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Interactive Dashboards and Data Apps with Plotly and Dash

You're reading from   Interactive Dashboards and Data Apps with Plotly and Dash Harness the power of a fully fledged frontend web framework in Python – no JavaScript required

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Product type Paperback
Published in May 2021
Publisher Packt
ISBN-13 9781800568914
Length 364 pages
Edition 1st Edition
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Author (1):
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Elias Dabbas Elias Dabbas
Author Profile Icon Elias Dabbas
Elias Dabbas
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Table of Contents (18) Chapters Close

Preface 1. Section 1: Building a Dash App
2. Chapter 1: Overview of the Dash Ecosystem FREE CHAPTER 3. Chapter 2: Exploring the Structure of a Dash App 4. Chapter 3: Working with Plotly's Figure Objects 5. Chapter 4: Data Manipulation and Preparation, Paving the Way to Plotly Express 6. Section 2: Adding Functionality to Your App with Real Data
7. Chapter 5: Interactively Comparing Values with Bar Charts and Dropdown Menus 8. Chapter 6: Exploring Variables with Scatter Plots and Filtering Subsets with Sliders 9. Chapter 7: Exploring Map Plots and Enriching Your Dashboards with Markdown 10. Chapter 8: Calculating the Frequency of Your Data with Histograms and Building Interactive Tables 11. Section 3: Taking Your App to the Next Level
12. Chapter 9: Letting Your Data Speak for Itself with Machine Learning 13. Chapter 10: Turbo-charge Your Apps with Advanced Callbacks 14. Chapter 11: URLs and Multi-Page Apps 15. Chapter 12: Deploying Your App 16. Chapter 13: Next Steps 17. Other Books You May Enjoy

Setting up your environment

With the fast pace of change in all the packages used in the book, you will most likely come across some differences in functionality, so in order to reproduce the exact outcomes described in the book, you can clone the book's repository, install the packages used (in the specified versions), and use the included dataset. From the command line, go to a folder in which you want to build the project and do the following:

  1. Create a Python virtual environment in a folder called dash_project (or any other name you want). This will also create a new folder with the name you chose:
    python3 –m venv dash_project
  2. Activate the virtual environment.

    On Unix or macOS, run this:

    source dash_project/bin/activate

    On Windows, run this:

    dash_project\Scripts\activate.bat
  3. Go to the created folder:
    cd dash_project
  4. Clone the book's GitHub repository:
    git clone   https://github.com/PacktPublishing/Interactive-Dashboards-and-Data-Apps-with-Plotly-and-Dash 
  5. You should now have a file containing the required packages and their versions called requirements.txt. You can install those packages by going to the repository's folder and running the install command as follows:
    cd Interactive-Dashboards-and-Data-Apps-with-Plotly-and-Dash/
    pip install -r requirements.txt

You should find a copy of the dataset in the data folder, which was downloaded from this link: https://datacatalog.worldbank.org/dataset/poverty-and-equity-database. You can get the latest version if you want, but as with packages, if you want to get the same results, it's better to work with the provided dataset.

In order for Plotly figures and apps to be displayed in JupyterLab, you will need to install Node.js, which can be install from https://nodejs.org.

You will also need to install the JupyterLab Plotly extension, which can be done by running the following from the command line in your virtual environment:

jupyter labextension install jupyterlab-plotly@4.14.1

Note that the version number at the end should correspond to the version of Plotly that you are running. You can replace the preceding version numbers if you want to upgrade (making sure to upgrade the Plotly Python package as well).

Once you have run the preceding code, you should have everything you need to follow along. You will see that each chapter of this book builds on the previous one: we will be building an app that adds more and more functionality and complexity as we go through the chapters.

The main objective is to put you in a practical setting as much as possible. In general, it is straightforward to create any standalone Dash component, but it gets more challenging when you already have a few components in a running app. This becomes clear when you have to decide how to change the layout to accommodate new changes and how to refactor code, focusing on the details without losing sight of the big picture.

Now that the environment has been established, let's get an overview of Dash.

You have been reading a chapter from
Interactive Dashboards and Data Apps with Plotly and Dash
Published in: May 2021
Publisher: Packt
ISBN-13: 9781800568914
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