BUG: Label and integer based indexing return different values for same column #45684
Description
Pandas version checks
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Reproducible Example
import numpy as np import pandas as pd def main(): # create a data frame # dtypes must be the same for the issue to occur data = {'x': np.arange(8, dtype=np.int64), 'y': np.int64(0)} df = pd.DataFrame(data) # These next three lines are necessary to produce the issue. df = df.copy() data = df['y'] df.iat[7, df.columns.get_loc('x')] = 9999 # set the last row of column y to a desired value df.iat[7, df.columns.get_loc('y')] = 1234 # compare get values for at and iat atValue = df.at[7, 'y'] iatValue = df.iat[7, df.columns.get_loc('y')] print(iatValue, atValue, iatValue == atValue) # inspect data print("\nThe DataFrame:") print(df) print("\nLabel Based:") print(df['y']) print("\nInteger Based:") print(df.iloc[:, df.columns.get_loc('y')]) if __name__ == '__main__': main()Issue Description
In the above example, a value of 1234 was set to the last row in column 'y' using an integer based method of indexing. However, if using a label based method of indexing to view the values, it returns the original value of 0 instead of 1234. This issue does not occur on pandas version 1.3.5.
1234 0 False The DataFrame: x y 0 0 0 1 1 0 2 2 0 3 3 0 4 4 0 5 5 0 6 6 0 7 9999 1234 Label Based: 0 0 1 0 2 0 3 0 4 0 5 0 6 0 7 0 Name: y, dtype: int64 Integer Based: 0 0 1 0 2 0 3 0 4 0 5 0 6 0 7 1234 Name: y, dtype: int64 Expected Behavior
The label based method returns the correct value.
Installed Versions
INSTALLED VERSIONS
commit : bb1f651
python : 3.9.10.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.17763
machine : AMD64
processor : Intel64 Family 6 Model 142 Stepping 12, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252
pandas : 1.4.0
numpy : 1.22.1
pytz : 2021.3
dateutil : 2.8.2
pip : 21.3.1
setuptools : 60.5.0
Cython : 0.29.26
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.7.1
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : 1.3.2
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.5.1
numba : 0.53.1
numexpr : None
odfpy : None
openpyxl : 3.0.9
pandas_gbq : None
pyarrow : 6.0.1
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.7.3
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
zstandard : None