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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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 Navlani Navlani
Author Profile Icon Navlani
Navlani
Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
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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

Discrete and continuous attributes

There are various ways to classify attributes. In the previous sub-section, we have seen nominal, ordinal, and numeric attributes. In this sub-section, we will see another type of attribute classification. Here, we will talk about discrete or continuous attributes. A discrete variable accepts only a countable finite number, such as how many students are present in a class, how many cars are sold, and how many books are published. It can be obtained by counting numbers. A continuous variable accepts an infinite number of possible values, such as the weight and height of students. It can be obtained by measuring.

A discrete variable accepts integral values, while a continuous variable accepts real values. In other words, we can say a discrete variable accepts values whose fraction doesn't make sense, whereas a continuous variable accepts values whose fraction makes sense. A discrete attribute uses a limited number of values, while a continuous...

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