Python for Data Visualization
4.0 /5- Offered byLinkedin Learning
Python for Data Visualization at Linkedin Learning Overview
Duration | 2 hours |
Mode of learning | Online |
Difficulty level | Intermediate |
Credential | Certificate |
Python for Data Visualization at Linkedin Learning Highlights
- Earn a certificate of completion from LinkedIn Learning
Python for Data Visualization at Linkedin Learning Course details
- Data Visualization
- Python (Programming Language)
- Python is a popular, easy-to-use programming language that offers a number of libraries specifically built for data visualization
- In this course from the experts at Madecraft, you can learn how to build accurate, engaging, and easy-to-generate charts and graphs using Python
- Explore the pandas and Matplotlib libraries, and then discover how to load and clean data sets and create simple and advanced plots, including heatmaps, histograms, and subplots
- Instructor Michael Galarnyk provides all the instruction you need to create professional data visualizations through programming
Python for Data Visualization at Linkedin Learning Curriculum
Introduction
Effectively present data with Python
What you should know before you start
Using the exercise files
1. Data Visualization Tools
Value of data visualization
Why use a programming language?
Overview of Jupyter Notebooks
2. pandas
Introduction to pandas
Create sample data
Load sample data
Basic operations
Slicing
Filtering
Renaming and deleting columns
Aggregate functions
Identifying missing data
Removing or filling in missing data
Convert pandas DataFrames to NumPy arrays or dictionaries
Export pandas DataFrames to CSV and Excel files
3. Matplotlib
Basics of Matplotlib
Setting marker type and colors
MATLAB-style vs. object syntax
Setting titles, labels, and limits
Grids
Legends
Saving plots to files
Matplotlib wrappers (pandas and Seaborn)
4. Advanced Plotting
Heatmaps
Histograms
Subplots
Conclusion
Next steps
Other courses offered by Linkedin Learning
Student Forum
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