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Python Data Analysis

You're reading from   Python Data Analysis Perform data collection, data processing, wrangling, visualization, and model building using Python

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Product type Paperback
Published in Feb 2021
Publisher Packt
ISBN-13 9781789955248
Length 478 pages
Edition 3rd Edition
Languages
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Authors (2):
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Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
Avinash Navlani Avinash Navlani
Author Profile Icon Avinash Navlani
Avinash Navlani
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Toc

Table of Contents (20) Chapters Close

Preface 1. Section 1: Foundation for Data Analysis
2. Getting Started with Python Libraries FREE CHAPTER 3. NumPy and pandas 4. Statistics 5. Linear Algebra 6. Section 2: Exploratory Data Analysis and Data Cleaning
7. Data Visualization 8. Retrieving, Processing, and Storing Data 9. Cleaning Messy Data 10. Signal Processing and Time Series 11. Section 3: Deep Dive into Machine Learning
12. Supervised Learning - Regression Analysis 13. Supervised Learning - Classification Techniques 14. Unsupervised Learning - PCA and Clustering 15. Section 4: NLP, Image Analytics, and Parallel Computing
16. Analyzing Textual Data 17. Analyzing Image Data 18. Parallel Computing Using Dask 19. Other Books You May Enjoy

Dummy variables

Dummy variables are categorical independent variables used in regression analysis. It is also known as a Boolean, indicator, qualitative, categorical, and binary variable. Dummy variables convert a categorical variable with N distinct values into N–1 dummy variables. It only takes the 1 and 0 binary values, which are equivalent to existence and nonexistence.

pandas offers the get_dummies() function to generate the dummy values. Let's understand the get_dummies() function through an example:

# Import pandas module
import pandas as pd

# Create pandas DataFrame data=pd.DataFrame({'Gender':['F','M','M','F','M']})
# Check the top-5 records data.head()

This results in the following output:

Gender

0

F

1

M

2

M

3

F

4

M

In the preceding code block, we have created the DataFrame with the Gender column and generated the dummy variable using the get_dummies() function...

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