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']))

Asked By: Kristofer

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Source

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.

Answered By: niraj

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

Answered By: Darshan Jain

Answer 3

 from sklearn.preprocessing import LabelEncoder
 le = LabelEncoder()
 X[:, 2] = le.fit_transform(X[:, 2])

this could be helpful if you want to change the particular column in your CSV data

Answered By: METTA APPALA GANESH KUMAR

How to apply LabelEncoder for a specific column in Pandas dataframe

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