i have to filter value column_A 1st and then Fill the nan value as team 1 for abc and team 2 for def
| Column_A | Column_B |
|---|---|
| abc | team 1 |
| def | team 5 |
| def | team 5 |
| def | NaN |
| abc | team 1 |
| abc | NaN |
CodePudding user response：
IIUC, try this using fillna:
df['Column_B'] = df['Column_B'].fillna(df['Column_A'].map({'abc':'team 1', 'def' : 'team 2'}))
df
Output:
Column_A Column_B
0 abc team 1
1 def team 5
2 def team 5
3 def team 2
4 abc team 1
5 abc team 1
CodePudding user response：
You can set index to your reference column and use a dictionary:
df['Column_B'] = df.set_index('Column_A')['Column_B']\
.fillna({'abc':'team 1', 'def' : 'team 2'}).values