Pandas Tutorial : How to split columns of dataframe   

Columns can be split with Python and Pandas by:

• creating new dataframe from the results - you don't need to provide column names and types
• adding the results as columns to the old dataframe - you will need to provide headers for your columns

Both methods use pandas.Series.str.split:

Series.str.split(pat=None, n=-1, expand=False)

Split strings around given separator/delimiter.
Split each string in the caller’s values by given pattern, propagating NaN values. Equivalent to str.split().

import pandas as pd

df = pd.DataFrame({'Company': ['Samsung', 'Samsung', 'Samsung', 'Samsung', 'Samsung',
                               'LG', 'LG', 'LG', 'LG', 'LG', 'Sony', 'Sony', 'Sony',
                               'Sony', 'Sony'],
                   'Date': ['10/9/2018', '10/9/2018', '10/9/2018', '10/10/2018',
                            '10/10/2018', '10/10/2018', '10/9/2018', '10/9/2018',
                            '10/9/2018', '10/10/2018', '10/10/2018', '10/10/2018',
                            '10/10/2018', '10/10/2018', '10/10/2018'],
                   'Country': ['India', 'India', 'USA', 'France', 'India', 'India',
                               'Germany', 'USA', 'Brazil', 'Brazil', 'India', 'Germany',
                               'India', 'India', 'Brazil'],
                   'Sells': [15, 81, 29, 33, 21, 42, 67, 35, 2, 34, 21, 50, 10, 26, 53]})

# creating new dataframe single column
new_df_no_expand = df['Date'].str.split('/')

# expand to new columns
new_df = df['Date'].str.split('/',expand=True)

# limit the split to first one
new_df_limit = df['Date'].str.split('/', n=1,expand=True)

# adding new columns to the old dataframe
df[['day', 'mm', 'year']] = df['Date'].str.split('/',expand=True)

a = 1

Result for new dataframe:

if you want to add the result values as columns to the old dataframe:

In case of a missing data you will get None - example:

10/10/2018
10/10

will result into:

    0   1     2
0   10   10  2018
1   10   10  None

Reference

• pandas.Series.str.split