import pandas as pd
raw_data = {'first_name': ['Jason', 'Molly', 'Tina', 'Jake', 'Amy'],
'last_name': ['Miller', 'Jacobson', 'Ali', 'Milner', 'Cooze'],
'age': [42, 52, 36, 24, 73],
'city': ['San Francisco', 'Baltimore', 'Miami', 'Douglas', 'Boston']}
df = pd.DataFrame(raw_data, columns = ['first_name', 'last_name', 'age', 'city'])
df
first_name | last_name | age | city | |
---|---|---|---|---|
0 | Jason | Miller | 42 | San Francisco |
1 | Molly | Jacobson | 52 | Baltimore |
2 | Tina | Ali | 36 | Miami |
3 | Jake | Milner | 24 | Douglas |
4 | Amy | Cooze | 73 | Boston |
5 rows × 4 columns
city_to_state = { 'San Francisco' : 'California',
'Baltimore' : 'Maryland',
'Miami' : 'Florida',
'Douglas' : 'Arizona',
'Boston' : 'Massachusetts'}
df['state'] = df['city'].map(city_to_state)
df
first_name | last_name | age | city | state | |
---|---|---|---|---|---|
0 | Jason | Miller | 42 | San Francisco | California |
1 | Molly | Jacobson | 52 | Baltimore | Maryland |
2 | Tina | Ali | 36 | Miami | Florida |
3 | Jake | Milner | 24 | Douglas | Arizona |
4 | Amy | Cooze | 73 | Boston | Massachusetts |
5 rows × 5 columns