By Edwin Bomela, Big Data Engineering

Create Smart Maps In Python and Leaflet

Language: English
All Levels

Course description

Welcome to the Smart Map In Python Tutorial Series. In this tutorial series we'll be building a python GIS application from scratch using a variety of open source technologies. The purpose of this tutorial 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. The operating system that we will be working on is Ubuntu Linux 16.04.

Related Skills

Course overview - 27

  • Introduction

  • Installing PostgreSQL and PostGIS Part1

  • Installing PostgreSQL and PostGIS Part2

  • Installing Python Django in a Virtual Environment

  • Installing and Configuring Atom IDE Part1

  • Installing and Configuring Atom IDE Part2

  • Creating a GeoDjango Application Skeleton

  • Adding a Spatial Database to our Django Backend

  • Updating our django models file

  • Registering our model in the admin file Part1

  • Registering our model in the admin file Part2

  • Registering our model in the admin file Part3

  • Updating the settings file

  • Creating the layout page Part 1

  • Creating the layout page Part 2

  • Creating the layout page Part 3

  • Creating the index page Part 1

  • Creating the index page Part 2

  • Updating the index page

  • Creating datasets

  • Displaying data on the map Part 1

  • Displaying data on the map Part 2

  • Creating a legend

  • Creating the barchart legend

  • Creating the barchart Part 1

  • Creating the barchart Part 2

  • Project Source Code

Learners who have already enrolled in this course

Meet your instructor

Edwin  Bomela
Edwin BomelaBig Data Engineering
Big Data Engineering and Consulting, 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. Currently 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.