我想不出这个错误。我认为这是我对数据帧和索引的误解。另外,可能是对for循环的误解。(我习惯了matlab 对于 循环…直观地说,迭代更容易:d)

错误如下:

KeyError: "['United States' 'Canada' 'Mexico'] not found in axis"

这发生在一行: as_df=as_df.drop(as_df[column])

但这毫无意义…我调用的是一个单独的列,而不是整个虚拟变量集。

可以复制并运行以下代码。我确定了。

我的代码:

import pandas as pd
import numpy as np
df=pd.DataFrame({"country": ['United States','Canada','Mexico'], "price": [23,32,21], "points": [3,4,4.5]})
df=df[['country','price','points']]
df2=df[['country']]
features=df2.columns
print(features)
target='points'

#------_-__-___---____________________
as_df=pd.concat([df[features],df[target]],axis=1)
#Now for Column Check
for column in as_df[features]:
    col=as_df[[column]]
    #Categorical Data Conversion
#This will split the countries into their own column with 1 being when it 
#is true and 0 being when it is false
    col.select_dtypes(include='object')
    dummies=pd.get_dummies(col)
    #ML Check:
    dumcols=dummies.drop(dummies.columns[1],axis=1)
    if dumcols.shape[1] > 1:
        print(column)
        as_df=as_df.drop(as_df[column])
    else:
        dummydf=col
as_df=pd.concat([as_df,dummydf],axis=1)
as_df.head()