通过应用具有多个条件的IF语句为列赋值

djp7away 于 2022-09-21 发布在其他

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如何修复这段代码，因为我试图根据各种条件给列中的值赋值。编写下面的代码会给我一个错误，提示我：

The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all()

list = [df1,df2,df3,df4]             # multiple dataframes
grp_list = ["con", "eco", "dip", "pol"]      # multiple categories in a column 

for i in list: 
    if i['pgp'].isin(group_list) and (i.egp == i.pgp):
        i['value'] == 1
    elif ~i['pgp'].isin(group_list):
        i['value'] == 2
    else:
        i['value'] == 0

预期输出df1：

pgp     egp     value
con     con      1     # return 1 if pgp value is in the element list & pgp = egp
eco     eco      1     
dip     health   0     # else 0
pol     health   0
god     con      2
ent     eco      2     # return 2 if pgp value is not in the element list

pandas

来源：https://stackoverflow.com/questions/73790151/assigning-value-to-a-column-by-applying-if-statement-with-multiple-conditions

2条答案

按热度按时间

k97glaaz1#

使用np.select~

def apply_conditions(df, group_list):
    in_group_list = df['pgp'].isin(group_list)
    conditions = (
        in_group_list & df['egp'].eq(df['pgp']),
        ~in_group_list
    )
    choices = (
        1,
        2
    )
    df['value'] = np.select(conditions, choices, default=0)
    return df

dfs = [df1,df2,df3,df4]
grp_list = ['con', 'eco', 'dip', 'pol']

dfs = [apply_conditions(df, grp_list) for df in dfs]

赞(0）回复(0）举报 2022-09-21

kpbwa7wx2#

您可以在此处使用np.select：

import numpy as np

df1 = pd.DataFrame({
    'pgp': ['con', 'eco', 'dip', 'pol', 'god', 'ent'],
    'egp': ['con', 'eco', 'health', 'health', 'con', 'eco']
})

grp_list = ["con", "eco", "dip", "pol"]

m1 = df1['pgp'].isin(grp_list)
m2 = df1['pgp'] == df1['egp']

conditions=[m1&m2, ~m1]
choices = [1, 2]

df1['value'] = np.select(conditions, choices, default=0)
print(df1)

产出：

pgp     egp  value
0  con     con      1
1  eco     eco      1
2  dip  health      0
3  pol  health      0
4  god     con      2
5  ent     eco      2

赞(0）回复(0）举报 2022-09-21

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通过应用具有多个条件的IF语句为列赋值

2条答案

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