How to apply LabelEncoder for a specific column in Pandas dataframe

Question

I have a dataset loaded by dataframe where the class label needs to be encoded using LabelEncoder from scikit-learn. The column label is the class label column which has the following classes:

[‘Standing’, ‘Walking’, ‘Running’, ‘null’] 

To perform label encoding, I tried the following but it does not work. How can I fix it?

from sklearn import preprocessing import pandas as pd  df = pd.read_csv('dataset.csv', sep=',')  df.apply(preprocessing.LabelEncoder().fit_transform(df['label'])) 

Answer 1

You can try as following:

le = preprocessing.LabelEncoder() df['label'] = le.fit_transform(df.label.values) 

Or following would work too:

df['label'] = le.fit_transform(df['label']) 

It will replace original label values in dataframe with encoded labels.

Answer 2

You can also do:

from sklearn.preprocessing import LabelEncoder le = LabelEncoder() df.col_name= le.fit_transform(df.col_name.values) 

where col_name = the feature that you want to label encode