Groupby on single key should be accessible by tuple of length 1

[KeithWM]

Code Sample, a copy-pastable example if possible

import pandas as pd

df = pd.DataFrame(data={'col1': [1, 2], 'col2': [3, 4], 'col3': [5, 6]})


def select_by_dict(dataframe, d):
    return dataframe.groupby(list(d.keys())).get_group(tuple(d.values()))


select_by_dict(df, {'col1': 1, 'col2': 3})
select_by_dict(df, {'col1': 1})  # this one fails

Problem description

I would like to use a dictionary of arbitrary length to select certain groups from a DataFrame, but if I group by a single key, it won't accept a tuple of length 1 as the key value.

Expected Output

I expect the second call to the function to return a DataFrame containing those values for which col1 == 1. (I.e. as df[df['col1'] == 1]). Perhaps my approach is ill-advised, but I have come across this problem before in situations where it was more obvious to use groupby (in the current case it might well be better to use boolean indexing).

Output of pd.show_versions()

INSTALLED VERSIONS ------------------ commit: None python: 3.6.1.final.0 python-bits: 64 OS: Darwin OS-release: 18.2.0 machine: x86_64 processor: i386 byteorder: little LC_ALL: None LANG: None LOCALE: None.None pandas: 0.23.3 pytest: 3.3.1 pip: 18.1 setuptools: 36.6.0 Cython: 0.29.5 numpy: 1.14.5 scipy: 1.1.0 pyarrow: None xarray: None IPython: 5.4.0 sphinx: None patsy: 0.4.1 dateutil: 2.6.1 pytz: 2017.3 blosc: None bottleneck: None tables: 3.4.2 numexpr: 2.6.4 feather: None matplotlib: 2.0.2 openpyxl: 2.5.4 xlrd: 1.1.0 xlwt: None xlsxwriter: None lxml: None bs4: 4.7.1 html5lib: 0.9999999 sqlalchemy: None pymysql: None psycopg2: None jinja2: 2.10 s3fs: None fastparquet: None pandas_gbq: None pandas_datareader: None

I hope you find this a useful issue.

[WillAyd]

I think this is a duplicate we already closed. Can you check

…

Sent from my iPhone

On Apr 3, 2019, at 2:12 AM, KeithWM ***@***.***> wrote: Code Sample, a copy-pastable example if possible import pandas as pd df = pd.DataFrame(data={'col1': [1, 2], 'col2': [3, 4], 'col3': [5, 6]}) def select_by_dict(dataframe, d): return dataframe.groupby(list(d.keys())).get_group(tuple(d.values())) select_by_dict(df, {'col1': 1, 'col2': 3}) select_by_dict(df, {'col1': 1}) # this one fails Problem description I would like to use a dictionary of arbitrary length to select certain groups from a DataFrame, but if I group by a single key, it won't accept a tuple of length 1 as the key value. Expected Output I expect the second call to the function to return a DataFrame containing those values for which col1 == 1. (I.e. as df[df['col1'] == 1]). Perhaps my approach is ill-advised, but I have come across this problem before in situations where it was more obvious to use groupby (in the current case it might well be better to use boolean indexing). Output of pd.show_versions() I hope you find this a useful issue. — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub, or mute the thread.

[KeithWM]

I did do a search for similar issues, naturally, but did not find anything. I will have a more thorough search and let you know whether I find anything.