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 library.
Each section of the course contains practical examples and tasks for self-completion.
Knowledge requirements: course completion 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 Impact libraries is being studied.jl and Interpolations.jl (linear interpolation and interpolation by B-splines of various degrees).
Data visualization using the Makie library.
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 the preservation of graphs.