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I have checked that this issue has not already been reported.
I have confirmed this bug exists on the latest version of pandas.
I have confirmed this bug exists on the main branch of pandas.
In [2]: pd.Series([3600], dtype="timedelta64[s]") Out[2]: 0 0 days dtype: timedelta64[s] In [3]: pd.Series([3600], dtype="timedelta64[s]")._values._ndarray Out[3]: array([0], dtype='timedelta64[s]') In [4]: pd.Series([3600], dtype="timedelta64[ns]")._values._ndarray Out[4]: array([3600], dtype='timedelta64[ns]')
I would expect Out[3] to return array([3600], dtype='timedelta64[s]')
Out[3]
array([3600], dtype='timedelta64[s]')
Replace this line with the output of pd.show_versions()
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Pandas version checks
I have checked that this issue has not already been reported.
I have confirmed this bug exists on the latest version of pandas.
I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
Issue Description
I would expect
Out[3]
to returnarray([3600], dtype='timedelta64[s]')
Expected Behavior
array([3600], dtype='timedelta64[s]')
Installed Versions
Replace this line with the output of pd.show_versions()
The text was updated successfully, but these errors were encountered: