000", "2/1/2000", "2/1/2000", "2/1/2000"]
...     ),
... )
>>> df.groupby("foo").apply(lambda df: df.copy())
Traceback (most recent call last):
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\groupby\groupby.py", line 725, in apply
    result = self._python_apply_general(f)
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\groupby\groupby.py", line 745, in _python_apply_general
    keys, values, not_indexed_same=mutated or self.mutated
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\groupby\generic.py", line 372, in _wrap_applied_output
    return self._concat_objects(keys, values, not_indexed_same=not_indexed_same)
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\groupby\groupby.py", line 973, in _concat_objects
    sort=False,
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\reshape\concat.py", line 258, in concat
    return op.get_result()
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\reshape\concat.py", line 473, in get_result
    mgrs_indexers, self.new_axes, concat_axis=self.axis, copy=self.copy
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\internals\managers.py", line 2059, in concatenate_block_managers
    return BlockManager(blocks, axes)
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\internals\managers.py", line 143, in __init__
    self._verify_integrity()
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\internals\managers.py", line 345, in _verify_integrity
    construction_error(tot_items, block.shape[1:], self.axes)
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\internals\managers.py", line 1719, in construction_error
    "Shape of passed values is {0}, indices imply {1}".format(passed, implied)
ValueError: Shape of passed values is (5, 2), indices imply (6, 2)

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\groupby\groupby.py", line 737, in apply
    return self._python_apply_general(f)
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\groupby\groupby.py", line 745, in _python_apply_general
    keys, values, not_indexed_same=mutated or self.mutated
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\groupby\generic.py", line 372, in _wrap_applied_output
    return self._concat_objects(keys, values, not_indexed_same=not_indexed_same)
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\groupby\groupby.py", line 973, in _concat_objects
    sort=False,
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\reshape\concat.py", line 258, in concat
    return op.get_result()
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\reshape\concat.py", line 473, in get_result
    mgrs_indexers, self.new_axes, concat_axis=self.axis, copy=self.copy
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\internals\managers.py", line 2059, in concatenate_block_managers
    return BlockManager(blocks, axes)
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\internals\managers.py", line 143, in __init__
    self._verify_integrity()
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\internals\managers.py", line 345, in _verify_integrity
    construction_error(tot_items, block.shape[1:], self.axes)
  File "C:\Users\simon\Anaconda3\lib\site-packages\pandas\core\internals\managers.py", line 1719, in construction_error
    "Shape of passed values is {0}, indices imply {1}".format(passed, implied)
ValueError: Shape of passed values is (5, 1), indices imply (6, 1)
>>>

and on master ...

>>> import pandas as pd
>>> pd.__version__
'1.1.0.dev0+1108.gcad602e16'
>>> df = pd.DataFrame(
...     {"foo": list("ababb"), "bar": range(5)},
...     index=pd.DatetimeIndex(
...         ["1/1/2000", "1/1/2000", "2/1/2000", "2/1/2000", "2/1/2000"]
...     ),
... )
>>> df.groupby("foo").apply(lambda df: df.copy())
               foo  bar
foo
a   2000-01-01   a    0
    2000-02-01   a    2
b   2000-01-01   b    1
    2000-02-01   b    3
    2000-02-01   b    4
>>>

amy12xx · 2020-09-24T14:42:30Z

This looks fixed in 1.1.2


Python 3.7.3 (default, Apr 24 2019, 15:29:51) [MSC v.1915 64 bit (AMD64)] :: Anaconda, Inc. on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import pandas as pd
>>> pd.__version__
'1.1.2'
>>> df = pd.DataFrame({"foo": list("ababb"), "bar": range(5)},index=pd.DatetimeIndex(["1/1/2000", "1/1/2000", "2/1/2000", "2/1/2000", "2/1/2000"]),)
>>> df.groupby("foo").apply(lambda df: df.copy())
               foo  bar
foo
a   2000-01-01   a    0
    2000-02-01   a    2
b   2000-01-01   b    1
    2000-02-01   b    3
    2000-02-01   b    4
>>> exit()

