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Data Visualization with Python


Data Visualization with Python


Advanced SQL
Analysing Data with Excel
Critical Thinking
Data Modelling with M and Power Query
Data Visualization with R
Excel Dashboards and Power Pivot
GIS ESSENTIALS – “Getting Spatially Enabled”
Introduction to Statistics
Machine Learning with Python
Machine Learning with R
Microsoft Power BI Boot Camp
Microsoft Power BI Desktop Advanced Course
Microsoft Power Query
Microsoft PowerBI Dashboard User Course
MySQL Administration
PostgreSQL Administration
PostgreSQL for Business Intelligence and Mass-data-analysis
Problem Solving and Decision Making
Problem-Solving SAQA US242817
Python Dashboards with plotly Dash
Python Pandas and Jupyter ETL and Data wrangling
Python Regression
Python Statistical Modelling
Python Statistics
Python Web Apps with Flask MVC Framework
R, Into the Tidyverse (Data Wrangling and ETL)
Regression with R
Statistics with R


Mark Badham


To interpret your data and draw insights, you need to be able to visualise it. Python, one of the most popular and powerful coding languages around, has impressive libraries and resources for displaying your data. You'll be able to take your data and use it to tell insightful stories with compelling visualisations to convince stakeholders and build trust.

In this course you will learn to:

  • Create data visualisations
  • Use various graph types
  • Apply skills to real world scenarios
  • Improve data accessibility and understandability
  • Create robust summaries

Delivery Methods

Leading Training is focusing on providing virtual training courses for the foreseeable future and will only consider in-person and classroom training on request, with a required minimum group size of six delegates. We remain committed to offering training that is fast, focused and effective.

Delivery Method Duration Price (excl. VAT)
Classroom 1 Days ZAR 5,500.00 Get a Quote
Live Virtual Training 1 Days ZAR 4,500.00 Get a Quote

Discounts Available

Save up to 10% by booking and paying 10 business days before the course.


Download Brochure

Information may change without notice.


  • Data scientists
  • Programmers
  • Business analysts 
  • Engineers
  • Scientists


Leading Training's Python Course or equivalent knowledge


Course Outline / Curriculum

Visualising Data

  • Instantiating defaults 
  • Changing colors and line widths 
  • Setting limits 
  • Setting ticks 
  • Setting tick labels 
  • Moving spines 
  • Adding a legend 
  • Annotate some points 
  • Putting it all together 
  • Figures, Subplots, Axes and Ticks 

Graph Types 

  • Scatter Plots 
  • Bar Plots 
  • Contour Plots 
  • Imshow 
  • Pie Charts 
  • Quiver Plots 
  • Multi Plots 
  • Polar Axis 
  • Histogram 
  • 3D Plots 

 Data visualization in practice 

  • Case study: new insights on poverty 
  • Hans Rosling’s quiz
  • Scatterplots
  • Faceting
  • Fixed scales for better comparisons
  • Time series plots
  • Labels instead of legends
  • Data transformations
  •  Log transformation
  • Which base?
  • Transform the values or the scale?
  • Visualizing multimodal distributions
  •  Comparing multiple distributions with boxplots and ridge plots
  •  Boxplots
  •  Ridge plots
  • Example: 1970 versus 2010 income distributions
  •  Accessing computed variables
  • Weighted densities
  • The ecological fallacy and importance of showing the data
  •  Logistic

Data visualization principles 

  •  Encoding data using visual cues
  •  Know when to include 
  •  Do not distort quantities
  •  Order categories by a meaningful value
  •  Show the data
  •  Ease comparisons
  • Use common axes
  • Align plots vertically to see horizontal changes and horizontally to see
  • vertical changes
  • Consider transformations
  •  Visual cues to be compared should be adjacent
  • Use color
  •  Think of the color blind
  •  Plots for two variables
  • Slope charts
  • Bland-Altman plot
  •  Encoding a third variable
  • Avoid pseudo-three-dimensional plots
  • Avoid too many significant digits
  • Know your audience
  • Exercises
  • Case study: vaccines and infectious diseases
  • Exercises

Robust summaries 

  •  Outliers
  •  Median
  •  The inter quartile range (IQR)
  •  Tukey’s definition of an outlier
  •  Median absolute deviation
  •  Exercises
  •  Case study: self-reported student heights

Schedule Dates and Booking

There are currently no scheduled dates.

Please note that this course needs a minimum of 6 delegates to schedule a course. You can choose to be added to the waiting list by clicking the button below, and we will contact you when we have enough delegates interested. Should we not get enough delegates, we will refund or credit your paid booking.

Add me to the waiting list

Should you need this course urgently, the following options are available:

  1. Pay for 6 delegates (whether you have them or not) and we will schedule the course as soon as possible.
  2. If you have fewer delegates and cannot pay for 6, we can negotiate a shortened course where some of the time will be spent in blended learning - watching videos and doing tutorials and exercises with some contact time with the trainer. We would want to discuss what your core needs are so that we cover those aspects. You need to have paid for 3 delegates at least.
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