How to find what values are assigned to labels that where encoded using LabelEncoder?












1












$begingroup$


places = ['India','France','India','Australia','Australia','India','India','France']



Here places are the DataFrame Series, now how can I find that which
label was encoded with values like India = 0 , Australia = 1 ,France =
2.
This is ok for few labels what if there are 100's of labels available
in a huge dataset.











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    1












    $begingroup$


    places = ['India','France','India','Australia','Australia','India','India','France']



    Here places are the DataFrame Series, now how can I find that which
    label was encoded with values like India = 0 , Australia = 1 ,France =
    2.
    This is ok for few labels what if there are 100's of labels available
    in a huge dataset.











    share|improve this question







    New contributor




    sk jainmiah is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
    Check out our Code of Conduct.







    $endgroup$















      1












      1








      1





      $begingroup$


      places = ['India','France','India','Australia','Australia','India','India','France']



      Here places are the DataFrame Series, now how can I find that which
      label was encoded with values like India = 0 , Australia = 1 ,France =
      2.
      This is ok for few labels what if there are 100's of labels available
      in a huge dataset.











      share|improve this question







      New contributor




      sk jainmiah is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.







      $endgroup$




      places = ['India','France','India','Australia','Australia','India','India','France']



      Here places are the DataFrame Series, now how can I find that which
      label was encoded with values like India = 0 , Australia = 1 ,France =
      2.
      This is ok for few labels what if there are 100's of labels available
      in a huge dataset.








      machine-learning python scikit-learn






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      asked 13 hours ago









      sk jainmiahsk jainmiah

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          $begingroup$

          Use the classes_ attribute of your LabelEncoder. For example:



          le = preprocessing.LabelEncoder()
          le.fit(places)
          print(le.classes_)


          The index of the label in le.classes_ is the encoded value of the label. See another example here.






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            $begingroup$

            Use the classes_ attribute of your LabelEncoder. For example:



            le = preprocessing.LabelEncoder()
            le.fit(places)
            print(le.classes_)


            The index of the label in le.classes_ is the encoded value of the label. See another example here.






            share|improve this answer








            New contributor




            Wes is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
            Check out our Code of Conduct.






            $endgroup$


















              0












              $begingroup$

              Use the classes_ attribute of your LabelEncoder. For example:



              le = preprocessing.LabelEncoder()
              le.fit(places)
              print(le.classes_)


              The index of the label in le.classes_ is the encoded value of the label. See another example here.






              share|improve this answer








              New contributor




              Wes is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
              Check out our Code of Conduct.






              $endgroup$
















                0












                0








                0





                $begingroup$

                Use the classes_ attribute of your LabelEncoder. For example:



                le = preprocessing.LabelEncoder()
                le.fit(places)
                print(le.classes_)


                The index of the label in le.classes_ is the encoded value of the label. See another example here.






                share|improve this answer








                New contributor




                Wes is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                Check out our Code of Conduct.






                $endgroup$



                Use the classes_ attribute of your LabelEncoder. For example:



                le = preprocessing.LabelEncoder()
                le.fit(places)
                print(le.classes_)


                The index of the label in le.classes_ is the encoded value of the label. See another example here.







                share|improve this answer








                New contributor




                Wes is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
                Check out our Code of Conduct.









                share|improve this answer



                share|improve this answer






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                Wes is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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                answered 12 hours ago









                WesWes

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                    sk jainmiah is a new contributor. Be nice, and check out our Code of Conduct.










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