html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/1143#issuecomment-417337306,https://api.github.com/repos/pydata/xarray/issues/1143,417337306,MDEyOklzc3VlQ29tbWVudDQxNzMzNzMwNg==,12130884,2018-08-30T14:21:55Z,2018-08-30T14:21:55Z,NONE,"Pardon me for extending this discussion.
I encountered the same problem when calculating timedelta in a dataframe. It even ended with an error when I tried to call the days attribute. I am using Numpy 1.6.1
AttributeError: 'Series' object has no attribute 'days'
Problem
df_trans['DELTA'] = df_trans['DATE2'] - df_trans['DATE1']
print df_trans['DELTA'].dtype
>>timedelta64[ns]
print df_trans['DELTA']
>> 0 8 days, 00:00:00
>> 1 15 days, 00:00:00
>> 2 5 days, 00:00:00
df_trans['DELTA'] = df_trans['DELTA'].astype('timedelta64[D]')
print df_trans['DELTA'].dtype
>> Name: DELTA, dtype: timedelta64[D]
print df_trans['DELTA']
>> 0 8 days, 00:00:00
>> 1 15 days, 00:00:00
>> 2 5 days, 00:00:00
>>Nothing changed at all
print df_trans['DELTA'].days
>> AttributeError: 'Series' object has no attribute 'days'
I get rid of the problem by putting it in to a list for the conversion.
Ss_timedelta = df_trans['DATE2'] - df_trans['DATE1']
ls_timedelta = Ss_timedelta.values.astype('timedelta64[D]').tolist()
for i in range(0, len(ls_timedelta)):
ls_timedelta[i] = ls_timedelta[i].days / 1000
df_trans['HOLDDAYS'] = pd.Series(ls_timedelta)
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