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How to Handle Categorical Data

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Deals with transforming, cleaning and handling of Categorical data while performing predictions.

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How to handle Categorical Data By Srinivas Rao PrithviNag Kolla, Masters in Data Science, University of North Texas, Email: prithvikolla8@gmail.com
Categorical Variable: Generally Data falling into a fixed set of categories is called a categorical data. Ex: Survey of what type of phone brand people own comes under categorical data. Id Name Phone Brand 1 Alex Apple 2 George Nokia 3 Chen Apple 4 prithvi Samsung Dropping Categorical Variables: If the columns in the data set have categorical values , which are not useful for modeling , we can drop them.
Label Encoding: Giving a unique integer value for the labels in the categorical column. Ex: Phone Brand Apple Nokia Jio Apple Phone Brand 0 1 2 0 Label Encoding Decision Trees and Random Forests work well with Label Encoding. ‘Apple’(0) < ‘Nokia’(1) < ‘Jio’(2)
One – Hot – Encoding • As previously in Label Encoding, we gave an order based unique values to the labels. • It doesn’t work well, so we use the method of separating the categorical values into columns and give ‘1’ as they are present in that row, if not ‘0’. Ex: Phone Brand Apple Nokia Apple Jio Nokia Apple Nokia Jio 1 0 0 0 1 0 1 0 0 0 0 1 0 1 0 One-Hot-Encoding

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How to Handle Categorical Data

  • 1. How to handle Categorical Data By Srinivas Rao PrithviNag Kolla, Masters in Data Science, University of North Texas, Email: prithvikolla8@gmail.com
  • 2. Categorical Variable: Generally Data falling into a fixed set of categories is called a categorical data. Ex: Survey of what type of phone brand people own comes under categorical data. Id Name Phone Brand 1 Alex Apple 2 George Nokia 3 Chen Apple 4 prithvi Samsung Dropping Categorical Variables: If the columns in the data set have categorical values , which are not useful for modeling , we can drop them.
  • 3. Label Encoding: Giving a unique integer value for the labels in the categorical column. Ex: Phone Brand Apple Nokia Jio Apple Phone Brand 0 1 2 0 Label Encoding Decision Trees and Random Forests work well with Label Encoding. ‘Apple’(0) < ‘Nokia’(1) < ‘Jio’(2)
  • 4. One – Hot – Encoding • As previously in Label Encoding, we gave an order based unique values to the labels. • It doesn’t work well, so we use the method of separating the categorical values into columns and give ‘1’ as they are present in that row, if not ‘0’. Ex: Phone Brand Apple Nokia Apple Jio Nokia Apple Nokia Jio 1 0 0 0 1 0 1 0 0 0 0 1 0 1 0 One-Hot-Encoding