CODEWITHSUNDEEP
pythonpandas
warrenfitzhenry
warrenfitzhenry

Reputation: 2299

Pandas convert column to datetime

I have this df:

    A
0   2017-04-17 00:00:00
1   2017-04-18 00:00:00
2   2017-04-19 00:00:00
3   2017-04-20 00:00:00
4   2017-04-21 00:00:00

I am trying to get rid of the H, M, S, so that I am left with:

     A
0   2017-04-17
1   2017-04-18 
2   2017-04-19 
3   2017-04-20 
4   2017-04-21

the dtype of column A is object. I have tried:

df['A'] = df['A']datetime.strftime('%Y-%m-%d')

with:

import datetime as datetime

I get:

AttributeError: 'Series' object has no attribute 'strftime'

Upvotes: 4

Views: 8867

Answers (1)

jezrael
jezrael

Reputation: 862641

I think you need dt.strftime - output are strings:

#if necessary
#df['A'] = pd.to_datetime(df['A'])

print (type(df.loc[0, 'A']))
<class 'pandas.tslib.Timestamp'>

df['A'] = df['A'].dt.strftime('%Y-%m-%d')
print (df)
            A
0  2017-04-17
1  2017-04-18
2  2017-04-19
3  2017-04-20
4  2017-04-21

print (type(df.loc[0, 'A']))
<class 'str'>

and for dates use date:

df['A'] = df['A'].dt.date
print (df)

            A
0  2017-04-17
1  2017-04-18
2  2017-04-19
3  2017-04-20
4  2017-04-21

print (type(df.loc[0, 'A']))
<class 'datetime.date'>

Upvotes: 5

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