TypeError in to_datetime when passing Int64 column · Issue #30050 · pandas-dev/pandas (original) (raw)

Code Sample

df = pd.DataFrame({'a':[1,2,3]}) df.a = df.a.astype("Int64") pd.to_datetime(df.a, unit='ms')

Problem description

When a nullable int type is used, to_datetime gives the error:

TypeError: Argument 'values' has incorrect type (expected numpy.ndarray, got IntegerArray)

The error is unexpected and hard to track down (reliant on pandas internal storage formats).

Expected Output

Converted date times or NaT when input is NaN

Output of pd.show_versions()

INSTALLED VERSIONS ------------------ commit : None python : 3.7.3.final.0 python-bits : 64 OS : Linux OS-release : 5.0.0-36-generic machine : x86_64 processor : x86_64 byteorder : little LC_ALL : None LANG : en_US.UTF-8 LOCALE : en_US.UTF-8

pandas : 0.25.3
numpy : 1.17.0
pytz : 2018.9
dateutil : 2.8.0
pip : 19.0.3
setuptools : 41.0.1
Cython : 0.29.6
pytest : 4.3.1
hypothesis : None
sphinx : 1.8.5
blosc : None
feather : None
xlsxwriter : 1.1.5
lxml.etree : 4.3.2
html5lib : 1.0.1
pymysql : None
psycopg2 : None
jinja2 : 2.10
IPython : 7.4.0
pandas_datareader: None
bs4 : 4.7.1
bottleneck : 1.2.1
fastparquet : None
gcsfs : None
lxml.etree : 4.3.2
matplotlib : 3.0.3
numexpr : 2.6.9
odfpy : None
openpyxl : 2.6.1
pandas_gbq : None
pyarrow : None
pytables : None
s3fs : None
scipy : 1.2.1
sqlalchemy : 1.3.1
tables : 3.5.1
xarray : None
xlrd : 1.2.0
xlwt : 1.3.0
xlsxwriter : 1.1.5