Python for Data Visualization: The Complete Masterclass
Python for Data Visualization: The Complete Masterclass
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Overview
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.
Enroll today and enjoy:
- 100% online flexibility: Learn at your own pace, from anywhere in the world.
- Expert support: We're by your side throughout your journey, providing guidance and assistance.
- Comprehensive curriculum: Dive deep into relevant topics aligned with industry standards.
- Practical focus: Apply your learnings to real-world scenarios and situations.
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
- Video lessons
- Online study materials
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.
Certification
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 | ||
Important Links
With a team of industry professionals producing and delivering our course content, you can be sure the skills and knowledge you learn are applicable to your career aspirations, whether that’s in management, administration or beyond.
