Survey Of Python For Gis Applications

Introduction to the python language and ecosystem for GIS professionals

What you'll learn

This course is broad rather than deep. My goal is that when finished, students have some knowledge of the tools in the python ecosystem for geospatial applications and more importantly, how they all work together. More detailed courses will be forthcoming. Some of the topics covered will be

An introduction to the language and its core principles.

An introduction to object oriented programming in python.

FInding and using third party python modules.

Working with the operating system

Working with files

Working with databases

Reading spatial data with GDAL/OGR

Visualizing data with matplotlib and other tools

Data Analysis with pandas and geopandas

Jupyter notebooks

Requirements

This course is not a beginner programming course. I assume you have some programming knowledge, i.e. what . variable is, what an expression is, what a loop is, what a function is, etc. But i do go over the basics of how all those things are implemented in python.

Description

This course covers the basics of the python language, the python language, and the core python packages for data analysis, especially of geospatial data. The goal of the course is to provide a broad introduction to the capabilities of python and how all the various packages work together. This will provide a starting point for deeper exploration on your own or in future courses.Introduction to pythonObject oriented pythonPackages and modulesUnit testsJupyter notebooksNumpyMatplotlibPandasFiona and shapelyGeopandasRasterioGeocodingPyQt

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 What is python?

Lecture 3 Why use python?

Lecture 4 What can you do with Python?

Lecture 5 What can you do with python? - Part 2 GIS

Lecture 6 About Python

Section 2: Installing Python

Lecture 7 Getting started

Lecture 8 Installing Python on MacOS

Lecture 9 Installing PyCharm on MacOS

Section 3: Getting started with Python

Lecture 10 Boolean and numeric variables

Lecture 11 Converting between variable types

Lecture 12 Strings

Lecture 13 String methods

Lecture 14 String formatting

Section 4: Operators and expressions in Python

Lecture 15 Operators Part 1

Lecture 16 Operators Part 2

Lecture 17 Expressions

Section 5: Complex data structures

Lecture 18 Lists

Lecture 19 Working with lists

Lecture 20 Tuples

Lecture 21 Sets

Lecture 22 Working with sets

Lecture 23 Dictionaries

Lecture 24 Working with dictionaries

Lecture 25 Review of complex data structures

Section 6: Program control

Lecture 26 The if statement in Python

Lecture 27 While loops in Python

Lecture 28 For loops in Python

Lecture 29 Generators

Section 7: User Input

Lecture 30 The input() function

Lecture 31 Command line arguments

Lecture 32 Working with user input

Section 8: Functions

Lecture 33 Introduction to functions

Lecture 34 Function example

Lecture 35 Function arguments

Lecture 36 Map and filter functions

Lecture 37 Lambda functions

Lecture 38 Nested functions, decorator functions, and scope

Section 9: Error Handling in Python

Lecture 39 Error Handling in Python

Lecture 40 Error handling - Part 2

Section 10: Modules

Lecture 41 What is a module?

Section 11: Objects in python

Lecture 42 What is an object?

Lecture 43 Defining a custom object class

Lecture 44 Object example

Lecture 45 String representation of an object

Lecture 46 Object inheritance

Lecture 47 Private properties and methods

Lecture 48 Principles of object oriented programing

Section 12: Python packages, virtual environments, and documentation

Lecture 49 What is a package?

Lecture 50 Working with third party packages

Lecture 51 Virtual Environments

Lecture 52 Virtual Environments - Part 2

Lecture 53 Documentation in python

Section 13: Formal testing in python

Lecture 54 The unittest module

Lecture 55 Writing a test suite for the Point class

Section 14: Working with the operating system and files

Lecture 56 The OS module

Lecture 57 The OS.path submodule

Lecture 58 Reading and writing plain text files

Lecture 59 Reading and writing plain text files - Part 2

Lecture 60 Creating a word count application

Lecture 61 Reading and writing CSV files

Lecture 62 Reading and writing CSV files - Part 2

Lecture 63 Word Count Application - Part 2

Lecture 64 Working with JSON data

Lecture 65 Working with JSON data - Part 2

Lecture 66 Word Count Application - Part 3

Lecture 67 Working with shape files

Lecture 68 Working with shapefiles - Part 2

Lecture 69 Application: Shapefile to GeoJSON converter

Section 15: Working with database data

Lecture 70 Working with database data

Lecture 71 SQLite example

Lecture 72 PostgreSQL and PostGIS

Section 16: The python data science stack

Lecture 73 Introduction

Lecture 74 Jupyter Notebooks

Lecture 75 Numpy

Lecture 76 Matplotlib

Lecture 77 Pandas

Section 17: Geospatial analysis in python

Lecture 78 GDAL/OGR

Lecture 79 Fiona and Shapely

Lecture 80 Geopandas - Part 1

Lecture 81 Geopandas - Part 2

Lecture 82 Rasterio

Lecture 83 GeoPy

Lecture 84 Where to go next

Section 18: Bonus Lectures

Lecture 85 Bonus Lecture: How to get the most from my series of Udemy courses.

This course is oriented towards geospatial professionals who want a better understanding of the complete python ecosystem for geospatial applications.,For this course I will not go into detail about any specific python tool, rather this is intended to be an introduction to the language and an overview of its capabilities.