BUG: agg function failed [how->mean,dtype->object]

[AAG-AZTEC]

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Reproducible Example

import numpy as np
import pandas as pd
data = {'planet': ['Mercury', 'Venus', 'Earth', 'Mars',
                   'Jupiter', 'Saturn', 'Uranus', 'Neptune'],
        'radius_km': [2440, 6052, 6371, 3390, 69911, 58232,
                     25362, 24622],
        'moons': [0, 0, 1, 2, 80, 83, 27, 14],
        'type': ['terrestrial', 'terrestrial', 'terrestrial', 'terrestrial',
                 'gas giant', 'gas giant', 'ice giant', 'ice giant'],
        'rings': ['no', 'no', 'no', 'no', 'yes', 'yes', 'yes','yes'],
        'mean_temp_c': [167, 464, 15, -65, -110, -140, -195, -200],
        'magnetic_field': ['yes', 'no', 'yes', 'no', 'yes', 'yes', 'yes', 'yes']
        }
planets = pd.DataFrame(data)
planets
planets.groupby(['type', 'magnetic_field']).mean()

Issue Description

The .groupby is not excluding the strings(objects) in this dataframe. In the older versions (1.3.5 pandas), this works for mean, min, max and even aggregate function.

Expected Behavior

agg function failed [how->mean,dtype->object]

Installed Versions

INSTALLED VERSIONS

commit : f538741
python : 3.12.1.final.0
python-bits : 64
OS : Windows
OS-release : 11
Version : 10.0.22631
machine : AMD64
processor : Intel64 Family 6 Model 140 Stepping 1, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United Kingdom.1252

pandas : 2.2.0
numpy : 1.26.3
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 69.0.3
pip : 23.3.2
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 5.0.1
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.19.0
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.2
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.8.2
numba : None
numexpr : None
odfpy : None
openpyxl : 3.1.2
pandas_gbq : None
pyarrow : 14.0.2
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.4
qtpy : None
pyqt5 : None

[Moutlou888]

I am too keep getting the same error while using this line ----> products.groupby(["Brand"]).mean()

[rhshadrach]

This behavior was changed in pandas 2.0: https://pandas.pydata.org/docs/whatsnew/v1.5.0.html#numeric-only-default-value

Specify .mean(numeric_only=True) if you'd like to keep the old behavior.

[sarwesh123]

Use this it will work fine

Assuming 'df' is your DataFrame and 'grouping_columns' are the columns you're grouping by

result = df.groupby(grouping_columns).mean(numeric_only=True)

[askchandan]

what if you're using .agg() function to perform multiple operations on the grouped columns.

eg : movies.groupby(['Director', 'Star1']).agg(['min', 'max', 'mean'])

It shows the same error (TypeError: agg function failed [how->mean,dtype->object])

Even after I used the numeric_only = True parameter, it returned

TypeError: Cannot use numeric_only=True with SeriesGroupBy.min and non-numeric dtypes.

Please help

[HardWorker-DaSc]

what if you're using .agg() function to perform multiple operations on the grouped columns.

eg : movies.groupby(['Director', 'Star1']).agg(['min', 'max', 'mean'])

It shows the same error (TypeError: agg function failed [how->mean,dtype->object])

Even after I used the numeric_only = True parameter, it returned

TypeError: Cannot use numeric_only=True with SeriesGroupBy.min and non-numeric dtypes.

Please help

you are trying to use the min() method on a data group that contains non-numeric (atypical) data types
you can use the .select_type() method to select only numeric columns before performing the addition operation.

df.select_types(include='number')

the .select_types(include='number') method selects only numeric columns from the Data Frame df

[deepakyadavfad]

not working for me.

[talkativewarrior]

@sarwesh123 This works like magic. Thank you so much

[Dineshbabu0603]

I"m using pandas version 2.2.2 still its not working

[Chakri3434]

used this :
if our df is DataFrame ------>
df.groupby(['Dataframe']).mean(numeric_only = True)

this feature is changed and readily available in documentation :)