Pandas: Split a string and then create a new column?

I think this will work . If...else logic here is for your additional requested, when do not have '_' keep the original

   df['Col2']= df['Col1'].apply(lambda x: x.split('_')[1] if x.find('_')!=-1 else x )

Edit to handle strings without '_':

df['Col2'] = (np.where(df['Col1'].str.contains('_'),
                  df['Col1'].str.split('_').str[1],
                  df['Col1']))

OR as COLDSPEED suggests in comments:

df['Col1'].str.split('_').str[-1]

You can use the .str access with indexing:

df['Col2'] = df['Col1'].str.split('_').str[1]

Example:

df = pd.DataFrame({'Col1':['Name_John','Name_Jay','Name_Sherry']})
df['Col2'] = df['Col1'].str.split('_').str[1]

Output:

          Col1    Col2
0    Name_John    John
1     Name_Jay     Jay
2  Name_Sherry  Sherry

You can simply use str.split() method with expand=True argument.

For example:

ncaa[['Win', 'Lose']] = ncaa['Record'].str.split('-', expand=True)

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