Description
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()
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