Data Visualization with Python and
Matplotlib Online Course
2KO offers an online
computer course called Data Visualization with Python and Matplotlib
which is for students wishing to use Python for data visualization,
which is currently a red-hot skill in the job market.
2KO International runs computer courses across the African continent, and is a top provider of internationally certified online IT training from the comfort
of home or work.
More and more people are
realising the vast benefits and uses of analysing big data. However,
the majority of people lack the skills and the time needed to
understand this data in its original form. That's where data
visualisation comes in; creating easy to read, simple to understand
graphs, charts and other visual representations of data.
Python 3 and Matplotlib are
the most easily accessible and efficient to use programs to
do just this.
Visualise multiple forms of 2D and 3D graphs; line
graphs, scatter plots, bar charts, etc.
and organise data from various sources for visualisation
Create and customise live graphs
finesse and style to make your graphs visually
Data Visualisation made Easy
With over 58 lectures and 6 hours of content, this course covers
almost every major chart that Matplotlib is capable of providing.
Intended for students who already have a basic understanding of
Python, you'll take a step-by-step approach to create line graphs,
scatter plots, stack plots, pie charts, bar charts, 3D lines, 3D
wire frames, 3D bar charts, 3D scatter plots, geographic maps, live
updating graphs, and virtually anything else you can think of!
Starting with basic functions like labels, titles, window buttons
and legends, you'll then move onto each of the most popular types of
graph, covering how to import data from both a CSV and NumPy. You'll
then move on to more advanced features like customised spines,
styles, annotations, averages and indicators, geographical plotting
with Basemap and advanced wireframes.
This course has been specially designed for students who want to
learn a variety of ways to visually display python data. On
completion of this course, you will not only have gained a deep
understanding of the options available for visualising data, but
you'll have the know-how to create well presented, visually
appealing graphs too.
Python is a general purpose programming language which a focus on
readability and concise code, making it a great language for new
coders to learn. Learning Python gives a solid foundation for
learning more advanced coding languages, and allows for a wide
variety of applications.
Matplotlib is a plotting library that works with the Python
programming language and its numerical mathematics extension 'NumPy'.
It allows the user to embed plots into applications using various
general purpose toolkits (essentially, it's what turns the data into
IDLE is an Integrated Development Environment for Python; i.e where
you turn the data into the graph. Although you can use any other IDE
to do so, we recommend the use of IDLE for this particular course.
Getting Matplotlib And Setting Up
Different types of basic Matplotlib charts
Section Introduction (1:18)
Labels, titles and window buttons
Loading data from a CSV
Loading data with NumPy
Basic Customization Options
Source for our Data* (9:59)
Parsing stock prices from the internet*
Plotting basic stock data*
Modifying labels and adding a grid*
Converting from unix time and adjusting subplots*
remove, and customize spines*
Candlestick OHLC charts*
Styles with Matplotlib*
Creating our own Style* (9:27)
Adding and placing text*
Annotating a specific plot*
Dynamic annotation of last price*
Section Conclusion (1:44)
Advanced Customization Options
Subplot2grid * (8:05)
Incorporating changes to candlestick graph*
Creating moving averages with our data*
Adding a High minus Low indicator to graph*
Customizing the dates that show*
and Tick customizations*
Geographical Plotting with Basemap
Downloading and installing Basemap
Customizing the projection
customization, like colors, fills, and forms of boundaries