dictionary and none within dataframe-CodePudding

I have the following dataframe:

I would like to modify the column category by implementing the following method : if the dictionary = None return "NA" (str) else I would like to keep only the value of 'second' (for example EUR in the first line) as a value for the column. Also if the 'second' is None so return "NA".
I tried the following logic : df['category']= df['category'].apply(lambda x: x['second'] if x is not None) but it didn't work as there are some None.

CodePudding user response：

I think this will work:

import pandas as pd

df = pd.DataFrame(
    {'category': [{'first': 'ABC',
                   'second': 'EUR'},
                  {'first': 'ABC',
                   'second': None}]})
df['category'] = df['category'].str['second'].fillna('NA')

Output:

  category
0      EUR
1       NA

CodePudding user response：

You just have to add 'NA' if x is None else to your lambda expression to check for None first:

df['category'] = df['category'].apply(lambda x: 'NA' if x is None else #check for None
                     x['second'] if x['second'] is not None else 'NA') #check for second