df1 =
| name | age | branch | subject | date of joining | |
|---|---|---|---|---|---|
| 1 | Steve | 27 | Mechanical | Autocad | 01-08-2021 |
| 2 | Adam | 32 | Electrical | control sys | 14-08-2021 |
| 3 | Raj | 24 | Electrical | circuit | 20-08-2021 |
| 4 | Tim | 25 | Computers | clouding | 21-08-2021 |
df2= [['name','branch']]
print(df2)
| name | branch | |
|---|---|---|
| 1 | Steve | Mechanical |
| 2 | Adam | Electrical |
| 3 | Raj | Electrical |
| 4 | Tim | Computers |
Now I have two data frames,
I need only name and branch columns and remove the remaining columns, all these operations should apply to the original df1. I don't want separately df2
CodePudding user response：
Simply, Overwrite the df1 only
df1= df1[['name','branch']] or df2= df1[['name','branch']] del df1
To delete df1 or df2. del df1 or del df2
Based on requirement
CodePudding user response：
You can simply set df1 to df2 or you can drop the columns from df1.
Method 1: drop in place
columns_to_drop = [x for x in df1.columns if x not in ['name','branch']]
df1.drop(columns=columns_to_drop, inplace=True)
Method 2:
df1 = df1[['name','branch']]