I am using the below code to convert str(' 1495596971') to '%Y-%m-%d %H:%M:%S' but unable to do it for the whole column. Could you please help me with that?
ho['tweet'] = ho['tweet'].astype(str)
c=ho['tweet']
stddate=c.split('.')[0].split('0')[1]
t=print(
datetime.datetime.fromtimestamp(
int(stddate)
).strftime('%Y-%m-%d %H:%M:%S')
)
It is showing this error:-'Series' object has no attribute 'split'
Input:-
tweet
0 1495596971.6034188::automotive auto ebc greens...
1 1495596972.330948::new free stock photo of cit...
2 1495596972.775966::ebay: 1974 volkswagen beetl...
3 1495596975.6460807::cars fly off a hidden spee...
4 1495596978.12868::rt @jiikae: guys i think mar...
I only want '1495596971','1495596972',etc this data from the column and want to convert it to standard date and time format.
Pandas Series has no method split, what you can do is get every item, then split with '.', then fetch str ('1495596971'), convert and format it :
import pandas as pd
import datetime
c = pd.Series(['1495596971.6034188::automotive auto ebc greens','1495596972.330948::new free stock photo of cit','1495596972.775966::ebay: 1974 volkswagen beetl'])
stddate_list = [c[i].split('.')[0] for i in range(len(c))]
print(stddate_list)
t = [datetime.datetime.fromtimestamp(int(stddate)).strftime('%Y-%m-%d %H:%M:%S') for stddate in stddate_list]
print(t)
Output for stddate_list and t:
['1495596971', '1495596972', '1495596972']
['2017-05-24 11:36:11', '2017-05-24 11:36:12', '2017-05-24 11:36:12']