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Learn Python by Building Data Science Applications

You're reading from  Learn Python by Building Data Science Applications

Product type Book
Published in Aug 2019
Publisher Packt
ISBN-13 9781789535365
Pages 482 pages
Edition 1st Edition
Languages
Authors (2):
Philipp Kats Philipp Kats
Profile icon Philipp Kats
David Katz David Katz
Profile icon David Katz
View More author details

Table of Contents (26) Chapters

Preface Section 1: Getting Started with Python
Preparing the Workspace First Steps in Coding - Variables and Data Types Functions Data Structures Loops and Other Compound Statements First Script – Geocoding with Web APIs Scraping Data from the Web with Beautiful Soup 4 Simulation with Classes and Inheritance Shell, Git, Conda, and More – at Your Command Section 2: Hands-On with Data
Python for Data Applications Data Cleaning and Manipulation Data Exploration and Visualization Training a Machine Learning Model Improving Your Model – Pipelines and Experiments Section 3: Moving to Production
Packaging and Testing with Poetry and PyTest Data Pipelines with Luigi Let's Build a Dashboard Serving Models with a RESTful API Serverless API Using Chalice Best Practices and Python Performance Assessments Other Books You May Enjoy

Building a dashboard – three types of dashboard

In Chapter 12, Data Exploration and Visualization, we explored a dataset by visualizing different features, using two packagesmatplotlib and altair. The differences between those visualizations and a dashboard are twofold:

  • The audience for the dashboard is meant to be wide, so it should be easily accessible via an internet browser. Visualizations are often made for self-consumption.
  • Dashboards are meant to be frequently updated and, to some extent, interactive. Visualizations are often done on-the-spot, are static, and show only specific aspects of the data.

To a large extent, dashboards are full-blown projects requiring regular improvement and maintenance! However, as the demand for this kind of product is large, and the task is easily generalizable, there are plenty of solutions, tools, and services at our disposal...

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