Categorical-To-Neumerical
Sat 17 May 2025
import numpy as np
import pandas as pd
data = {
'sam' : ['archery', 'badminton', 'athletics', 'cycling_road', 'canoe_sprint', 'boxing'],
'medal' : ['gold', 'silver', 'bronze', 'gold', 'gold', 'silver']
}
df = pd.DataFrame(data)
df
| sam | medal | |
|---|---|---|
| 0 | archery | gold |
| 1 | badminton | silver |
| 2 | athletics | bronze |
| 3 | cycling_road | gold |
| 4 | canoe_sprint | gold |
| 5 | boxing | silver |
def get_medal_points(medal):
if(medal == 'gold'):
return 10
if(medal == 'silver'):
return 5
if(medal == 'bronze'):
return 1
return 0
df['medal_points'] = df['medal'].apply(get_medal_points)
df
| sam | medal | medal_points | |
|---|---|---|---|
| 0 | archery | gold | 10 |
| 1 | badminton | silver | 5 |
| 2 | athletics | bronze | 1 |
| 3 | cycling_road | gold | 10 |
| 4 | canoe_sprint | gold | 10 |
| 5 | boxing | silver | 5 |
Score: 5
Category: pandas