CODEWITHSUNDEEP
pythonpandasdatetime
PV8
PV8

Reputation: 6260

Convert int64 column to time column

I have a pandas dataframe with a "time" column, which currently looks like:

ab['ZEIT'].unique()
array([     0, 165505, 203355, ...,  73139,  75211,  74244], dtype=int64)

How can i get german time format out of it with hh:mm:ss so basically that it looks like:

array([00:00:00, 16:55:05, 20:33:55, ..., 07:31:39, 07:52:11, 07:42:44], dtype=?)

Upvotes: 0

Views: 373

Answers (1)

Zero
Zero

Reputation: 76917

Use pd.to_datetime after converting values to string with padded 0s. Then call dt accessor for time 

In [12]: pd.to_datetime(df['ZEIT'].astype(str).str.zfill(6), format='%H%M%S').dt.time
Out[12]: 
0    00:00:00
1    16:55:05
2    20:33:55
3    07:31:39
4    07:52:11
5    07:42:44
Name: ZEIT, dtype: object

Details

In [13]: df
Out[13]: 
     ZEIT
0       0
1  165505
2  203355
3   73139
4   75211
5   74244

In [14]: df['ZEIT'].astype(str).str.zfill(6)
Out[14]: 
0    000000
1    165505
2    203355
3    073139
4    075211
5    074244
Name: ZEIT, dtype: object

In [15]: pd.to_datetime(df['ZEIT'].astype(str).str.zfill(6), format='%H%M%S')
Out[15]: 
0   1900-01-01 00:00:00
1   1900-01-01 16:55:05
2   1900-01-01 20:33:55
3   1900-01-01 07:31:39
4   1900-01-01 07:52:11
5   1900-01-01 07:42:44
Name: ZEIT, dtype: datetime64[ns]

Upvotes: 1

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