Course description

Welcome to Web Scraping and Mapping Dam Levels in Python. In this course we'll be building a python GIS application from scratch using a variety of open source technologies. The purpose of this course and many more to follow, is to take geospatial analytics and convert it into a functional application.

We will be powering our application with a PostgreSQL and PostGIS database. In the front-end we'll use Bootstrap, JavaScript and Ajax. On the server side we'll be using Python 3 Django combined with use of scientific libraries like pandas, for our data transformation and conversion operations, and BeautifulSoup for web scraping and data extraction. The operating system that we will be working on is Ubuntu Linux 16.04.

At a later stage we'll be using time series forecasting to predict the consumption values for the following month using our historical data.

Course curriculum

  • 2

    Building a Spatial Database

    • Installing PostgreSQL and PostGIS

    • Creating the Database

  • 3

    Creating a Django Python Application

    • Installing Django in a Python virtual environment

    • Installing the ATOM IDE

  • 4

    Creating a Django Python Application

    • Creating the Django Base Project

    • Adding the Database Configuration to settings.py file

    • Creating a Model in models.py

  • 5

    Web Scraping and ETL

    • Extracting Data From the Web

    • Cleaning and Transforming the Data Part 1

    • Cleaning and Transforming the Data Part 2

    • Loading the Data into the Model

  • 6

    Building the Django Front-End

    • Adding the Web Map Tile Service Link in settings.py

    • Reading from the Model and Creating a GeoJSON Dataset

    • Adding Template Files the HTML files.

    • Adding a Layout and the Base Map

  • 7

    Data Visualization

    • Plotting Circle Markers

    • Creating a Sliding Sidebar

    • Creating a Doughnut Chart

    • Creating a Multi-Bar Bar Chart

    • Creating a KPI

Meet your instructor!

Edwin Bomela 
Data Engineer 

Edwin Bomela is a Big Data Engineer and Consultant, involved in multiple projects ranging from Business Intelligence, Software Engineering, IoT and Big data analytics. Expertise are in building data processing pipelines in the Hadoop and Cloud ecosystems and software development. 

He is currently a consulting at one of the top business intelligence consultancies helping clients build data warehouses, data lakes, cloud data processing pipelines and machine learning pipelines. 

The technologies he uses to accomplish client requirements range from Hadoop, Amazon S3, Python, Django, Apache Spark, MSBI, Microsoft Azure, SQL Server Data Tools, Talend and Elastic MapReduce.

Private Label Rights (PLR)

This course is available with Private Label Rights (PLR). 

When you buy a course with private label rights on Uthena, the author of the course gives you permission to download the course and sell it as your own on your website according to the terms of the PLR license included.

If you would like to know more about the license terms, please visit this page.

After purchasing, you will have access to the course on Uthena and you will receive the PLR license with a download link and a special bonus.


See a sample of the PLR license.

Bundle including this course!

You can buy Private Label Rights (PLR) for this course and others, click here.