Reputation: 443
Good evening,
is it possible to simply replace all empty cells - empty string, not nan - in a specific column with a given string or integer?
Let's say...
name | age |
---|---|
john doe | 27 |
jane doe | 29 |
marianne mustermann | |
max mustermann | 23 |
jean dupont |
to...
name | age |
---|---|
john doe | 27 |
jane doe | 29 |
marianne mustermann | 0 |
max mustermann | 23 |
jean dupont | 0 |
Thank you for all your help and have great day!
Upvotes: 1
Views: 1768
Reputation: 1734
I've added a NaN to demonstrate this works:
df
name age
0 john doe 27.0
1 jane doe 29.0
2 marianne mustermann
3 max mustermann 23.0
4 jean dupont
5 final NaN
df['age'] = df['age'].replace('',0)
df
name age
0 john doe 27.0
1 jane doe 29.0
2 marianne mustermann 0.0
3 max mustermann 23.0
4 jean dupont 0.0
5 final NaN
df.dropna()
name age
0 john doe 27.0
1 jane doe 29.0
2 marianne mustermann 0.0
3 max mustermann 23.0
4 jean dupont 0.0
Upvotes: 1