Python beginner here. I have values in a Pandas Dataframe that I would like to change to a new value. Also, I then want to apply an ascending value at the end of the new text. My zone column below needs to be changed to still group by zone.
This is an example of how my Dataframe currently looks:
| value | section | zone |
|---|---|---|
| 1 | red | 25 |
| 2 | red | 25 |
| 3 | grey | 28 |
| 4 | blue | 35 |
| 5 | yellow | 35 |
| 6 | yellow | 35 |
| 7 | blue | 50 |
| 8 | green | 50 |
This is the changes in the ‘zone’ column I would like to make:
| value | section | zone |
|---|---|---|
| 1 | red | Zone1 |
| 2 | red | Zone1 |
| 3 | grey | Zone2 |
| 4 | blue | Zone3 |
| 5 | yellow | Zone3 |
| 6 | yellow | Zone3 |
| 7 | blue | Zone4 |
| 8 | green | Zone4 |
I’m not quite sure how to handle this problem. I’m assuming I need to use some sort of dataframe.replace(). I am not too skilled with python yet, so I hope this question makes sense.
>Solution :
Try:
df['zone'] = 'Zone' + (df.groupby('zone').ngroup() + 1).astype(str)
print(df)
Prints:
value section zone
0 1 red Zone1
1 2 red Zone1
2 3 grey Zone2
3 4 blue Zone3
4 5 yellow Zone3
5 6 yellow Zone3
6 7 blue Zone4
7 8 green Zone4