Description
Pandas version checks
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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.
-
I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
#!/usr/bin/env python
import argparse
import pandas as pd
def main(args):
df_data = {
"A": ["A1", "A2", "A3", "A1"],
"B": ["B1", "B2", "B3", "B1"],
"C": [1.1, 1.2, 1.3, 1.4]
}
df = pd.DataFrame(df_data)
as_index = args.as_index
print("df:")
print(df)
print('---------')
print(f"Non-Category: Groupby non-agg, as_index={as_index}")
gdf = df.groupby(["A", "B"], as_index=as_index)["C"].sum()
print(gdf)
print('---------')
print(f"Non-Category: Groupby agg, as_index={as_index}")
gdf = df.groupby(["A", "B"], as_index=as_index).agg({"C": "sum"})
print(gdf)
print('---------')
df["A"] = df["A"].astype("category")
df["B"] = df["B"].astype("category")
print(f"Category: Groupby non-agg, as_index={as_index}")
gdf = df.groupby(["A", "B"], as_index=as_index)["C"].sum()
print(gdf)
print('---------')
print(f"Category: Groupby agg, as_index={as_index}")
gdf = df.groupby(["A", "B"], as_index=as_index).agg({"C": "sum"})
print(gdf)
print('---------')
if __name__ == "__main__":
parser = argparse.ArgumentParser(
description="Main script",
epilog="Example usage: python test_gb_with_cats.py filename",
)
parser.add_argument("--as-index", default=False, action="store_true")
args = parser.parse_args()
main(args)Issue Description
When using cateogry types as gb columns with as_index=True
Both df.groupby and df.groupby.agg work but the result seems to have all permutations of the underyling categories.
See output of reproducible example below
df:
A B C
0 A1 B1 1.1
1 A2 B2 1.2
2 A3 B3 1.3
3 A1 B1 1.4
---------
Non-Category: Groupby non-agg, as_index=True
A B
A1 B1 2.5
A2 B2 1.2
A3 B3 1.3
Name: C, dtype: float64
---------
Non-Category: Groupby agg, as_index=True
C
A B
A1 B1 2.5
A2 B2 1.2
A3 B3 1.3
---------
Category: Groupby non-agg, as_index=True
A B
A1 B1 2.5
B2 0.0
B3 0.0
A2 B1 0.0
B2 1.2
B3 0.0
A3 B1 0.0
B2 0.0
B3 1.3
Name: C, dtype: float64
---------
Category: Groupby agg, as_index=True
C
A B
A1 B1 2.5
B2 0.0
B3 0.0
A2 B1 0.0
B2 1.2
B3 0.0
A3 B1 0.0
B2 0.0
B3 1.3
---------
When using cateogry types as gb columns with as_index=False
df.groupby works but again the result seems to have all permutations of the underyling categories.
However, df.groupby.agg fails with a crpytic error message like
ValueError: Length of values (3) does not match length of index (9)
Expected Behavior
Both groupby and groupby.agg should work with/without as_index and shouldn't do a cross join on the underlying categories
Installed Versions
INSTALLED VERSIONS
commit : 66e3805
python : 3.7.13.final.0
python-bits : 64
OS : Darwin
OS-release : 20.6.0
Version : Darwin Kernel Version 20.6.0: Mon Aug 30 06:12:21 PDT 2021; root:xnu-7195.141.6~3/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_GB.UTF-8
LOCALE : en_GB.UTF-8
pandas : 1.3.5
numpy : 1.21.1
pytz : 2021.1
dateutil : 2.8.2
pip : 22.0.4
setuptools : 57.0.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : 1.3.7
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : 2.9.3 (dt dec pq3 ext lo64)
jinja2 : 3.0.1
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : 2021.07.0
fastparquet : None
gcsfs : None
matplotlib : 3.5.0
numexpr : None
odfpy : None
openpyxl : 3.0.7
pandas_gbq : None
pyarrow : 4.0.1
pyxlsb : None
s3fs : None
scipy : 1.7.0
sqlalchemy : 1.4.32
tables : None
tabulate : 0.8.9
xarray : None
xlrd : 1.1.0
xlwt : None
numba : 0.53.1