Survey of python for GIS applications

Survey of python for GIS applications, available at $64.99, has an average rating of 4.5, with 85 lectures, based on 226 reviews, and has 1372 subscribers.

You will learn about 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 This course is ideal for individuals who are This course is oriented towards geospatial professionals who want a better understanding of the complete python ecosystem for geospatial applications. or 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. It is particularly useful for This course is oriented towards geospatial professionals who want a better understanding of the complete python ecosystem for geospatial applications. or 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.

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Summary

Title: Survey of python for GIS applications

Price: $64.99

Average Rating: 4.5

Number of Lectures: 85

Number of Published Lectures: 85

Number of Curriculum Items: 85

Number of Published Curriculum Objects: 85

Original Price: $89.99

Quality Status: approved

Status: Live

What You Will 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

Who Should Attend

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.

Target Audiences

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.

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 python

Object oriented python

Packages and modules

Unit tests

Jupyter notebooks

Numpy

Matplotlib

Pandas

Fiona and shapely

Geopandas

Rasterio

Geocoding

PyQt

Course Curriculum

Chapter 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

Chapter 2: Installing Python

Lecture 1: Getting started

Lecture 2: Installing Python on MacOS

Lecture 3: Installing PyCharm on MacOS

Chapter 3: Getting started with Python

Lecture 1: Boolean and numeric variables

Lecture 2: Converting between variable types

Lecture 3: Strings

Lecture 4: String methods

Lecture 5: String formatting

Chapter 4: Operators and expressions in Python

Lecture 1: Operators Part 1

Lecture 2: Operators Part 2

Lecture 3: Expressions

Chapter 5: Complex data structures

Lecture 1: Lists

Lecture 2: Working with lists

Lecture 3: Tuples

Lecture 4: Sets

Lecture 5: Working with sets

Lecture 6: Dictionaries

Lecture 7: Working with dictionaries

Lecture 8: Review of complex data structures

Chapter 6: Program control

Lecture 1: The if statement in Python

Lecture 2: While loops in Python

Lecture 3: For loops in Python

Lecture 4: Generators

Chapter 7: User Input

Lecture 1: The input() function

Lecture 2: Command line arguments

Lecture 3: Working with user input

Chapter 8: Functions

Lecture 1: Introduction to functions

Lecture 2: Function example

Lecture 3: Function arguments

Lecture 4: Map and filter functions

Lecture 5: Lambda functions

Lecture 6: Nested functions, decorator functions, and scope

Chapter 9: Error Handling in Python

Lecture 1: Error Handling in Python

Lecture 2: Error handling – Part 2

Chapter 10: Modules

Lecture 1: What is a module?

Chapter 11: Objects in python

Lecture 1: What is an object?

Lecture 2: Defining a custom object class

Lecture 3: Object example

Lecture 4: String representation of an object

Lecture 5: Object inheritance

Lecture 6: Private properties and methods

Lecture 7: Principles of object oriented programing

Chapter 12: Python packages, virtual environments, and documentation

Lecture 1: What is a package?

Lecture 2: Working with third party packages

Lecture 3: Virtual Environments

Lecture 4: Virtual Environments – Part 2

Lecture 5: Documentation in python

Chapter 13: Formal testing in python

Lecture 1: The unittest module

Lecture 2: Writing a test suite for the Point class

Chapter 14: Working with the operating system and files

Lecture 1: The OS module

Lecture 2: The OS.path submodule

Lecture 3: Reading and writing plain text files

Lecture 4: Reading and writing plain text files – Part 2

Lecture 5: Creating a word count application

Lecture 6: Reading and writing CSV files

Lecture 7: Reading and writing CSV files – Part 2

Lecture 8: Word Count Application – Part 2

Lecture 9: Working with JSON data

Lecture 10: Working with JSON data – Part 2

Lecture 11: Word Count Application – Part 3

Lecture 12: Working with shape files

Lecture 13: Working with shapefiles – Part 2

Lecture 14: Application: Shapefile to GeoJSON converter

Chapter 15: Working with database data

Lecture 1: Working with database data

Lecture 2: SQLite example

Lecture 3: PostgreSQL and PostGIS

Chapter 16: The python data science stack

Lecture 1: Introduction

Lecture 2: Jupyter Notebooks

Lecture 3: Numpy

Lecture 4: Matplotlib

Lecture 5: Pandas

Chapter 17: Geospatial analysis in python

Lecture 1: GDAL/OGR

Lecture 2: Fiona and Shapely

Lecture 3: Geopandas – Part 1

Lecture 4: Geopandas – Part 2

Lecture 5: Rasterio

Lecture 6: GeoPy

Instructors

Michael Miller
GIS Programming

Rating Distribution

1 stars: 1 votes

2 stars: 3 votes

3 stars: 26 votes

4 stars: 82 votes

5 stars: 114 votes

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