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Numerical Variables

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In this course, you will learn how to apply basic and more advanced feature engineering to tabular data with python, during this course,  we will see a range of different techniques and methods to handle many common cases within the data set, so in result, you will create great features so that your machine learning models can predict good results.

Feature Engineering with Python

## Definition
Complete case analysis (CCA) describes the act of including only observations for which we have no missing data on the variables of interest. Moreover, exclude all observations with any missing.

> This method works with both categorical and numerical variables.

See the following example to understand the concept better:


# Definition
Complete case analysis (CCA) describes the act of including only observations for which we have no missing data on the variables of interest. Moreover, exclude all observations with any missing.

> This method works with both categorical and numerical variables.

See the following example to understand the concept better:


Complete case analysis is a data imputation technique suitable for categorical and numerical variables. The objective of this lesson is to understand this method, its assumptions, its advantages and disadvantages, and the scenarios in which we can use it to deal with missing data.


Complete case analysis

Complete case analysis is a data imputation technique suitable for categorical and numerical variables. The objective of this lesson is to understand this method, its assumptions, its advantages and disadvantages, and the scenarios in which we can use it to deal with missing data.

Introduction

Variable Types

Common Concerns in Datasets

Handling & Imputing Missing Values

Encoding Categorical Variables

Transforming Variables

Variable Discretization

Handling Outliers

Feature Scaling

Engineering Geospatial Data

Handling Date-Time and Mixed Variables

Resampling Imbalanced Data

Advanced Feature Engineering Techniques

Conclusion

Complete case analysis

Definition