python - 用于重新映射值的 If 语句

Question

我正在尝试创建一个 if 语句，如果“薪资类别”列是“费用”，则用“法律”填充工具类型列。

但是，无论付款类别如何，它都会将包含 Legal 的所有内容标记为 Legal。

test={"Pay Category":["Indemnity","Indemnity","Indemnity","Indemnity","Expense","Expense","Expense","Medical"],"Description of Payment":["Legal","Legal","Legal","Legal","Legal","Legal","Frog","Legal",]}
test=pd.DataFrame(test)

test["Tool Type"]=""
if (test["Pay Category"]=="Medical") is not False: 
test["Tool Type"][test["Description of Payment"].str.contains("Pharmacy|Prescription|RX",case=False)]="Pharmacy"

if (test["Pay Category"]=='Expense') is not False:
test["Tool Type"][test["Description of Payment"].str.contains("Legal|Attorney|Court|Defense",case=False)]="Legal"

我的理解是，if (test["Pay Category"]=='Expense') is not False: 是一个 bool 值，True 或 False ，它应该只在满足条件“不为假”时执行 if 语句。我错过了什么？

布兰登

Answer 1

我认为您需要添加条件并将它们与 & (and)链接:

test["Tool Type"]=""
m1 = test["Description of Payment"].str.contains("Pharmacy|Prescription|RX",case=False)
m2 = test["Pay Category"]=="Medical"

m3 = test["Description of Payment"].str.contains("Legal|Attorney|Court|Defense",case=False)
m4 = test["Pay Category"]=="Expense"

test.loc[m1 & m2, "Tool Type"]="Pharmacy"
test.loc[m3 & m4, "Tool Type"]="Legal"
print (test)
  Description of Payment Pay Category Tool Type
0                  Legal    Indemnity          
1                  Legal    Indemnity          
2                  Legal    Indemnity          
3                  Legal    Indemnity          
4                  Legal      Expense     Legal
5                  Legal      Expense     Legal
6                   Frog      Expense          
7                  Legal      Medical          

另一个带有双 numpy.where 的解决方案:

test['Tool Type'] = np.where(m1 & m2, 'Pharmacy',
                    np.where(m3 & m4, 'Legal', ''))
print (test)
  Description of Payment Pay Category Tool Type
0                  Legal    Indemnity          
1                  Legal    Indemnity          
2                  Legal    Indemnity          
3                  Legal    Indemnity          
4                  Legal      Expense     Legal
5                  Legal      Expense     Legal
6                   Frog      Expense          
7                  Legal      Medical          

编辑:非常好的解决方案 unutbu评论是使用numpy.select

test['Tool Type']  = np.select([(m1 & m2), (m3 & m4)], ['Pharmacy', 'Legal'], default='')
print (test)
  Description of Payment Pay Category Tool Type
0                  Legal    Indemnity          
1                  Legal    Indemnity          
2                  Legal    Indemnity          
3                  Legal    Indemnity          
4                  Legal      Expense     Legal
5                  Legal      Expense     Legal
6                   Frog      Expense          
7                  Legal      Medical