Sklearn Label Encoding multiple columns pandas dataframe

Question

I try to encode a number of columns containing categorical data (\"Yes\" and \"No\") in a large pandas dataframe. The complete dataframe contains

Answer 1

First, find out all the features with type object:

objList = all_data.select_dtypes(include = "object").columns
print (objList)

Now, to convert the above objList features into numeric type, you can use a forloop as given below:

#Label Encoding for object to numeric conversion
from sklearn.preprocessing import LabelEncoder
le = LabelEncoder()

for feat in objList:
    df[feat] = le.fit_transform(df[feat].astype(str))

print (df.info())

Note that we are explicitly mentioning as type string in the forloop because if you remove that it throws an error.