Python - Data Visualisation using Python and Bokeh library

About

This coding example is part of a Udemy Python course using Python to visualise data for modern web browsers.

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Technologies

Languages

• Python3
  • Used to create the main application functionality

Libraries / Packages / Modules

• Bokeh

  • Bokeh is a Python library for creating interactive visualisations for modern web browsers.

• Pandas

  • Used to read csv data ito DataFrames for plotting graphs using Bokeh

• openpyxl

  • A Python library to read/write Excel 2010 xlsx/xlsm files

• xlrd

  • A Python library Used to load legacy Excel .xls files

Tools

• VS Code
  • Code Editor

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Deployment

The website was developed using VS Code & Git pushed to GitHub, which hosts the repository. I made the following steps to deploy the site:

Cloning Interactive_Data_Visulaisation

Prerequisites

Ensure the following are installed locally on your computer:

• Python 3.6 or higher
• PIP3 Python package installer
• Git Version Control

Cloning the GitHub repository

• navigate to simonjvardy/python-image-face-detection GitHub repository.
• Click the Code button
• Copy the clone url in the dropdown menu
• Using your favourite IDE open up your preferred terminal.
• Navigate to your desired file location.

Copy the following code and input it into your terminal to clone Sportswear-Online:

git clone https://github.com/simonjvardy/Interactive_Data_Visualisation.git

Creation of a Python Virtual Environment

Note: The process may be different depending upon your own OS - please follow this Python help guide to understand how to create a virtual environment.

Run the application locally

• To run the face detection application, enter the following command into the terminal window:

python3

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Acknowledgements

• Udemy: The Python Mega Course - Build 10 Real World Applications Credit: Ardit Sulce