Docs: broken groupby.GroupBy.apply example #19337
Description
Sample
Copied directly from pandas-docs-travis:
import pandas as pd df = pd.DataFrame({'A': 'a a b'.split(), 'B': [1,2,3], 'C': [4,6, 5]}) g = df.groupby('A') # ValueError g.apply(lambda x: x / x.sum()) # ValueError g.apply(lambda x: x.max() - x.min()) # Works fine g.apply(lambda x: x.C.max() - x.B.min()) Problem description
The first two apply operations return ValueError: can only convert an array of size 1 to a Python scalar. The third apply operation works as expected.
Expected Output
As given by pandas-docs-travis:
>>> g.apply(lambda x: x / x.sum()) B C 0 0.333333 0.4 1 0.666667 0.6 2 1.000000 1.0>>> g.apply(lambda x: x.max() - x.min()) B C A a 1 2 b 0 0>>> g.apply(lambda x: x.C.max() - x.B.min()) A a 5 b 2 dtype: int64Output of pd.show_versions()
INSTALLED VERSIONS
commit: None
python: 2.7.13.final.0
python-bits: 64
OS: Darwin
OS-release: 16.7.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_AU.UTF-8
LOCALE: None.None
pandas: 0.22.0
pytest: 3.0.5
pip: 9.0.1
setuptools: 38.4.0
Cython: 0.25.2
numpy: 1.12.1
scipy: 1.0.0
pyarrow: None
xarray: None
IPython: 5.4.1
sphinx: 1.5.1
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2016.10
blosc: None
bottleneck: 1.2.1
tables: 3.3.0
numexpr: 2.6.4
feather: None
matplotlib: 2.1.1
openpyxl: 2.4.1
xlrd: 1.0.0
xlwt: 1.2.0
xlsxwriter: 0.9.6
lxml: 3.7.2
bs4: 4.5.3
html5lib: 0.9999999
sqlalchemy: 1.1.5
pymysql: None
psycopg2: None
jinja2: 2.9.4
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None