Reputation: 41377
i'm getting data from mysql and using panda DataFrame i'm separating the data to column
data = pd.DataFrame(data)
print(data.ix[:,3])
0 2006-04-01
1 2006-08-01
2 2006-12-01
3 2006-02-01
4 2006-01-01
5 2006-07-01
6 2006-06-01
7 2006-03-01
8 2006-05-01
9 2006-11-01
10 2006-10-01
11 2006-09-01
12 2007-04-01
13 2007-08-01
14 2007-12-01
15 2007-02-01
16 2007-01-01
17 2007-07-01
18 2007-06-01
19 2007-03-01
20 2007-05-01
21 2007-11-01
22 2007-10-01
23 2007-09-01
24 2009-04-01
25 2009-08-01
when i put this data into linear regression prediction it gives dtype is different. how can i convert this date field to int and put it in the linear prediction
Upvotes: 1
Views: 1854
Reputation: 294198
you can convert the dates into ordinals by:
data.loc[:, 3].apply(lambda x: x.toordinal())
assuming this column is of type dtype('<M8[ns]')
It would look like:
2006-04-01 732402
2006-08-01 732524
2006-12-01 732646
2006-02-01 732343
2006-01-01 732312
2006-07-01 732493
2006-06-01 732463
2006-03-01 732371
2006-05-01 732432
2006-11-01 732616
2006-10-01 732585
2006-09-01 732555
2007-04-01 732767
2007-08-01 732889
2007-12-01 733011
2007-02-01 732708
2007-01-01 732677
2007-07-01 732858
2007-06-01 732828
2007-03-01 732736
2007-05-01 732797
2007-11-01 732981
2007-10-01 732950
2007-09-01 732920
2009-04-01 733498
2009-08-01 733620
Name: 1, dtype: int64
Upvotes: 1