Python for Data Visualization: The Complete Masterclass

Python for Data Visualization The Complete Masterclass


Empower your career journey with our in-demand course: Python for Data Visualization: The Complete Masterclass

Boost your proficiency and propel your career forward with our meticulously crafted course, designed to be your ultimate guide to professional development. Our super-accessible modules break down complex topics into bite-sized, easy-to-understand lessons, filling your knowledge gaps and equipping you with real-world, practical skills.

Seeking career advancement and application of your skills? You’ve found the right place. This Python for Data Visualization: The Complete Masterclass is your exclusive passport to unlocking your full potential.

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This sought-after course is your key to a successful and lucrative career. Don’t miss out on this transformative opportunity. Enroll now and take your professional life to the next level!

Course design

The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace.

You are taught through a combination of

Exam & Retakes

It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable.


Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery).

Course Curriculum

Setup & Installation
Installing the Anaconda Navigator 00:07:00
Installing Matplotlib, seaborn & cufflinks 00:03:00
Reading data from a csv file with pandas 00:03:00
Explaining Matplotlib libraries apart 00:07:00
Plotting Line Plots with matplotlib
Changing the axis scales 00:06:00
Label Styling 00:04:00
Adding a legend 00:04:00
Changing colors, linestyles, linewidth and markers 00:09:00
Adding a grid to the chart 00:04:00
Filling only a specific area 00:07:00
Filling area on line plots and filling only specific area 00:04:00
Changing fill color of different areas (negative vs positive for example) 00:03:00
Plotting Histograms & Bar Charts with matplotlib
Changing edge color and adding shadow on the edge 00:04:00
Adding legends, titles, location and rotating pie chart 00:06:00
Histograms vs Bar charts (Part 1) 00:03:00
Histograms vs Bar charts (Part 2) 00:02:00
Changing edge colour of the histogram 00:03:00
Changing the axis scale to log scale 00:07:00
Adding median to histogram 00:04:00
Advanced Histograms and Patches (Part 1) 00:04:00
Advanced Histograms and Patches (Part 2) 00:05:00
Overlaying bar plots on top of each other (Part 1) 00:04:00
Overlaying bar plots on top of each other (Part 2) 00:01:00
Creating Box and Whisker Plots 00:11:00
Plotting Stack Plots & Stem Plots
Plotting a basic stack plot 00:13:00
Plotting a stem plot 00:05:00
Plotting a stack plot od data with constant total 00:04:00
Plotting Scatter Plots with matplotlib
Plotting a basic scatter plot 00:06:00
Changing the size of the dots 00:06:00
Changing colors of markers 00:05:00
Adding edges to dots 00:04:00
Time Series Data Visualization with matplotlib
Using the Python datetime module 00:03:00
Connecting data points by line 00:04:00
Converting string dates using the .to_datetime() pandas method 00:05:00
Plotting live data using FuncAnimation in matplotlib 00:04:00
Creating multiple subplots
Setting up the number of rows and columns 00:04:00
Plotting multiple plots in one figure 00:02:00
Getting separate figures 00:03:00
Saving figures to your computer 00:03:00
Plotting charts using seaborn
Introduction to seaborn 00:02:00
Working on hue, style and size in seaborn 00:05:00
Subplots using seaborn 00:05:00
Line plots 00:02:00
Cat plots 00:03:00
Jointplot, pair plot and regression plot 00:02:00
Controlling Plotted Figure Aesthetics 00:03:00
Plotly and Cufflinks
Installation and Setup 00:02:00
Line, Scatter, Bar, box and area plot 00:07:00
3D plots, spread plot and hist plot, bubble plot, and heatmap 00:07:00

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