Course: Python with Altair

$139.00
$168.19 incl. vat

duration: 7 hours |

Language: English (US) |

access duration: 90 days |

Details

This course will get you familiar with the building blocks of Altair visualizations and some of the important chart settings. You'll start off by learning about the basic data structures that can form the basis of Altair visualizations, including JSON data and Pandas DataFrames in both wide-form and long-form. Next, you’ll get familiar with a wide variety of graphs to, for example, visualize a distribution of numeric values using box plots and violin charts. You will get to explore a variety of aggregate operations that are available in Altair in order to calculate a sum, mean, median, and so on. Finally, you’ll learn to work with specialized graphs such as a heatmap to analyze the numbers associated with a combination of two categorical variables.

Result

After completing this course, you can use large variety of graphs in Altair to present and analyze your data.

Prerequisites

No prerequisites

Target audience

Software Developer, Data analist

Content

Python with Altair

7 hours

Python with Altair: An Introduction to Altair

  • This course will get you familiar with the building blocks of

  • Altair visualizations and some of the important chart settings. You
  • will touch upon some of the fundamentals of plotting graphs in
  • Altair. You'll start off by learning about the basic data
  • structures that can form the basis of Altair visualizations,
  • including JSON data and Pandas DataFrames in both wide-form and
  • long-form. You'll then move on to plotting one of the simpler
  • graphs, histograms, to visualize the distribution of values for a
  • quantitative field in your dataset. While doing so, you'll get to
  • explore the different ways in which Altair graphs can be customized
  • including augmenting your chart with text, layering histograms to
  • view two distributions together, and making histograms
  • interactive.

Python with Altair: Plotting Fundamental Graphs

  • This course will introduce you to a breadth of charts available

  • in Altair and how you can use them to get an all-round
  • understanding of your data. The focus is to get you familiar with
  • the wide variety of graphs that are available. You'll begin by
  • visualizing a distribution of numeric values using box plots and
  • violin charts, each of which has its own strengths and limitations
  • when analyzing distributions. You'll then move on to bar charts to
  • analyze numbers associated with categories in your data. While
  • doing so, you will get to explore a variety of aggregate operations
  • that are available in Altair in order to calculate a sum, mean,
  • median, and so on. You'll then use line charts to visualize the
  • changes in a particular value over a period of time and also its
  • related visual - the area chart. Finally, you'll produce scatter
  • plots to visualize the relationship between a pair of fields in
  • your data. Throughout this course, you'll delve into a number of
  • customizations which are available in Altair for each of the graphs
  • which you plot.

Python with Altair: Working with Specialized Graphs

  • This course introduces you to the use of Altair visualizations

  • which can convey very detailed information for specialized
  • datasets. You will cover some of the graphs that can be used to
  • convey the information in very specific kinds of datasets, while
  • also giving you some hands-on experience with advanced chart
  • configurations. You'll begin by plotting information on a map, both
  • to mark locations of places as well as to convey numerical
  • information about regions. You'll then build a heatmap to analyze
  • the numbers associated with a combination of two categorical
  • variables. Next, you'll implement candlestick charts to visualize
  • stock price movements, dot plots to analyze the range of movement
  • for some values, and Gantt charts to view a project plan. Finally,
  • you'll explore the use of window functions to analyze the top K
  • elements in each category of your dataset.

Course options

We offer several optional training products to enhance your learning experience. If you are planning to use our training course in preperation for an official exam then whe highly recommend using these optional training products to ensure an optimal learning experience. Sometimes there is only a practice exam or/and practice lab available.

Optional practice exam (trial exam)

To supplement this training course you may add a special practice exam. This practice exam comprises a number of trial exams which are very similar to the real exam, both in terms of form and content. This is the ultimate way to test whether you are ready for the exam. 

Optional practice lab

To supplement this training course you may add a special practice lab. You perform the tasks on real hardware and/or software applicable to your Lab. The labs are fully hosted in our cloud. The only thing you need to use our practice labs is a web browser. In the LiveLab environment you will find exercises which you can start immediatelyThe lab enviromentconsist of complete networks containing for example, clients, servers,etc. This is the ultimate way to gain extensive hands-on experience. 

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