Data Visualization in Python by Examples

COURSE
Packt Admin
1 hr

Data Visualization in Python by Examples

COURSE
Packt Admin
1 hr
$124.99per person
OR
Included in GO1 PremiumStarting from $12 per user for teamsLearn moreTry it free
$124.99per person
OR
Included in GO1 PremiumStarting from $12 per user for teamsLearn moreTry it free

Course Overview 

Data visualization is just a wise investment in your future big-data needs. You will learn how to deploy maps and networks to display geographic and network data. To do this, we will focus on the following very popular libraries in Python: matplotlib, ggplot, seaborn, and plotly. In this course, you will walk through some of the fundamentals of data visualization, sharing many examples of how to handle different types of data and how best to present your insights. We'll take a look at chart types, such as Matplotlib for visualizing the impact of tornadoes in the US, North Korean nuke tests on global stocks, and analyze forex performances using charts. You will see how ggplot can be used to analyze trends in BRICS economies and crude oil price trends. You will see how to level up your data visualization skills using Python's advanced plotting libraries: matplotlib and Seaborn, and how you can present the data from the most unstable regions in the world through data visualization. You will then carry out a visual analysis of the performance of various Hollywood releases. Finally, you will use Plotly to plot comparative graphs of Apple iPhone version releases and compare the performance of gaming consoles such as Xbox and PlayStation. Style and Approach: This friendly course takes you through data visualization in Python using matplotlib, ggplot, seaborn, and plotly. It is packed with step-by-step instructions and working examples. This comprehensive course is divided into clear bite-size chunks so you can learn at your own pace and focus on the areas of most interest to you.


Target Audience 

This course is designed for all Python users who wish to enter the field of data visualization or enhance their data visualization skills to become more effective visual communicators. The target audience includes business analysts; data analysts; web developers; scientists; journalists; product managers; program managers; political and marketing campaign staff; decision makers


Learning Objectives 

  • Set up various data visualization tools available in Python
  • Learn the best ways to visualize data on the most interesting data sets
  • Create your own plots to show the impact of events on different trends
  • Visualize relationships, patterns between various activities
  • Identify and act on emerging trends more rapidly
  • Manipulate and interact directly with data
  • Foster a new business language for your board meetings
  • Absorb information in new and more constructive ways
  • Add impact to data analysis by visualizing the interpretation

Business Outcomes  

  • Use data visualization as your preferred business reporting tool
  • Add impact to your data by representing information in the form of a chart, diagram, pictures, and so on
  • Deploy plots and charts using various data visualization tools in Python 
Learning
Section 1: Programming Data Visualizations Using Python's Matplotlib
1.1 The Course Overviewvideo
1.2 Setting Up and Getting Started with Python Data Visualizationvideo
1.3 Analyzing Effects of Tornadoes in the US – Most Affected Statesvideo
1.4 Analyzing Effects of Tornadoes in the US – Least Affected Statesvideo
1.5 Plots – Impact of North Korean Atomic Test on Global Stock Marketsvideo
1.6 Analyzing Forex Performance Using Custom Chartsvideo
Section 2: Data Visualization with ggplot Python Library
2.1 Setting Up and Getting Started with ggplotvideo
2.2 Plotting a Comparison of BRICS Market Economies – GDP Numbersvideo
2.3 Plotting a Comparison of BRICS Market Economies – GDP Growth Trendsvideo
2.4 Crude Prices Representation Through Plots with ggplotvideo
2.5 Customizing Representation of Crude Prices with ggplotvideo
Section 3: Programming Advanced Visualizations with Seaborn
3.1 Setting Up and Getting Started with Seaborn Python Libraryvideo
3.2 Plotting the Most Unstable Areas in the World Using Seabornvideo
3.3 Plotting the Most Unstable Areas – Advanced Customizationsvideo
3.4 Visualizing Performance of Recent Hollywood Releases in Seabornvideo
3.5 Visualizing Performance of Hollywood Releases in Seaborn Using Custom Plotsvideo
Section 4: Data Visualization Using Plotly
4.1 Setting Up and Getting Started with Plotlyvideo
4.2 Plotting the Data for Apple iPhone Launches with Plotlyvideo
4.3 Plotting the Data for Apple iPhone Launches – Customizationsvideo
4.4 Various Plots Showing Performance of Game Consoles Salesvideo
4.5 Performance of Game Consoles Sales – Building Online Dashboardsvideo
CommunityBlogPartners
© Copyright 2019 GO1 - All Rights Reserved