Python groupby-根据其他列中的条件更改列值

我想先按“组”列分组。 然后根据“结果”列和“排名”列中的条件更改“结果”列中的值

这就是我现在拥有的：

import pandas as pd
import numpy as np

group = ['g1','g1','g1','g1','g1','g2','g2','g2','g2','g2','g2']
rank = ['1','2','3','4','5','1','2','3','4','5','6']
result = ['1','4','2','4','4','1','4','4','2','4','4']

df = pd.DataFrame({"group": group, "rank": rank, "result": result})

    group   rank    result
0   g1        1       1
1   g1        2       4
2   g1        3       2
3   g1        4       4
4   g1        5       4
5   g2        1       1
6   g2        2       4
7   g2        3       4
8   g2        4       2
9   g2        5       4
10  g2        6       4

在同一组中，当秩大于result=2的秩时，我想将结果从4更改为6
例如：在g1中，result=2的排名是3。因此，排名4和5的结果将是6。
在g2中，result=2的秩为4。因此排名5和6的结果将是6。

在这种情况下，我希望的输出是：

    group   rank    result
0   g1        1       1
1   g1        2       4
2   g1        3       2
3   g1        4       6
4   g1        5       6
5   g2        1       1
6   g2        2       4
7   g2        3       4
8   g2        4       2
9   g2        5       6
10  g2        6       6

我不知道实现这一目标的最佳方法。有人能帮忙吗

提前谢谢

用于将结果中与

2

匹配的行的

rank

替换为

NaN

，然后用于每组的重复值by，最后一次比较较大的by和设置值

6

：

这样就行了

import pandas as pd
import numpy as np

group = ['g1','g1','g1','g1','g1','g2','g2','g2','g2','g2','g2']
rank = ['1','2','3','4','5','1','2','3','4','5','6']
result = ['1','4','2','4','4','1','4','4','2','4','4']

df = pd.DataFrame({"group": group, "rank": rank, "result": result})

def changeDf(x):
    df_gp = df[df['group'] == x['group']]
    rank_of_2 = df_gp.loc[df_gp['result'] =='2', 'rank'].values[0]
    if int(x['rank']) > int(rank_of_2):
        return '6'
    else:
        return x['result']

df['result'] = df.apply(changeDf, axis=1)
print(df)

---

如果不匹配“2”，此操作将失败，并且无法更正比较字符串（如

10

）。因为例如

'5'>'10'

import pandas as pd
import numpy as np

group = ['g1','g1','g1','g1','g1','g2','g2','g2','g2','g2','g2']
rank = ['1','2','3','4','5','1','2','3','4','5','6']
result = ['1','4','2','4','4','1','4','4','2','4','4']

df = pd.DataFrame({"group": group, "rank": rank, "result": result})

def changeDf(x):
    df_gp = df[df['group'] == x['group']]
    rank_of_2 = df_gp.loc[df_gp['result'] =='2', 'rank'].values[0]
    if int(x['rank']) > int(rank_of_2):
        return '6'
    else:
        return x['result']

df['result'] = df.apply(changeDf, axis=1)
print(df)