Data Analysis and Visualization
Description
In the course Data Analysis and Visualization you will learn how to work with popular tabular data formats Workspace Array and DataFrame, load and process tabular data, work with missing data in tables, perform data interpolation using polynomials and visualize data using the Makie package.
Each section of the course contains practical examples and self-study tasks.
Knowledge requirements: completion of the course Welcome to Engee.
Total course time: ~2 hours.
Course program
Working with Workspace Array
The methods of creating Workspace Array objects, loading data from CSV files, lazy slices, slices by fields, methods and interface of Workspace Array are studied.
Working with DataFrames
The creation of DataFrame objects, reading data from CSV and XLSX files, basic operations with data frames, receiving and modifying data in frames, selecting elements from a frame, sorting data and saving a data frame are studied.
Working with missing data
The processing of missing data in DataFrame format tables, detection, elimination and filling of missing values is being studied.
Interpolation of data
The interpolation of tabular data using the Impute.jl and Interpolations.jl packages is studied (linear interpolation and interpolation by B-splines of various degrees).
Data visualization using the Makie package
The main features of the Makie ecosystem are studied: the construction of two-dimensional graphs, the usage of Figure and Axis objects, the application of style to graphs, the construction of three-dimensional graphs and saving the graphs.