使用 loc pandas dataframe 追加列

Question

I am working with a dataframe that I have created with the below code:

df = pd.DataFrame({'player': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'], 
               'playerlookup': ['B', 'C', 'D', 'E', 'F', 'G', 'H', 'I'], 
               'score': ['10', '9', '8', '7', '6', '5', '4', '3']})

I want to add a new column called "scorelookup" to this dataframe that for each row, takes the value in the 'playerlookup' column, searches for it in the 'player' column and then returns the score in a new column. For example, the value in the "scorelookup" column in the first row of the dataframe would be '9' because that was the score for player 'B'. In instances where the value in the 'playerlookup' column isn't contained within the 'player' column (for example the last row of the table which has a value of 'I' in the 'playerlookup' column), the value in that column would be blank.

I have tried using code like:

df['playerlookup'].apply(lambda n: df.loc[df['player'] == n, 'score'])

but have been unsuccessful.

Any help massively appreciated!

Answer 1

I hope this is the result you are looking for:

import pandas as pd
df = pd.DataFrame({'player': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'], 
               'playerlookup': ['B', 'C', 'D', 'E', 'F', 'G', 'H', 'I'], 
               'score': ['10', '9', '8', '7', '6', '5', '4', '3']})

d1 = df[["playerlookup"]].copy()
d2 = df[["player","score"]].copy()
d1.rename({'playerlookup':'player'}, axis='columns',inplace=True)

df["scorelookup"] = d1.merge(d2, on='player', how='left')["score"]

The output

  player  playerlookup  score   scorelookup
0   A          B          10        9
1   B          C           9        8
2   C          D           8        7
3   D          E           7        6
4   E          F           6        5
5   F          G           5        4
6   G          H           4        3
7   H          I           3       NaN