I have a csv files with dates in the format displayed as dd-mmm-yy and i want to read in the format yyyy-mm-dd. parse dates option works but it not converting dates correct before 2000 Example: actual date is 01-Aug-1968. It is displayed as 01-Aug-68. Pandas date parase and correction=true reads the date as 01-Aug-2068.
Is there any option to read the date in pandas in the correct format for the dates before 2000.
from dateutil.relativedelta import relativedelta
import datetime
let's assume you have a csv like this:
mydates
18-Aug-68
13-Jul-45
12-Sep-00
20-Jun-10
15-Jul-60
Define your date format
d = lambda x: pd.datetime.strptime(x, '%d-%b-%y')
Put a constraint on them
dateparse = lambda x: d(x) if d(x) < datetime.datetime.now() else d(x) - relativedelta(years=100)
read your csv:
df = pd.read_csv("myfile.csv", parse_dates=['mydates'], date_parser=dateparse)
here is your result:
print df
mydates
0 1968-08-18
1 1945-07-13
2 2000-09-12
3 2010-06-20
4 1960-07-15
Voilà