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

Making your first NumPy array

The easiest example to create a one-dimensional array would be a straightforward command.After renaming your Jupyter notebook from Untitled to array_basics, the first thing to do is to import the numpy library into your active session by typing in import numpy as np in the In [] command and running the cell.

I like to run this line first to ensure the library is installed properly so if you receive an error, double-check and ensure that conda or pip was set up correctly.See Chapter 2,Overview of Python and Installing Jupyter Notebook, for help.

Next, you want to assign the array object a variable name so you can reference it in future commands.It is common to use single character values such as a or x as a shortcut for your array but for just getting started, let's use something more descriptive, such as my_first_array for easier reference.To the right of the equals sign, we reference the numpy method using np.array followed...