Python for Data Visualization - A Beginner's Guide

Python for Data Visualization - A Beginner's Guide

by Meta Brains
Released September 2023
Publisher(s): Packt Publishing
ISBN: 9781805127598

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Video description

Python-based data visualization uses the Python programming language and its libraries to transform data into visual representations, such as charts, graphs, and interactive dashboards. Python’s libraries, including Matplotlib, Seaborn, Plotly, and Bokeh, offer customizable plot types and interactive features to craft compelling visual narratives. Through data storytelling and customization, Python shares insights and effectively communicates them, making it an indispensable skill for anyone working with data.

In this course, we will begin by grasping the importance of data visualization and exploring essential Python libraries such as Matplotlib, Seaborn, and Plotly. You will learn to customize and enhance visualizations, adjust colors, labels, and legends, and understand the principles of effective data storytelling. The course delves into advanced topics such as creating interactive dashboards and dynamic data plots. We will work on practical projects and real-world examples to equip us with the skills to turn raw data into informative visuals using Python.

Upon completion, we will master Python-based data visualization from core principles to practical skills, Matplotlib, Seaborn, and Plotly, and transform raw data into compelling visuals. We will acquire tools to create visuals, convey insights, and make data-driven decisions with confidence.

What You Will Learn

  • Understand the importance/principles of effective data visualization
  • Learn Matplotlib, Seaborn, and Plotly to create various visualizations
  • Learn to tailor colors, labels, and styles to enhance visuals
  • Craft data visualizations to create compelling narratives
  • Create engaging and user-friendly interactive data displays
  • Explore geospatial data mapping and location-based visualizations

Audience

This course caters to a wide audience from beginners with no programming experience to experienced data professionals, programmers looking to expand their skillsets, business professionals seeking practical data visualization knowledge, and students/researchers aiming to strengthen their data visualization proficiency using Python. There are no specific prerequisites for this course. However, having a basic understanding of mathematics and readiness to learn are helpful attributes for successfully completing the course.

About The Author

Meta Brains: Meta Brains is a professional training brand developed by a team of software developers and finance professionals who have a passion for finance, coding, and Excel. They bring together both professional and educational experiences to create world-class training programs accessible to everyone.

Currently, they’re focused on the next great revolution in computing: The Metaverse. Their ultimate objective is to train the next generation of talent so that we can code and build the metaverse together!

Table of contents

  1. Chapter 1 : Setup and Installation
    1. Installing the Anaconda Navigator
    2. Installing Matplotlib, Seaborn, and Cufflinks
    3. Reading Data from a CSV File with Pandas
    4. Explaining Matplotlib Libraries
  2. Chapter 2 : Plotting Line Plots with Matplotlib
    1. Changing the Axis Scales
    2. Label Styling
    3. Adding a Legend
    4. Changing Colors, Line Styles, Line Width, and Markers
    5. Adding a Grid to the Chart
    6. Filling Only a Specific Area
    7. Filling Area on Line Plots and Filling Only Specific Areas
    8. Changing Fill Color of Different Areas (Negative Versus Positive, For Example)
  3. Chapter 3 : Plotting Histograms and Bar Charts with Matplotlib
    1. Changing Edge Color and Adding Shadow on the Edge
    2. Adding Legends, Titles, Location, and Rotating Pie Chart
    3. Histograms Versus Bar Charts (Part 1)
    4. Histograms Versus Bar Charts (Part 2)
    5. Changing Edge Color of the Histogram
    6. Changing the Axis Scale to Log Scale
    7. Adding Median to Histogram
    8. Advanced Histograms and Patches (Part 1)
    9. Advanced Histograms and Patches (Part 2)
    10. Overlaying Bar Plots on Top of Each Other (Part 1)
    11. Overlaying Bar Plots on Top of Each Other (Part 2)
    12. Creating Box and Whisker Plots
  4. Chapter 4 : Plotting Stack Plots and Stem Plots
    1. Plotting a Basic Stack Plot
    2. Plotting a Stem Plot
    3. Plotting a Stack Plot of Data with Constant Total
  5. Chapter 5 : Plotting Scatter Plots with Matplotlib
    1. Plotting a Basic Scatter Plot
    2. Changing the Size of the Dots
    3. Changing Colors of Markers
    4. Adding Edges to Dots
  6. Chapter 6 : Time Series Data Visualization with Matplotlib
    1. Using the Python Datetime Module
    2. Connecting Data Points by Line
    3. Converting String Dates Using the .to_datetime() Pandas Method
    4. Plotting Live Data Using FuncAnimation in Matplotlib
  7. Chapter 7 : Creating Multiple Subplots
    1. Setting Up the Number of Rows and Columns
    2. Plotting Multiple Plots in One Figure
    3. Getting Separate Figures
    4. Saving Figures to Your Computer
  8. Chapter 8 : Plotting Charts Using Seaborn
    1. Introduction to Seaborn
    2. Working on Hue, Style, and Size in Seaborn
    3. Subplots Using Seaborn
    4. Line Plots
    5. Cat Plots
    6. Jointplot, Pair Plot, and Regression Plot
    7. Controlling Plotted Figure Aesthetics
  9. Chapter 9 : Plotly and Cufflinks
    1. Installation and Setup
    2. Line, Scatter, Bar, Box, and Area Plots
    3. 3D Plots, Spread Plot, Hist Plot, Bubble Plot, and Heatmap

Product information

  • Title: Python for Data Visualization - A Beginner's Guide
  • Author(s): Meta Brains
  • Release date: September 2023
  • Publisher(s): Packt Publishing
  • ISBN: 9781805127598