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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
Mixed variables are a type of variable that can have both numbers and labels as values. Mixed variables occur in a dataset when filling its values. 

Here is an example showing two types of mixed variables, each one in a column:




# Definition
Mixed variables are a type of variable that can have both numbers and labels as values. Mixed variables occur in a dataset when filling its values. 

Here is an example showing two types of mixed variables, each one in a column:




Mixed variables are a particular type of variable. They are pretty rare but can be found in some datasets. For this reason, we will talk about them in this lesson while looking at a detailed example of how these variables occur.

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

Mixed variables

Definition