Description
Code Sample, a copy-pastable example if possible
import pandas as pd
from decimal import Decimal
df = pd.DataFrame({'id': [1], 'x': [1], 'y': [Decimal(1)]})
df.groupby('id')[['x', 'y']].sum()
# x
# id
# 1 1
Problem description
I unknowingly encountered the feature described here when running the above code. While I see how this can be a useful feature, it's a nuisance not knowing that it happened and that I can't disable it. I feel that in the case of doing a groupby on explicitly selected columns groupby(...)[COLS]
, it should not drop any columns and let whatever errors that occur raise. I also think that a warning could be added and/or an option to disable the feature.
Expected Output
# x y
# id
# 1 1 1
Output of pd.show_versions()
INSTALLED VERSIONS
commit: None
python: 3.6.2.final.0
python-bits: 64
OS: Linux
OS-release: 3.10.0-327.10.1.el7.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None
pandas: 0.22.0
pytest: 3.2.1
pip: 9.0.1
setuptools: 36.4.0
Cython: 0.28.1
numpy: 1.13.1
scipy: None
pyarrow: None
xarray: None
IPython: 6.1.0
sphinx: None
patsy: None
dateutil: 2.6.1
pytz: 2017.2
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 0.9999999
sqlalchemy: 1.1.13
pymysql: None
psycopg2: 2.7.1 (dt dec pq3 ext lo64)
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None