Python 3.8.5 | packaged by conda-forge | (default, Aug 29 2020, 00:43:28) [MSC v.1916 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import pandas as pd
>>> pd.__version__
'1.2.0.dev0+328.g2067d7e30'
>>> df = pd.DataFrame({"foo": list("ababb"), "bar": range(5)},index=pd.DatetimeIndex(["1/1/2000", "1/1/2000", "2/1/2000", "2/1/2000", "2/1/2000"]),)
>>> df.groupby("foo").apply(lambda df: df.copy())
               foo  bar
foo
a   2000-01-01   a    0
    2000-02-01   a    2
b   2000-01-01   b    1
    2000-02-01   b    3
    2000-02-01   b    4
>>>

simonjayhawkins · 2020-09-24T15:20:19Z

Thanks @amy12xx would you like to submit a PR with a test? see #26182 (comment)

simonjayhawkins · 2020-09-24T15:21:59Z

can use code sample in #26182 (comment) as validation test.

amy12xx · 2020-09-25T03:29:24Z

Sure, I can do that.

WillAyd added the Needs Info Clarification about behavior needed to assess issue label Apr 22, 2019

gfyoung added Groupby Indexing Related to indexing on series/frames, not to indexes themselves Regression Functionality that used to work in a prior pandas version and removed Needs Info Clarification about behavior needed to assess issue labels Apr 23, 2019

jbrockmendel added Needs Tests Unit test(s) needed to prevent regressions and removed Indexing Related to indexing on series/frames, not to indexes themselves labels Feb 18, 2020

simonjayhawkins removed Groupby Regression Functionality that used to work in a prior pandas version labels Apr 4, 2020

simonjayhawkins added the good first issue label Apr 4, 2020

simonjayhawkins added this to the Contributions Welcome milestone Apr 4, 2020

amy12xx mentioned this issue Sep 26, 2020

[MRG] TST: Added test for groupby apply datetimeindex fix #36671

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jreback modified the milestones: Contributions Welcome, 1.2 Oct 2, 2020

jreback added Groupby Datetime Datetime data dtype labels Oct 2, 2020

mroeschke closed this as completed in #36671 Oct 2, 2020

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groupby apply failed on dataframe with DatetimeIndex #26182

groupby apply failed on dataframe with DatetimeIndex #26182

goldenbull commented Apr 22, 2019

INSTALLED VERSIONS

WillAyd commented Apr 22, 2019

goldenbull commented Apr 23, 2019

goldenbull commented Sep 24, 2019

goldenbull commented Feb 2, 2020

jreback commented Feb 2, 2020

simonjayhawkins commented Apr 4, 2020

simonjayhawkins commented Apr 4, 2020

amy12xx commented Sep 24, 2020

simonjayhawkins commented Sep 24, 2020

simonjayhawkins commented Sep 24, 2020

amy12xx commented Sep 25, 2020

groupby apply failed on dataframe with DatetimeIndex #26182

groupby apply failed on dataframe with DatetimeIndex #26182

Comments

goldenbull commented Apr 22, 2019

Code Sample, a copy-pastable example if possible

Problem description

Expected Output

Output of pd.show_versions()

INSTALLED VERSIONS

WillAyd commented Apr 22, 2019

goldenbull commented Apr 23, 2019

goldenbull commented Sep 24, 2019

goldenbull commented Feb 2, 2020

jreback commented Feb 2, 2020

simonjayhawkins commented Apr 4, 2020

simonjayhawkins commented Apr 4, 2020

amy12xx commented Sep 24, 2020

simonjayhawkins commented Sep 24, 2020

simonjayhawkins commented Sep 24, 2020

amy12xx commented Sep 25, 2020

Output of `pd.show_versions()`