Data Preprocessing In Python.

Data preprocessing :

(Data preprocessing)

Data preprocessing steps:

Library
Package and Library
(The Three Musketeers)
(Import dataset)
(Matrix of features)
(Features)
(Missing data)
  1. Numerical data: Represents quantitative measurements. Numerical data contains Discrete data (Proper countable) and Continuous data (Infinite possible values)
  2. Categorical data: The data that has no mathematical meaning. For example True, False etc.
  3. Ordinal data: It is a mixture of numerical and categorical data. For example 1–5 scale where 5 is perfect and 1 is worse.
(Categorical data)
(Splitting datasets)
(Scaling)

Practical Scene:

(Dataset)
(Import dataset into Spyder)
(Matrix of feature results)
(Missing data result)
(Label Encode on Dependent feature)
(OneHotEncoder results)
(Splitting)
(After scaling)

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Data Science Engineer

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Kishan Tongrao

Kishan Tongrao

Data Science Engineer

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