python：pandas：按条件将其他 dataframe 的值添加到新列中

Question

我有两个包含以下数据的数据框：

fixtures = pd.DataFrame(
    {'HomeTeam': ["A", "B", "C", "D"], 'AwayTeam': ["E", "F", "G", "H"]})

ratings = pd.DataFrame({'team': ["A", "B", "C", "D", "E", "F", "G", "H"], "rating": [
                       "1,5", "0,2", "0,5", "2", "3", "4,8", "0,9", "-0,4"]})

现在我想要 map 从ratings["rating"]到各自团队名称的值，但我无法让它工作。 是否可以在HomeTeam和AwayTeam列的右侧显示评级的新列？

预计 output：

固定装置：

homeTeam  homeTeamRating  awayTeam  AwayTeamRating  
Team A    1,5             Team E    3

Answer 1

您可以使用：

to_replace=dict(zip(ratings.team,ratings.rating)) #create a dict. Key is team name value is rating.
#{'A': '1,5', 'B': '0,2', 'C': '0,5', 'D': '2', 'E': '3', 'F': '4,8', 'G': '0,9', 'H': '-0,4'}

fixtures['homeTeamRating']=fixtures['HomeTeam'].map(to_replace) #use map and  replace team column as a new column.
fixtures['AwayTeamRating']=fixtures['AwayTeam'].map(to_replace)

fixtures=fixtures[['HomeTeam','homeTeamRating','AwayTeam','AwayTeamRating']]

'''
  HomeTeam homeTeamRating AwayTeam AwayTeamRating
0        A            1,5        E              3
1        B            0,2        F            4,8
2        C            0,5        G            0,9
3        D              2        H           -0,4
'''

Answer 2

如果您需要在现有列上应用一种方法以计算最终将作为新列添加到现有DataFrame中的一些值，那么pandas.DataFrame.apply()方法应该可以解决问题。