Any way to get mappings of a label encoder in Python pandas?

Question

I am converting strings to categorical values in my dataset using the following piece of code.

data[\'weekday\'] = pd.Categorical.from_array(data.weekday).labels         


        

Answer 1

If you have numerical and categorical both type of data in dataframe You can use : here X is my dataframe having categorical and numerical both variables

from sklearn import preprocessing
le = preprocessing.LabelEncoder()

for i in range(0,X.shape[1]):
    if X.dtypes[i]=='object':
        X[X.columns[i]] = le.fit_transform(X[X.columns[i]])

Or you can try this:

from sklearn.preprocessing import LabelEncoder

le = LabelEncoder()
data = data.apply(le.fit_transform)

Note: This technique is good if you are not interested in converting them back.

Answer 2

The best way of doing this can be to use label encoder of sklearn library.

Something like this:

from sklearn import preprocessing
le = preprocessing.LabelEncoder()
le.fit(["paris", "paris", "tokyo", "amsterdam"])
list(le.classes_)
le.transform(["tokyo", "tokyo", "paris"])
list(le.inverse_transform([2, 2, 1]))