Transform with Count Agg against DateTime returns DateTime · Issue #19200 · pandas-dev/pandas (original) (raw)

Code Sample, a copy-pastable example if possible

df = pd.DataFrame({'a': pd.date_range('2018-01-01', periods=3), 'b': range(3)}) df.groupby('b')['a'].transform('count')

0 1970-01-01 00:00:00.000000001 1 1970-01-01 00:00:00.000000001 2 1970-01-01 00:00:00.000000001 Name: a, dtype: datetime64[ns]

Expected Output

The value 1.0 broadcasted with a float dtype, not a datetime64

Output of pd.show_versions()

INSTALLED VERSIONS

commit: 78c3ff9
python: 3.6.1.final.0
python-bits: 64
OS: Darwin
OS-release: 17.3.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.23.0.dev0+101.g78c3ff97a
pytest: None
pip: 9.0.1
setuptools: 27.2.0
Cython: None
numpy: 1.13.1
scipy: 0.19.1
pyarrow: None
xarray: None
IPython: 6.1.0
sphinx: 1.6.5
patsy: None
dateutil: 2.6.1
pytz: 2017.2
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.1.1
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: 4.6.0
html5lib: 0.999999999
sqlalchemy: 1.1.13
pymysql: None
psycopg2: 2.7.3.2 (dt dec pq3 ext lo64)
jinja2: 2.9.6
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None