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+--- Thread: Problem with replacing strings (/thread-27018.html)
Problem with replacing strings - donnertrud - May-22-2020
Hi guys,
I got a data set with Dates looking like this :
Jan. 01
Feb. 01
Mar. 01
and so on. It seems Python can't transform this kind of date format using
df['Date'] = pd.to_datetime(df['Date'])In order to work I guess the format has to be:
Jan. 2001
Feb. 2001
Mar. 2001
What I have been trying, and I am 100% sure there is a fancier way, is to replace all "01" with "2001" and so on. The code looks like that :
for i in range(len(df["Date"])):
df["Date"][i] = df["Date"][i].replace("00","2000")
df["Date"][i] = df["Date"][i].replace("01","2001")
df["Date"][i] = df["Date"][i].replace("02","2002")
df["Date"][i] = df["Date"][i].replace("03","2003")The problem what that code is, that transformed strings, e.g. 2020, are getting replaced again, because they have the string "02" in them. As a result, I get dates like : Jan 202000 
Is there a way to fix my approach, or a different approach that solves my problem?
RE: Problem with replacing strings - deanhystad - May-22-2020
def y2k(datestr):
year=datestr.split()[-1]
if len(year) < 4:
return datestr[:-2]+'20'+datestr[-2:]
return datestr
print(y2k('Jan. 01'))
print(y2k('Jan. 1999'))
RE: Problem with replacing strings - perfringo - May-22-2020
Maybe something along these lines:
>>> import pandas as pd
>>> df = pd.DataFrame({'date': ['Jan. 01', 'Feb. 01', 'Mar. 01']})
>>> df
date
0 Jan. 01
1 Feb. 01
2 Mar. 01
>>> df['date'] = pd.to_datetime(df['date'], format='%b. %y')
>>> df
date
0 2001-01-01
1 2001-02-01
2 2001-03-01
RE: Problem with replacing strings - donnertrud - May-22-2020
Both methods worked! Thank you so much