About the course
Use high-level Python APIs to visualize statistical data.
As organizations collect huge amounts of data, it has become increasingly important for data analysts and scientists to explore and visualize this data before performing further analysis. Seaborn is a visualization library especially built for statistical analysis; its higher-level APIs allow you to visualize relationships in your data. Seaborn is an integral part of the PyData stack and is closely integrated with other Python libraries such as Pandas and NumPy.
Here is what this course covers:
- Histograms and Kernel Density Estimation: Use high-level APIs to display regression plots and KDE curves
- Univariate and bi-variate relationships: Find linear relationships between multiple variables
- Pairwise relationships: Use FacetGrid and PairGrid to find relationships between pairs of features
- Themes, styles, and color palettes: Customize your visualizations using different colors, themes and figure styles
This course is built around hands-on demos, built to explicitly explain concepts underpinning each topic. Real-world datasets are used where possible.
All the code files are placed at https://github.com/PacktPublishing/Learn-By-Example-Seaborn
Style and Approach
This course will teach you to visualize statistical data using Python via real-life examples.
What You Will Learn
- Work with and display histograms and Kernel Density Estimation plots
- Visualize univariate and bivariate relationships in data
- Work with categorical and multi-panel data
- Customize color palettes for plots
Loonycorn is Janani Ravi and Vitthal Srinivasan. Between them, they have studied at Stanford, been admitted to IIM Ahmedabad, and have spent years working in tech, in the Bay Area, New York, Singapore and Bangalore. Janani spent 7 years at Google (New York, Singapore); Studied at Stanford and also worked at Flipkart and Microsoft. Vitthal also worked at Google (Singapore) and studied at Stanford; Flipkart, Credit Suisse and INSEAD too. They think they might have hit upon a neat way of teaching complicated tech courses in a funny, practical, engaging way, which is why they are so excited to be here. They hope you will try their offerings, and you'll like them.