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
Analyzing Textual Data

In the age of information, data is produced at incredible speeds and volumes. The data produced is not only structured or tabular types, it can also be in a variety of unstructured types such as textual data, image or graphic data, speech data, and video. Text is a very common and rich type of data. Articles, blogs, tutorials, social media posts, and website content all produce unstructured textual data. Thousands of emails, messages, comments, and tweets are sent by people every minute. Such a large amount of text data needs to be mined. Text analytics offers lots of opportunities for business people; for instance, Amazon can interpret customer feedback on a particular product, news analysts can analyze news trends and the latest issues on Twitter, and Netflix can also interpret reviews of each movie and web series. Business analysts can interpret customer...