Create multiple columns by splitting value from other column with one assignment

There is DataFrame as:

timestamp                filename
2023-12-20 10:09:52.011  2023/12/20/1703056183.log

How to create new columns "year","month","day" in one assignment by splitting of "filename" column?

Wished result is :

timestamp                year month day  filename
2023-12-20 10:09:52.011  2023 12    20   2023/12/20/1703056183.log

>Solution :

Use Series.str.split with n parameter for split first 3 /, for expected order add DataFrame.pop:

Notice: Filename column is changed

df[['year','month','day','filename']] = df.pop('filename').str.split('/', n=3, expand=True)
print (df)
                 timestamp  year month day        filename
0  2023-12-20 10:09:52.011  2023    12  20  1703056183.log

For your ouput with filename column in your order use:

df[['year','month','day','_']] = df['filename'].str.split('/', n=3, expand=True)

df = df[df.columns.drop(['filename','_']).union(['filename'], sort=False)]
print (df)
                 timestamp  year month day                   filename
0  2023-12-20 10:09:52.011  2023    12  20  2023/12/20/1703056183.log