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transform categorical variables python

from sklearn.preprocessing import LabelEncoder

lb_make = LabelEncoder()
obj_df["make_code"] = lb_make.fit_transform(obj_df["make"])
obj_df[["make", "make_code"]].head(11)
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how to convert contionous data into categorical data in python

pd.cut(df.Age,bins=[0,2,17,65,99],labels=['Toddler/Baby','Child','Adult','Elderly'])
# where bins is cut off points of bins for the continuous data 
# and key things here is that no. of labels is always less than 1
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how to change value of categorical variable in python

df['Gender'].str[0].str.upper().map({'M':'Male', 'F':'Female'})
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Converting categorical variable to numeric variable in python

## Converting Age to numeric variable

df['Gender']=pd.get_dummies(df['Gender'],drop_first=1)
df.head()
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