I get key error whenever I try to encode categorical_features in my dataframe - categorical-data

Question

These are the names of categorical features names that I have stored in a list
my_list=['MSZoning','Street','LotShape','LandContour','Utilities','LotConfig','LandSlope',
'Neighborhood','Condition1','Condition2','BldgType','HouseStyle','RoofStyle','RoofMatl',
'Exterior1st','Exterior2nd','MasVnrType','ExterQual','ExterCond','Foundation','BsmtFinType2',
'Heating','HeatingQC','CentralAir','KitchenQual','Functional','GarageType','GarageFinish',
'GarageQual','GarageCond','PavedDrive','SaleType','SaleCondition']
my code for encoding is as follows:
for cols in my_list:
df[cols]=pd.get_dummies(df[cols],drop_first=True)
I get the following error:
KeyError: 'MSZoning'
During handling of the above exception, another exception occurred:
I tried the above method for another dataset but it worked just fine but here it is giving me above error.

Answer 1

First of all , welcome to the Stack Overflow
for cols in my_list:
df[cols]=pd.get_dummies(df[cols], drop_first=True)
Reason of getting error:
You are getting KeyError because of the attribute drop_first=True in pd.get_dummies() function.
Explanation
So before making any dummy column pd.get_dummies() function is checking whether that column is present in the dataframe or not.
For example, you want to make dummy column MSZoning in the your dataframe df. So the function (get_dummies) is first checking whether MSZoning column is present in your df or not. If it is present in the df, it will delete that column and make a new column with the name MSZoning because you have written drop_first=True which means the drop or delete the first column of the same name whose dummy is to be created right now.
Solution
Remove that line drop_first = True and write it like below
for cols in my_list:
df[cols]=pd.get_dummies(df[cols])