Plotly and Dash Cookbook#
This is the working 👷🏽♀️ repository for the book Plotly and Dash Cookbook, by Dialid Santiago. It will contain over 119 recipes for Interactive Visualizations and Dashboards with Plotly and Dash.
This book offers practical, hands-on recipes covering a wide range of techniques and tools, making it an essential resource for both beginners and experienced users of Plotly and Dash.
The goal is to serve as a comprehensive guide for researchers, and practitioners looking to create dynamic, interactive visualizations and dashboards.
Note
This project is under construction 🦺 existing material may change and new recipes will be released on an ongoing basis 🌱
If you like this project, please give it a star in GitHub ⭐️
About me#
I am a mathematician with over eight years of experience as a Quant in Finance. Currently, I serve as a VP Strategist in the Cross-Asset Front Office Quant team at Bank of America. Throughout my career, I have had the opportunity to work in diverse teams at institutions such as Citigroup and Barclays.
My expertise lies in developing and implementing mathematical models for pricing across the Credit, Commodities, and Rates asset classes, as well as for assessing Counterparty Credit Risk, Market Risk, and Wholesale/Retail Credit Risk.
I hold a PhD in Statistics from the University of Warwick, where I spent four enriching years researching non-linear stochastic processes. Prior to moving to the UK, I earned an MSc in Probability and Statistics and a BSc in Applied Mathematics, both in Mexico. In my free time, I create open-source projects and write about financial mathematics, programming, statistics, data visualization, and other related topics.
Connect with me via:
Contents#
Part I. Getting Started
- Introduction to Plotly and Dash in Python
- Data Processing and Transformation
- 1. Creating Series and Data Frames
- 2. Selecting and Manipulating Data Frames
- 3. Creating Columns as Functions of Existing Columns
- 4. Handling Duplicated and Missing Values
- 5. Reshaping Data with Pandas
- 6. Reading Data from Excel
- 7. Handling Large Datasets Efficiently
- 8. Loading the Plotly Express Data Sets
- 9. Exploring the Gapminder Data set
- 10. Exploring the Iris Data Set
- 11. Fetching Data from APIs
- 12. Fetching Financial Data from the Web
Part II. Using Plotly
- Simple Recipes
- Recipes for Statistical Charts
- 1. Making Histograms
- 2. Making 2D-Histograms
- 3. Making Box Plots
- 4. Making Box Plots better with Jitter
- 5. Using Violin Plots as an alternative to Box Plots
- 6. Understanding marginal plots
- 7. Making histograms better with marginals
- 8. Using marginal plots with facets
- 9. Understanding ECDF charts
- 10. Visualizing Linear Regression
- 11. Visualizing Moving Averages
- 12. Visualizing Correlation Matrices
- Intermediate Recipes