Book Image

Python Data Analysis - Third Edition

By : Avinash Navlani, Ivan Idris
5 (1)
Book Image

Python Data Analysis - Third Edition

5 (1)
By: Avinash Navlani, Ivan Idris

Overview of this book

Data analysis enables you to generate value from small and big data by discovering new patterns and trends, and Python is one of the most popular tools for analyzing a wide variety of data. With this book, you’ll get up and running using Python for data analysis by exploring the different phases and methodologies used in data analysis and learning how to use modern libraries from the Python ecosystem to create efficient data pipelines. Starting with the essential statistical and data analysis fundamentals using Python, you’ll perform complex data analysis and modeling, data manipulation, data cleaning, and data visualization using easy-to-follow examples. You’ll then understand how to conduct time series analysis and signal processing using ARMA models. As you advance, you’ll get to grips with smart processing and data analytics using machine learning algorithms such as regression, classification, Principal Component Analysis (PCA), and clustering. In the concluding chapters, you’ll work on real-world examples to analyze textual and image data using natural language processing (NLP) and image analytics techniques, respectively. Finally, the book will demonstrate parallel computing using Dask. By the end of this data analysis book, you’ll be equipped with the skills you need to prepare data for analysis and create meaningful data visualizations for forecasting values from data.
Table of Contents (20 chapters)
Section 1: Foundation for Data Analysis
Section 2: Exploratory Data Analysis and Data Cleaning
Section 3: Deep Dive into Machine Learning
Section 4: NLP, Image Analytics, and Parallel Computing

Flipping images

Flipping an image is equivalent to a mirror effect. Let's learn how to flip an image across the x axis (vertical flipping), y axis (horizontal flipping), or both axes. OpenCV offers the flip() function to flip an image. The flip() function will take two arguments: image and flipcode. The image is a NumPy array of pixel values and the flipcode used defines the type of flip, such as horizontal, vertical, or both. The following flipcode values are for different types of flips:

  • Flipcode > 0 is for a horizontal flip.
  • Flipcode = 0 is for a vertical flip.
  • Flipcode < 0 is for both a horizontal and vertical flip.

Let's see an example of flipping an image:

# Import OpenCV module
import cv2

# Import NumPy
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

# Read image
image = cv2.imread('messi.png')

# Convert image color space BGR to RGB