Description
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I have checked that this issue has not already been reported.
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I have confirmed this bug exists on the latest version of pandas.
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(optional) I have confirmed this bug exists on the master branch of pandas.
Note: Please read this guide detailing how to provide the necessary information for us to reproduce your bug.
Code Sample, a copy-pastable example
# Your code here
import numpy as np
import pandas as pd
df = pd.DataFrame({'a':[1, 1, np.NaN, np.NaN], 'b':[10, np.NaN, 40, np.NaN]})df
a b
0 1.0 10.0
1 1.0 NaN
2 NaN 40.0
3 NaN NaN
# Case 1 - Forward fill using fillna
df.groupby(["a"]).fillna(method="ffill")
df
b
0 10.0
1 10.0
2 NaN
3 NaN
# Case 2 - Forward fill using ffill
df.groupby(["a"]).ffill()
df
b
0 10.0
1 10.0
2 40.0
3 40.0
Problem description
df.groupby(["a"]).ffill() is not ignoring the NaN group while performing forward fill.
Expected Output
df.groupby(["a"]).ffill() should give the same output as df.groupby(["a"]).fillna(method="ffill") since NaN groups are ignored as per https://pandas.pydata.org/pandas-docs/stable/user_guide/missing_data.html#na-values-in-groupby.
Output of pd.show_versions()
INSTALLED VERSIONS
commit : None
python : 3.8.3.final.0
python-bits : 64
OS : Darwin
OS-release : 16.7.0
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : None
LOCALE : en_US.UTF-8
pandas : 1.0.4
numpy : 1.18.1
pytz : 2019.3
dateutil : 2.8.1
pip : 20.0.2
setuptools : 44.0.0.post20200106
Cython : None
pytest : 5.4.3
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
fastparquet : None
gcsfs : None
lxml.etree : None
matplotlib : 3.1.2
numexpr : None
odfpy : None
openpyxl : 3.0.3
pandas_gbq : None
pyarrow : 0.17.0
pytables : None
pytest : 5.4.3
pyxlsb : None
s3fs : 0.4.2
scipy : None
sqlalchemy : None
tables : None
tabulate : 0.8.6
xarray : None
xlrd : None
xlwt : None
xlsxwriter : None
numba : None