pivot_table produces inconsistent columns if applied to empty table

Code Sample, a copy-pastable example if possible

# Part 1
df1 = pd.DataFrame([], columns=['a', 'b', 'value'])
pivot1 = df1.pivot_table(index='a', columns='b', values='value', 
                         aggfunc='count')
print(pivot1.columns)

#Output: 
MultiIndex(levels=[['value'], []],
           labels=[[], []],
           names=[None, 'b'])

# Part 2
df2 = pd.DataFrame([[1, 2, 3]], columns=['a', 'b', 'value'])
pivot2 = df2.pivot_table(index='a', columns='b', values='value', 
                         aggfunc='count')
print(pivot2.columns)

#Output:
Int64Index([2], dtype='int64', name='b')

Problem description

In the first example, I don’t expect to see any multiindex in .columns, as exactly one value for columns is provided. As we don’t have any data, and it is not possible to figure out the dtype of this index, one can probably assume it’s something like Index([], name='b').

Output of pd.show_versions()

INSTALLED VERSIONS ------------------ commit: None python: 3.7.0.final.0 python-bits: 64 OS: Darwin OS-release: 17.6.0 machine: x86_64 processor: i386 byteorder: little LC_ALL: en_US.UTF-8 LANG: en_US.UTF-8 LOCALE: en_US.UTF-8

pandas: 0.23.3 pytest: None pip: 10.0.1 setuptools: 39.2.0 Cython: None numpy: 1.14.5 scipy: 1.1.0 pyarrow: None xarray: None IPython: 6.4.0 sphinx: None patsy: 0.5.0 dateutil: 2.7.3 pytz: 2018.5 blosc: None bottleneck: None tables: None numexpr: None feather: None matplotlib: 2.2.2 openpyxl: None xlrd: None xlwt: None xlsxwriter: None lxml: None bs4: None html5lib: 1.0.1 sqlalchemy: None pymysql: None psycopg2: None jinja2: 2.10 s3fs: None fastparquet: None pandas_gbq: None pandas_datareader: None

[mroeschke]

Probably pandas/tests/reshape/test_pivot.py

[mroeschke]

Go for it @FaazAbidi