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to_timedelta('1', unit='h') does not work. #16791
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IMO, we should raise an error in such a case (combination of specifying a unit and parsing a string). I recall we had a similar discussion for If you have such a string, you should indeed first parse it to a numeric value (you can use |
I wouldn't have a problem raising, although it's worth noting that in In [22]: pd.to_datetime(1, unit='D')
Out[22]: Timestamp('1970-01-02 00:00:00')
In [23]: pd.to_datetime('1', unit='D')
Out[23]: Timestamp('1970-01-02 00:00:00') |
Hmm, OK, didn't check that :-) As long as we raise on invalid ones, I am OK with that as well.
(similar case with |
we need to raise if ANY unit is passed if its a string. The string contains or implies the unit. A string is parsed against the timedelta spec e.g. |
Closing this as a duplicate of #12136 |
Code Sample, a copy-pastable example if possible
Problem description
I would expect all the following to return Timedelta('0 days 01:00:00'). pd.to_timedelta(1, unit='h') does not. I must first cast the string '1' to a int or float then to a timedelta.
In [6]: pd.to_timedelta(1.0, unit='h')
Out[6]: Timedelta('0 days 01:00:00')
In [7]: pd.to_timedelta(1, unit='h')
Out[7]: Timedelta('0 days 01:00:00')
In [8]: pd.to_timedelta('1', unit='h')
Out[8]: Timedelta('0 days 00:00:00.000000')
In [9]: pd.to_timedelta('1 H')
Out[9]: Timedelta('0 days 01:00:00')
Expected Output
Output of
pd.show_versions()
INSTALLED VERSIONS
commit: None
python: 3.6.1.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 78 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: None.None
pandas: 0.20.2
pytest: 3.1.2
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.25.2
numpy: 1.12.1
scipy: 0.19.0
xarray: None
IPython: 6.0.0
sphinx: None
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2016.10
blosc: None
bottleneck: None
tables: 3.2.2
numexpr: 2.6.2
feather: None
matplotlib: 2.0.0
openpyxl: None
xlrd: 1.0.0
xlwt: None
xlsxwriter: None
lxml: None
bs4: 4.5.3
html5lib: 0.999999999
sqlalchemy: 1.1.5
pymysql: None
psycopg2: None
jinja2: 2.9.4
s3fs: None
pandas_gbq: None
pandas_datareader: None
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