python - Parse_dates in Pandas

Question

The following code can't parse my date column into dates from csv file.

data=pd.read_csv('c:/data.csv',parse_dates=True,keep_date_col = True) 

or

data=pd.read_csv('c:/data.csv',parse_dates=[0]) 

data is like following

date          value 
30MAR1990    140000 
30JUN1990    30000  
30SEP1990    120000  
30DEC1990    34555

What did I do wrong? Please help!

Thanks.

Answer 1

This is a non-standard format, so not caught by the default parser, you can pass your own:

In [11]: import datetime as dt

In [12]: dt.datetime.strptime('30MAR1990', '%d%b%Y')
Out[12]: datetime.datetime(1990, 3, 30, 0, 0)

In [13]: parser = lambda date: pd.datetime.strptime(date, '%d%b%Y')

In [14]: pd.read_csv(StringIO(s), parse_dates=[0], date_parser=parser)
Out[14]:
        date  value
0 1990-03-30  140000
1 1990-06-30   30000
2 1990-09-30  120000
3 1990-12-30   34555

Another option is to use to_datetime after you've read in the strings:

df['date'] = pd.to_datetime(df['date'], format='%d%b%Y')