Define date format in Python / Pandas

Question

I have two .csv files joined in Python with the Pandas module. One column is date with the format "dd.mm.yyyy".

Now I would like to extract only the month (as 2 digit integer with leading zero) from it for further use.

I have so far accomplished the job but I had to cheat. Python thinks the string that I am getting is the DAY. I don't like half-baked things, so I wanted to ask the community how I can tell Python specifically which part of the date is the month so it can be returned to me?

Here is what I have so far:

import pandas

def saison(input):
    if input == "04" or input == "05" or input == "06" or input == "07" or input == "08" or input == "09":
        return "Sommer"
    else:
        return "Winter"

df_1 = pandas.read_csv("a.csv", sep=';', names=["DWD_ID", "Datum"], header=0)
df_2 = pandas.read_csv("b.csv", sep=';', names=[VEG", "DWD_ID"], header=0)
df_joined = pandas.merge(df_1, df_2, on="DWD_ID")
df_joined["Datum"] = pandas.to_datetime(df_joined["Datum"])

df_joined["Saison"] = saison(df_joined["Datum"].apply(lambda x: x.strftime('%d')))

If I use

x.strftime('%m')

instead it returns me the day.

Nickil Maveli · Accepted Answer · 2016-09-26 10:53:54Z

1

You could supply the format you want to keep in the arg of to_datetime:

pd.to_datetime(df['date_col'], format="%d.%m.%Y").dt.month.astype(str).str.zfill(2)

answered Sep 26, 2016 at 10:53

Nickil Maveli

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4 Comments

Stop harming Monica Over a year ago

dayfirst=True would also work but format will be faster and will fail when something goes wrong instead of silently making choices that you might disagree with.

Kai Over a year ago

That did the job! Thanks!

Nickil Maveli Over a year ago

@Khaled, I see that you haven't accepted answers for any of your prior questions including this one ;-) You should certainly accept them(by clicking on the check mark) if it has solved your problem. This indicates to anyone coming over this page in future that this solution of mine worked to resolve the problem.

Kai Over a year ago

Oops, sorry, I haven't been aware of this feature yet!

jezrael · Accepted Answer · 2016-09-26 11:07:30Z

First it seems you have swap month and day in datetime, so you need add argument format='%Y-%d-%m' to to_datetime (Python's strftime directives):

df = pd.DataFrame({'Date': ['2016-24-02']})  
print (df)
         Date
0  2016-24-02

print (pd.to_datetime(df.Date, format='%Y-%d-%m'))
0   2016-02-24
Name: Date, dtype: datetime64[ns]

After converting you can use:

dt.strftime:

print (df.Date.dt.strftime('%m'))

Another solution with extract month, then convert to string and last add zero fill by zfill:

print (df.Date.dt.month.astype(str).str.zfill(2))

Sample:

start = pd.to_datetime('2015-02-24')
rng = pd.date_range(start, periods=10, freq='m')

df = pd.DataFrame({'Date': rng})  
print (df)
        Date
0 2015-02-28
1 2015-03-31
2 2015-04-30
3 2015-05-31
4 2015-06-30
5 2015-07-31
6 2015-08-31
7 2015-09-30
8 2015-10-31
9 2015-11-30


print (df.Date.dt.strftime('%m'))
0    02
1    03
2    04
3    05
4    06
5    07
6    08
7    09
8    10
9    11
Name: Date, dtype: object

print (df.Date.dt.month.astype(str).str.zfill(2))
0    02
1    03
2    04
3    05
4    06
5    07
6    08
7    09
8    10
9    11
Name: Date, dtype: object

Last you can use numpy.where with condition with isin:

saison = ["04","05","06","07","08","09"]
df['Saison'] = np.where(df.Date.dt.strftime('%m').isin(saison), 'Sommer','Winter')
print (df)
        Date  Saison
0 2015-02-28  Winter
1 2015-03-31  Winter
2 2015-04-30  Sommer
3 2015-05-31  Sommer
4 2015-06-30  Sommer
5 2015-07-31  Sommer
6 2015-08-31  Sommer
7 2015-09-30  Sommer
8 2015-10-31  Winter
9 2015-11-30  Winter

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