Crosstab Not Working with Duplicate Column Labels

Code Sample, a copy-pastable example if possible

1. Example with 2 lambdas applied on same column

df = pd.DataFrame([[0, 1], [0, 1], [1, 0]], columns=[‘a’, ‘b’]) df a b 0 0 1 1 0 1 2 1 0

pd.crosstab(df[‘a’].apply(lambda x: x), df[‘a’].apply(lambda x: x+1)) a 1 2 a 1 2 0 2 0 1

2. Example by manually renaming a column

df = pd.DataFrame([[0, 1], [0, 1], [1, 0]], columns=[‘a’, ‘b’]) df a b 0 0 1 1 0 1 2 1 0

pd.crosstab(df[‘a’], df[‘b’]) b 0 1 a 0 0 2 1 1 0

s = df[‘b’] s.name = ‘a’ pd.crosstab(df[‘a’], s) a 0 1 a 0 1 0 1 0 2

In both cases, the output is not the one expected. The crosstab applies one Series to itself.

Problem description

I encountered the problem when using a crosstab on the same column with 2 different lambdas. The crosstab output a crosstab applying the second column to itself. It seems that crosstab is confused by the same name of the 2 series.

The problem is the same when the 2nd column is manually renamed with the name of the 1rst one, before applying the crosstab. See examples.

Expected Output

Output of pd.show_versions()

INSTALLED VERSIONS

commit: None python: 3.6.4.final.0 python-bits: 64 OS: Windows OS-release: 7 machine: AMD64 processor: Intel64 Family 6 Model 69 Stepping 1, GenuineIntel byteorder: little LC_ALL: None LANG: None LOCALE: None.None

pandas: 0.22.0 pytest: 3.3.2 pip: 10.0.0 setuptools: 38.4.0 Cython: 0.27.3 numpy: 1.14.0 scipy: 1.0.0 pyarrow: None xarray: None IPython: 6.2.1 sphinx: 1.6.6 patsy: 0.5.0 dateutil: 2.6.1 pytz: 2017.3 blosc: None bottleneck: 1.2.1 tables: 3.4.2 numexpr: 2.6.4 feather: None matplotlib: 2.1.2 openpyxl: 2.4.10 xlrd: 1.1.0 xlwt: 1.3.0 xlsxwriter: 1.0.2 lxml: 4.1.1 bs4: 4.6.0 html5lib: 1.0.1 sqlalchemy: 1.2.1 pymysql: None psycopg2: None jinja2: 2.10 s3fs: None fastparquet: None pandas_gbq: None pandas_datareader: None

[TomAugspurger]

To be clear, this has nothing to do with lambdas, right? In the following, Out[26] is the expected output, but with the name a substituted for b?

In [25]: pd.crosstab(pd.Series([0, 0, 1, 1], name='a'), pd.Series([0, 1, 0, 1], name='a'))
Out[25]:
a  0  1
a
0  2  0
1  0  2

In [26]: pd.crosstab(pd.Series([0, 0, 1, 1], name='a'), pd.Series([0, 1, 0, 1], name='b'))
Out[26]:
b  0  1
a
0  1  1
1  1  1

[cuchoi]

I made a PR that raises an error when trying to use duplicated column names. Does it make sense to you?