Book Image

Practical Data Analysis Using Jupyter Notebook

By : Marc Wintjen
Book Image

Practical Data Analysis Using Jupyter Notebook

By: Marc Wintjen

Overview of this book

Data literacy is the ability to read, analyze, work with, and argue using data. Data analysis is the process of cleaning and modeling your data to discover useful information. This book combines these two concepts by sharing proven techniques and hands-on examples so that you can learn how to communicate effectively using data. After introducing you to the basics of data analysis using Jupyter Notebook and Python, the book will take you through the fundamentals of data. Packed with practical examples, this guide will teach you how to clean, wrangle, analyze, and visualize data to gain useful insights, and you'll discover how to answer questions using data with easy-to-follow steps. Later chapters teach you about storytelling with data using charts, such as histograms and scatter plots. As you advance, you'll understand how to work with unstructured data using natural language processing (NLP) techniques to perform sentiment analysis. All the knowledge you gain will help you discover key patterns and trends in data using real-world examples. In addition to this, you will learn how to handle data of varying complexity to perform efficient data analysis using modern Python libraries. By the end of this book, you'll have gained the practical skills you need to analyze data with confidence.
Table of Contents (18 chapters)
1
Section 1: Data Analysis Essentials
7
Section 2: Solutions for Data Discovery
12
Section 3: Working with Unstructured Big Data
16
Works Cited

Geoanalytical techniques and tips

For a data analyst, the concept of geoanalytics is a relatively new technique applied to spatial data to understand where data is geographically located. However, cartography, which is the study of maps, has been around for centuries and traditionally requires training, expertise, and niche software to provided insights from data by location. Today, there are multiple add-on modules and software available to create charts and visualizations that use maps to visualize data in exciting ways that provide a different perspective.

First, you need to understand the grain of the data you have available. Having precision of the exact latitude and longitude available in your source data is a luxury unless the source system was built to capture that information. For example, mobile app source data will commonly have this level of detail available because a smartphone can track your location. However, if we go back to our COVID-19 source...