About This Course
Data Visualization in Python
Python offers several data visualization libraries, such as Matplotlib, Seaborn, Plotly, GGPlot2(Grammer of Graphics), and many other data visualization packages. These packages provide the techniques needed for creating informative, customized, and eye-catching plots that present data in a visual way that attracts the attention of viewers.
Learning Objectives
This course is an introduction to data visualization and will apply three main frameworks for data visualization in Python. The three primary libraries that we will use include Matplotlib, Seaborn, Plotly, and GGPlot2(Grammer of Graphics). By the end of the course, students will be able to
Create summary statistics for a single group and different groups
Generate graphical display of data: histograms, QQ-plot, box plots, bar plots, empirical cumulative distribution, dot charts, and pie charts.
Material Includes
- A laptop, stable internet access, installation of Zoom for teleconferencing, and Google Collaboratory or Python Anaconda Navigator or any Python programming interface on your computer.
Requirements
- Installation of Python Anaconda or access to Google Collaboratory on your computer
Target Audience
- Professionals who would like to learn how to use the Python programming language to learn how to explore any dataset.
Curriculum
4h
Load external packages into Google Collaboratory
Load a dataset into Google Collaboratory
Identify the different data types from data
Create basic summary statistics of continuous variables from data
Generate histograms, QQ-plots and empirical cumulative distribution from data
Generate bar graphs from data
Generate box plots from data
Generate pie charts from data
Your Instructors
$29.99$199.00
Material Includes
- A laptop, stable internet access, installation of Zoom for teleconferencing, and Google Collaboratory or Python Anaconda Navigator or any Python programming interface on your computer.
-80%
Data Visualization using R programming Language
$39.99$199.99
