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
Supervised Learning - Regression Analysis

Regression is the most popular algorithm in statistics and machine learning. In the machine learning and data science field, regression analysis is a member of the supervised machine learning domain that helps us to predict continuous variables such as stock prices, house prices, sales, rainfall, and temperature. As a sales manager at an electronic store, for example, say you need to predict the sales of upcoming weeks for all types of products, such as televisions, air conditioners, laptops, refrigerators, and many more. Lots of factors can affect your sales, such as weather conditions, festivals, promotion strategy, competitor offers, and so on. Regression analysis is one of the tools that can help you to identify the importance of such factors that are important to make decisions at the store.

Regression analysis identifies how the...