从单独的 X 和 Y 列在 Pandas 中创建欧几里得距离列

Question

I have a pandas DataFrame of NBA basketball shooting statistics like the following. Each row refers to an individual shot taken during a game. X and Y refer to the respective horizontal and vertical distances from the net during each shot.

 | SHOOTER   | X      | Y        | SCORE      |
 | --------  | ------ | -------- | ---------- |
 | PlayerA   | -3.8   | 5.7      | MADE       |
 | PlayerB   | 0.7    | 5.9      | MADE       |
 | PlayerC   | -1.5   | 4.1      | MISSED     |
 | PlayerA   | 4.2    | 5.6      | MADE       |

I want to create a new column in the DataFrame showing each shot's Euclidian Distance from the xy coordinate (0, 0), to determine the distance from the net at each shot. How would I go about doing this?

Answer 1

You could create a function that uses the distance formula which is pretty staright forward. Or just use numpy and the np.linalg.norm() .

import pandas as pd
import numpy as np

columns = ['SHOOTER','X','Y','SCORE']
data =  [['PlayerA',-3.8,5.7,'MADE'],
['PlayerB',0.7,5.9,'MADE'],
['PlayerC',-1.5,4.1,'MISSED'],
['PlayerA',4.2,5.6,'MADE']]


df = pd.DataFrame(data=data, columns=columns)
df['dist'] = np.linalg.norm(df.loc[:, ['X','Y']].values, axis=1)

Output:

print(df)
   SHOOTER    X    Y   SCORE      dist
0  PlayerA -3.8  5.7    MADE  6.850547
1  PlayerB  0.7  5.9    MADE  5.941380
2  PlayerC -1.5  4.1  MISSED  4.365776
3  PlayerA  4.2  5.6    MADE  7.000000