Python 要检查Dataframe列是否为TRUE/FALSE，如果为TRUE，请检查另一列是否满足条件，并生成值为PASS/FAIL的新列

输入说明： 我有一个数据帧'df'，它包含'Space'和'Threshold'列

Space   Threshold

TRUE    0.1

TRUE    0.25

FALSE   0.5

FALSE   0.6

要考虑的场景：

---

当df['Space']为真时，检查df['Threshold']如果

TRUE

为布尔值，则您的解决方案仅通过比较

df['Space']

简化：

df['Space_Test'] = np.where(df['Space'],
                   np.where(df['Threshold'] <= 0.2, 'Pass', 'Fail'),'FALSE')
print (df)
   Space  Threshold Space_Test
0   True       0.10       Pass
1   True       0.25       Fail
2  False       0.50      FALSE
3  False       0.60      FALSE

另一个解决方案

from pandas import DataFrame

names = {
    'Space': ['TRUE','TRUE','FALSE','FALSE'],
    'Threshold': [0.1, 0.25, 1, 2]
         }
df = DataFrame(names,columns=['Space','Threshold'])

df.loc[(df['Space'] == 'TRUE') & (df['Threshold'] <= 0.2), 'Space_Test'] = 'Pass'
df.loc[(df['Space'] != 'TRUE') | (df['Threshold'] > 0.2), 'Space_Test'] = 'Fail'

print (df)

从导入数据帧
姓名={
“空格”：[“真”、“真”、“假”、“假”]，
“阈值”：[0.1,0.25,1,2]
}
df=DataFrame（名称、列=['Space'，'Threshold']）
df.loc[（df['Space']='TRUE'）&（df['Threshold']0.2），'Space\u Test']='Fail'
打印（df）

df['Space_Test'] = np.where(df['Space'],
                   np.where(df['Threshold'] <= 0.2, 'Pass', 'Fail'),'FALSE')
print (df)
   Space  Threshold Space_Test
0   True       0.10       Pass
1   True       0.25       Fail
2  False       0.50      FALSE
3  False       0.60      FALSE

m1 = df['Space']
m2 = df['Threshold'] <= 0.2
df['Space_Test'] = np.select([m1 & m2, m1 & ~m2], ['Pass', 'Fail'],'FALSE')
print (df)
   Space  Threshold Space_Test
0   True       0.10       Pass
1   True       0.25       Fail
2  False       0.50      FALSE
3  False       0.60      FALSE

from pandas import DataFrame

names = {
    'Space': ['TRUE','TRUE','FALSE','FALSE'],
    'Threshold': [0.1, 0.25, 1, 2]
         }
df = DataFrame(names,columns=['Space','Threshold'])

df.loc[(df['Space'] == 'TRUE') & (df['Threshold'] <= 0.2), 'Space_Test'] = 'Pass'
df.loc[(df['Space'] != 'TRUE') | (df['Threshold'] > 0.2), 'Space_Test'] = 'Fail'

print (df)