Convert a column of integers in pandas dataframe to month with leading zeros

Question

I want to change the Month and Day column in the Python pandas dataframe from integer to strings with leading zeros.

What I want is here: the input is here as a pandas dataframe:

Year Month  Day
2018     1    1
2018     1   12
2018     1   18
2018     2    4
2018     2    1
2018     2    2
2018     2   12
2018     3   30

I want to make them like this:

Year Month  Day
2018    01   01
2018    01   12
2018    01   18
2018    02   04
2018    02   01
2018    02   02
2018    02   12
2018    03   30

My method is pretty dumb, and it is very slow.

def Import():
    df = pd.read_csv('Transaction_data.csv',index_col=0)
    n = len(df)
    for i in range(n):
        temp = df['Year'].loc[i]
        df['Year'].loc[i] = str(temp)

    for i in range(n):
        temp = df['Month'].loc[i]
        if temp<10:
            df['Month'].loc[i] = '0'+str(temp)
        else:
            df['Month'].loc[i] = str(temp)

    for i in range(n):
        temp = df['Day'].loc[i]
        if temp<10:
            df['Day'].loc[i] = '0'+str(temp)
        else:
            df['Day'].loc[i] = str(temp)
    return df

Also

pd.to_datetime(df['Month'],format='%d')

won't help since to_datetime only has month as integers [1,12]

Answer 1

I want to change the Month and Day column in the Python pandas dataframe from integer to strings with leading zeros.

Use series.str.zfill() :

df[['Month','Day']]=df[['Month','Day']].astype(str).apply(lambda x: x.str.zfill(2))
print(df)

---

   Year Month Day
0  2018    01  01
1  2018    01  12
2  2018    01  18
3  2018    02  04
4  2018    02  01
5  2018    02  02
6  2018    02  12
7  2018    03  30

Answer 2

You mentioned you wish to have a string value so you can use a simple lambda. On the Day example you should have:

df['Day'].apply(lambda x: "0"+str(x) if x<10 else x)