- If you want to work in exciting analytics and data visualization project, then this is the starting point for you.
- Data is the currency of now and potential to use it the right way, at the right time for the right reason gives you possibility beyond imagination.
- Data visualization is a vast topic and consist of many sub-parts which are a subject in itself, we in our course have tried to paint a clear picture of what you need to know and what people will be looking of you in a visualization project.
- UX in Data visualization is key in modern times to meet the expectation of your user, this course will highlight what are the benefits of using a good UX and how to do it.
- This course is structured to provide all the key aspect of Data visualization in most simple and clear fashion.So you can start the journey in Data visualization world.
Who this course is for:
- Beginner Python developers curious about Data Science
Goals
- Matplotlib Introduction
- PyPlot, Bar, Pie, Histogram, Scatter & 3D Plot
- Multiple Plots in a Graph
- Seaborn Plotting Functions
- Plotting with Categorical Data
- Multi-Plot Grids
- Plot Aesthetics
- What is Data Science
- What is Machine Learning
- Data Visualization using Pandas
Prerequisites
- Just some high school mathematics level.
Instructors
No student enrolled.
Requirements
- Just some high school mathematics level.
Features
- Develop simple to advanced data visualizations in Matplotlib
- Use the pyplot API to quickly develop and deploy different plots
- Use object-oriented APIs for maximum flexibility with the customization of figures
- Develop interactive plots with animation and widgets
- Use maps for geographical plotting
- Enrich your visualizations using embedded texts and mathematical expressions
- Embed Matplotlib plots into other GUIs used for developing applications
- Use toolkits such as axisartist, axes_grid1, and cartopy to extend the base functionality of Matplotlib
