pandas reading dates from csv in yy-mm-dd format

问题

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.

回答1:

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

来源：https://stackoverflow.com/questions/32131742/pandas-reading-dates-from-csv-in-yy-mm-dd-format