Encodage d'étiquette
from sklearn.preprocessing import LabelEncoder
le = LabelEncoder()
companydata.ShelveLoc = le.fit_transform(companydata.ShelveLoc)
Condemned Cowfish
from sklearn.preprocessing import LabelEncoder
le = LabelEncoder()
companydata.ShelveLoc = le.fit_transform(companydata.ShelveLoc)##We apply Label Encoding on black Friday dataset on the target column which is Species. It contains three species Iris-setosa, Iris-versicolor, Iris-virginica.
# Import libraries
import numpy as np
import pandas as pd
# Importing dataset
df = pd.read_csv('../../data/blackFriday.csv')
#Cheking out the unique values in your dataset
df['Age'].unique()
# Import label encoder
from sklearn import preprocessing
# label_encoder object knows how to understand word labels.
label_encoder = preprocessing.LabelEncoder()
# Encode labels in column 'Age'.
df['Age']= label_encoder.fit_transform(df['Age'])
df['Age'].unique()
obj_df["body_style"] = obj_df["body_style"].astype('category')
obj_df.dtypes
obj_df["body_style_cat"] = obj_df["body_style"].cat.codes
obj_df.head()