Code Sample

import pandas as pd

df = pd.DataFrame({
    'a': [1, 1, 2, 3],
    'b': [None, 1, 2, 3],
    'c': [1,2,3,4],
})

grouped = df.groupby(('a', 'b'))
print('Number of groups:', len(grouped))
# Number of groups: 4

num_iterations = 0
for _ in grouped:
    num_iterations += 1

print('Number of groups iterated over:', num_iterations) 
# Number of groups iterated over: 3

Problem description

Presently, when a GroupBy object is iterated over, any group where one of the columns grouped by is None is skipped.

This is a problem because when iterating over groups, we expect to iterate over all groups.

It is also a problem because it is not sensible to say the length of an iterable is x when iterating over it only performs some y < x number of iterations.

Expected Output

I'd expect iterating over a GroupBy object to iterate over all groups, regardless of the value in the key columns.

Output of pd.show_versions()

INSTALLED VERSIONS ------------------ commit: None python: 3.5.2.final.0 python-bits: 64 OS: Linux OS-release: 2.6.32-504.12.2.el6.x86_64 machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 pandas: 0.18.1 nose: 1.3.7 pip: 9.0.1 setuptools: 23.0.0 Cython: 0.24 numpy: 1.11.1 scipy: 0.17.1 statsmodels: 0.6.1 xarray: None IPython: 5.1.0 sphinx: 1.4.1 patsy: 0.4.1 dateutil: 2.5.3 pytz: 2016.4 blosc: None bottleneck: 1.1.0 tables: 3.3.0 numexpr: 2.6.0 matplotlib: 1.5.1 openpyxl: 2.3.2 xlrd: 1.0.0 xlwt: 1.1.2 xlsxwriter: 0.9.2 lxml: 3.6.0 bs4: 4.4.1 html5lib: None httplib2: None apiclient: None sqlalchemy: 1.0.13 pymysql: None psycopg2: 2.6.2 (dt dec pq3 ext) jinja2: 2.8 boto: 2.40.0 pandas_datareader: None

Comment From: chris-b1

Thanks for the report, this is a duplicate of #3729, with a WIP fix at #12607 - please try it out and comment if you'd like.

Comment From: nsfinkelstein

@chris-b1 Thanks - apologies for the duplication, I didn't notice that post when I was looking through issues.