Description
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I have checked that this issue has not already been reported.
-
I have confirmed this bug exists on the latest version of pandas.
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I have confirmed this bug exists on the master branch of pandas.
Reproducible Example
import pandas as pd
df1 = pd.DataFrame({'a': [4, 4, 4], 'b': [1, 2, 3]}).astype({'a': 'float64', 'b': 'float64'})
# Nullable int 'Int64' gives wrong results. 'int64' works just fine.
df2 = pd.DataFrame({'a': [1, 2, 3], 'b': [1, 2, 3]}).astype({'a': 'Int64', 'b': 'float64'})
df1.compare(df2, keep_shape=True)Issue Description
The reproducible example returns
| ('a', 'self') | ('a', 'other') | ('b', 'self') | ('b', 'other') | |
|---|---|---|---|---|
| 0 | nan | 1 | nan | nan |
| 1 | nan | 2 | nan | nan |
| 2 | nan | 3 | nan | nan |
Expected Behavior
We expect the reproducible example to return
| ('a', 'self') | ('a', 'other') | ('b', 'self') | ('b', 'other') | |
|---|---|---|---|---|
| 0 | 4 | 1 | nan | nan |
| 1 | 4 | 2 | nan | nan |
| 2 | 4 | 3 | nan | nan |
Installed Versions
INSTALLED VERSIONS
commit : 73c6825
python : 3.8.10.final.0
python-bits : 64
OS : Linux
OS-release : 5.11.0-37-generic
Version : #41~20.04.2-Ubuntu SMP Fri Sep 24 09:06:38 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_SG.UTF-8
LOCALE : en_SG.UTF-8
pandas : 1.3.3
numpy : 1.21.2
pytz : 2021.1
dateutil : 2.8.2
pip : 21.1.1
setuptools : 56.0.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : 3.0.1
lxml.etree : 4.6.3
html5lib : None
pymysql : 0.8.1
psycopg2 : None
jinja2 : 2.11.3
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.4.3
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.7.1
sqlalchemy : 1.3.24
tables : None
tabulate : 0.8.7
xarray : None
xlrd : None
xlwt : None
numba : None