IF + AND 语句

Question

我在Python中有一个数据框形式的'Current Result'（在Excel中描述作为插图）。

我想添加一个列来分类某行是 'PRIME' 还是 'ALT' 指定。

判断某物是否为'ALT'的规则如下：

'Group' 列是不是 'NaN'
和
'Utilization' 总是 0

嵌套的 IF / AND 语句是唯一可行的概念吗？还是有更有效的方法来做到这一点？ PS 我是 Python 的新手。

添加数据框的示例代码：

import pandas as pd
 
### Generate data from lists.
data = {'Part':['AAA', 'BBB', 'CCC', 'DDD','EEE','FFF','GGG', 'HHH', 'III', 'JJJ', 'LLL','MMM','NNN'], 'Group':['', '', '', '','','45','45', '45', '', 'FF', 'FF','7J','7J'], 'Utl':['0', '0', '0', '0','0','100','0', '0', '0', '100', '0','100','0']}
 
### Create DataFrame
df = pd.DataFrame(data)
 
### Print the output.
print(df)

Answer 1

如果没有可消化的数据，re-create 有点难，但我相信这会为您提供所需的 IIUC

data = {
    'Group' : [np.nan, None, np.nan, '7f', '7f', '7f', None, None, None, '4j', '4j', None, None, '4j'],
    'Utilization':[0, 0, 0, 100, 0, 0, 0, 0, 0, 0, 100, 0, 0, 99]
}
df = pd.DataFrame(data)
#This is here just in case you have some np.nan's instead of None it'll make everything the same
df['Group'] = df['Group'].replace({np.nan : None})
condition_list = [
    (df['Group'].values == None) | ((df['Utilization']%2 == 0) & (df['Utilization'] > 0)), 
    (df['Group'].values != None) & (df['Utilization']%2 != 0) & (df['Utilization'] > 0),
    (df['Group'].values != None) & (df['Utilization'] == 0)
]
choice_list = ['Prime', 'Alt', 'Alt']
df['Check'] = np.select(condition_list, choice_list, 0)
df

IF + AND 语句

IF + AND Statements

python

arrays

pandas

if-statement

scripting