I got the following dataframe:
| Contact | Gender | Title |
|---|---|---|
| 1 | M | |
| 2 | F | Dear Ms |
| 3 | Female | Dear Ms |
| 4 | F. | Dear Ms |
| 5 | M | |
| 6 | M | |
| 7 | M. | Dear Mr |
How can I change contact 2,3,4 and 7 based on the Title column.
Ms is F and Mr is M
The other contacts who don't have a Title, must nothing happen to it. It must be the same.
So i want this:
| Contact | Gender | Title |
|---|---|---|
| 1 | M | |
| 2 | F | Dear Ms |
| 3 | F | Dear Ms |
| 4 | F | Dear Ms |
| 5 | M | |
| 6 | M | |
| 7 | M | Dear Mr |
Try the following:
df.loc[df.Title.str.contains('Mr'), 'Gender']='M'
df.loc[df.Title.str.contains('Ms'), 'Gender']='F'
Well In your sample dataframe Gender is correct according to Title:
If that's the case then you can simply do:
df['Gender']=df['Gender'].str[0]
IF that is not the case then use np.select():
#import numpy as np
conditions = [
df["Title"].str.contains("Ms",case=False).fillna(False),
df["Title"].str.contains("Mr",case=False).fillna(False)
]
choices = ["F", "M"]
df["Gender"] =pd.Series(np.select(conditions, choices)).replace('0',np.nan).fillna(df['Gender'])
