Python for Data Visualization: The Complete Masterclass

4.8 Rating

(9 Reviews)

17 Students

Last updated: June 28, 2024
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Language: English
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Flexible Schedule

Dive into the world of data visualization with “Python for Data Visualization: The Complete Masterclass.” This course is designed to transform how you perceive and present data. Whether you’re looking to create stunning line plots, dynamic histograms, or sophisticated scatter plots, this masterclass has got you covered. Using powerful tools like matplotlib, seaborn, Plotly, and Cufflinks, you’ll unlock the secrets to making your data not only comprehensible but also visually appealing. “Python for Data Visualization: The Complete Masterclass” ensures you gain a comprehensive understanding of how to visualize data in a way that makes a significant impact. By the end of this course, your ability to convey complex information through simple, beautiful visualizations will be second to none. Enrol now in “Python for Data Visualization: The Complete Masterclass” and elevate your data presentation skills to professional heights.

Learning Outcomes

  1. Master the setup and installation of data visualization tools.
  2. Create and customize line plots using matplotlib.
  3. Design and interpret histograms and bar charts.
  4. Develop complex visualizations with stack plots and stem plots.
  5. Visualize time series data effectively.
  6. Utilize seaborn and Plotly for advanced data visualization techniques.

Why buy this Python for Data Visualization: The Complete Masterclass course?

  1. Unlimited access to the course for forever
  2. Digital Certificate, Transcript, student ID all included in the price
  3. Absolutely no hidden fees
  4. Directly receive CPD accredited qualifications after course completion
  5. Receive one to one assistance on every weekday from professionals
  6. Immediately receive the PDF certificate after passing
  7. Receive the original copies of your certificate and transcript on the next working day
  8. Easily learn the skills and knowledge from the comfort of your home

Certification

After studying the course materials of the Python for Data Visualization: The Complete Masterclass there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99. Original Hard Copy certificates need to be ordered at an additional cost of £8.

Who is this Python for Data Visualization: The Complete Masterclass course for?

  • Data analysts looking to enhance their visualization skills.
  • Python programmers wanting to specialize in data visualization.
  • Students pursuing data science or related fields.
  • Researchers needing to present data compellingly.
  • Professionals aiming to improve their data presentation for reports.
  • Enthusiasts eager to learn about data visualization tools and techniques.

Prerequisites

This Python for Data Visualization: The Complete Masterclass does not require you to have any prior qualifications or experience. You can just enrol and start learning. This Python for Data Visualization: The Complete Masterclass was made by professionals and it is compatible with all PC’s, Mac’s, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection.

Career path

  • Data Analyst: £25,000 to £45,000 per year
  • Data Scientist: £40,000 to £70,000 per year
  • Business Intelligence Analyst: £30,000 to £55,000 per year
  • Machine Learning Engineer: £45,000 to £75,000 per year
  • Quantitative Analyst: £50,000 to £90,000 per year
  • Data Visualization Specialist: £35,000 to £60,000 per year

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
Python for Data Visualization: The Complete Masterclass
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This course includes:

  • level Skill Level
  • course_duration Duration
    3 hours, 44 minutes
  • studentsStudents
    17 Students