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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

Color models

Color models are a structure for processing and measuring the combination of primary colors. They help us to explain how colors will display on the computer screen or on paper. Color models can be of two types: additive or subtractive. Additive models are used for computer screens, for example, the RGB (red, green, and blue) model, and subtractive models are used for printing images, for example, the CMYK (cyan, magenta, yellow, and black) model:

There are lots of models other than RGB and CMYK, such as HSV, HSL, and Gray Scale. HSV is an acronym for hue, saturation, and value. It is a three-dimensional color model, which is an improved version of the RGB model. In the HSV model, the top of the center axis is white, the bottom is black, and the remaining colors lie in between. Here, the hue is the angle, saturation is the distance from the center axis, and value is the distance from the bottom of the axis.

HSL is an acronym for hue, saturation, and lightness. The main difference...

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