I want to subtract two data frames in python 2.x and format the result to be in hh:mm:ss. My problem is that I am assuming the delta column is a string and it's a number. I need help because I am struggling to make it work. I've searched and tried some solutions found on other posts but I am unable to solve it.
actual= ...select now()
This is the df
begin actual
0 2018-01-31 16:45:04.263 2018-01-31 16:48:06
1 2018-01-31 16:10:26.000 2018-01-31 16:50:06
Now:
df['actual'] = pd.to_datetime(df['actual'])
df['delta'] = df['actual'] - df['begin']
df['delta'] = df['delta'].apply(lambda x: str(x)[-8:])
The result it's this: 39:49 and 2.737000 . For the second one I want the same format as for the first. I've tried changing the function like this:
df['delta'] = df['delta'].apply(lambda x: pd.Timedelta(seconds=int(x.total_seconds())))
But it returns :
AttributeError: 'Timestamp' object has no attribute 'total_seconds'
Any ideas would be very appreciated.
I think you need:
print (df.dtypes)
begin datetime64[ns]
actual datetime64[ns]
dtype: object
df['delta'] = (df['actual'] - df['begin']).dt.total_seconds()
print (df)
begin actual delta
0 2018-01-31 16:45:04.263 2018-01-31 16:48:06 181.737
1 2018-01-31 16:10:26.000 2018-01-31 16:50:06 2380.000
If want format it is possible, but a bit crazy (not general solution, because days are removed):
df['delta'] = (df['actual'] - df['begin']).astype(str).str[7:15]
print (df)
begin actual delta
0 2018-01-31 16:45:04.263 2018-01-31 16:48:06 00:03:01
1 2018-01-31 16:10:26.000 2018-01-31 16:50:06 00:39:40
df['delta'] = (df['actual'] - df['begin']).astype(str)
print (df)
begin actual delta
0 2018-01-31 16:45:04.263 2018-01-31 16:48:06 0 days 00:03:01.737000000
1 2018-01-31 16:10:26.000 2018-01-31 16:50:06 0 days 00:39:40.000000000
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