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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

Drawing on images

Let's learn how to draw different figure shapes, such as a line, square, or triangle, on an image using OpenCV. When we draw any shape on an image, we need to take care of the coordinates, color, and thickness of the shape. Let's first create a blank image with a white or black background:

# Import cv2 latest version of OpenCV library
import cv2

# Import numeric python (NumPy) library import numpy as np
# Import matplotlib for showing the image import matplotlib.pyplot as plt
# Magic function to render the figure in a notebook %matplotlib inline
# Let's create a black image image_shape=(600,600,3) black_image = np.zeros(shape=image_shape,dtype=np.int16)
# Show the image plt.imshow(black_image)

This results in the following output:

In the preceding example, we created a blank image with a black background using the zeros() function of the NumPy module. The zeros() function creates an array of the given size and fills the matrix with zeros.

Let's create...

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