熊猫数据框系列:检查特定值是否存在

时间:2020-05-20 15:15:01

标签: python pandas pandas-groupby

如果列表中的值存在于pandas dataframe列之一中,则我需要遍历列表并执行特定操作。我尝试执行以下操作,但出现错误

'错误:#系列的真值不明确。使用a.empty,a.bool(),a.item(),a.any()或a.all()。'

import pandas as pd

people = {
    'fname':['Alex','Jane','John'],
    'age':[20,15,25],
    'sal':[100,200,300]
}

df=pd.DataFrame(people)

check_list=['Alex','John']

for column in check_list:
    if (column == df['fname']):
        df['new_column']=df['sal']/df['age']
    else:
        df['new_column']=df['sal']

df

必需的输出

fname   age sal new_column
Alex    20  100  5      <<-- sal/age
Jane    15  200  200    <<-- sal as it is
John    25  300  12     <<-- sal/age

3 个答案:

答案 0 :(得分:4)

使用np.where.isin来检查一列是否包含特定值。

df['new_column'] = np.where(
        df['fname'].isin(['Alex','John']),
        df['sal']/df['age'],
        df['sal']
)

print(df)

  fname  age  sal  new_column
0  Alex   20  100         5.0
1  Jane   15  200       200.0
2  John   25  300        12.0

纯熊猫版本。

df['new_column'] = (df['sal']/df['age']).where(
                            df['fname'].isin(['Alex','John']),other=df['sal'])

print(df)
 fname  age  sal  new_col
0  Alex   20  100      5.0
1  Jane   15  200    200.0
2  John   25  300     12.0

答案 1 :(得分:1)

尝试使用df.apply

import pandas as pd

people = {
    'fname':['Alex','Jane','John'],
    'age':[20,15,25],
    'sal':[100,200,300]
}

df=pd.DataFrame(people)

def checker(item):
    check_list=['Alex','John']
    if item["fname"] in check_list:
        return item['sal']/item['age']
    else:
        return item['sal']

df["Exists"] = df.apply(checker, axis=1)

df


答案 2 :(得分:1)

for index,row in df.iterrows():
    if row['fname'] in check_list:
           df.at[index,'new_column']=row['sal']/row['age']
    else:
           df.at[index,'new_column']=row['sal']

说明:要遍历数据框,请使用iterrows(),行变量将具有所有列的值,索引是行的索引。