Python 使用2个dataframe列作为参数应用函数

我想应用一个函数，根据其他两列中的变量创建一列

一列“SSPstaterank”返回郊区排名

第二列“SSPstaterank%”返回郊区排名百分比

我原以为这段代码可以工作，但它返回：

TypeError在索引处发生：“DataFrame”对象不可调用 0'

使用func1代替df2：

另一个具有的解决方案应该更快：

df2 = pd.DataFrame({'SSPstaterank':[2,1,2,2,7],
                    'SSPstaterank%':[.99,.93,.93,.98,.23]})


m1 = df2['SSPstaterank'] == 1
m2 = df2['SSPstaterank%'] >= 0.95
m3 = df2['SSPstaterank%'] >= 0.9

masks = [m1, m2, m3]
vals = ['the #1 suburb','ranked top 5% of suburbs','ranked top 10% of suburbs']

df2['rankdescript'] = np.select(masks, vals, default='not matched')
print (df2)
   SSPstaterank  SSPstaterank%               rankdescript
0             2           0.99   ranked top 5% of suburbs
1             1           0.93              the #1 suburb
2             2           0.93  ranked top 10% of suburbs
3             2           0.98   ranked top 5% of suburbs
4             7           0.23                not matched

使用func1代替df2：

另一个具有的解决方案应该更快：

df2 = pd.DataFrame({'SSPstaterank':[2,1,2,2,7],
                    'SSPstaterank%':[.99,.93,.93,.98,.23]})


m1 = df2['SSPstaterank'] == 1
m2 = df2['SSPstaterank%'] >= 0.95
m3 = df2['SSPstaterank%'] >= 0.9

masks = [m1, m2, m3]
vals = ['the #1 suburb','ranked top 5% of suburbs','ranked top 10% of suburbs']

df2['rankdescript'] = np.select(masks, vals, default='not matched')
print (df2)
   SSPstaterank  SSPstaterank%               rankdescript
0             2           0.99   ranked top 5% of suburbs
1             1           0.93              the #1 suburb
2             2           0.93  ranked top 10% of suburbs
3             2           0.98   ranked top 5% of suburbs
4             7           0.23                not matched

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第二种解决方案可能更快；使用df.apply…，axis=1通常非常慢。第二个解决方案可能更快；使用df.apply…，axis=1通常非常慢。

df2 = pd.DataFrame({'SSPstaterank':[2,1,2,2,7],
                    'SSPstaterank%':[.99,.93,.93,.98,.23]})


m1 = df2['SSPstaterank'] == 1
m2 = df2['SSPstaterank%'] >= 0.95
m3 = df2['SSPstaterank%'] >= 0.9

masks = [m1, m2, m3]
vals = ['the #1 suburb','ranked top 5% of suburbs','ranked top 10% of suburbs']

df2['rankdescript'] = np.select(masks, vals, default='not matched')
print (df2)
   SSPstaterank  SSPstaterank%               rankdescript
0             2           0.99   ranked top 5% of suburbs
1             1           0.93              the #1 suburb
2             2           0.93  ranked top 10% of suburbs
3             2           0.98   ranked top 5% of suburbs
4             7           0.23                not matched