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Survey of python for GIS applications

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

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Explores essential geospatial analysis packages for Python, including NumPy, Matplotlib, Pandas, Fiona, Shapely, Geopandas, and Rasterio

Provides a strong foundation for those seeking to learn the basics of Python and apply it to geospatial data analysis

Introduces object-oriented programming concepts in Python, fostering a deeper understanding of Python's capabilities

Emphasizes practical application through Jupyter notebooks, enabling learners to apply their knowledge immediately

Provides a comprehensive introduction to PyQt, a powerful library for creating graphical user interfaces in Python

Covers unit testing, an essential practice for ensuring code quality and reliability

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Survey of python for GIS applications with these activities:

Create a cheat sheet of Python functions and syntax

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Create a resource that can be used as a quick reference for Python functions and syntax

Browse courses on Python

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Gather a list of essential Python functions and syntax
Organize the functions and syntax
Create a cheat sheet

Python for Data Analysis

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This book provides a comprehensive overview of the Python programming language and its applications in data analysis

View Python for Data Analysis on Amazon

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Read chapters 1-3
Complete the exercises in chapters 1-3
Read chapters 4-6
Complete the exercises in chapters 4-6

Volunteer at a local GIS organization or government agency

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Gain hands-on experience and apply your skills to real-world projects

Browse courses on GIS

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Find a local GIS organization or government agency
Contact the organization or agency
Inquire about volunteer opportunities
Attend volunteer training
Volunteer your time

Five other activities

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Peer Code Review

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Refine your coding skills and understanding through peer review

Browse courses on Python

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Find a peer
Exchange code
Review each other's code
Provide feedback

Complete tutorials from plotly

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Familiarity with plotting libraries will greatly enhance your ability to visualize data

Browse courses on Plotting

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Visit the plotly website
Review the tutorials
Complete the interactive tutorials

Build a Web Mapping Application

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Combine the core concepts of Python data science and geospatial analysis by building a web mapping application

Browse courses on Development

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Review the Django tutorial
Set up a Django project
Create a model for your data
Create a view for your data
Create a template for your view

Practice coding challenges

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Improve your coding skills and problem-solving abilities

Browse courses on Python

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Find a coding challenge website
Select a challenge
Attempt to solve the challenge
Review the solution

Create a data visualization dashboard

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Develop your skills in data visualization and dashboard creation

Browse courses on Data Visualization

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Gather a dataset
Clean and prepare the dataset
Create visualizations
Create a dashboard

Career center

Learners who complete Survey of python for GIS applications will develop knowledge and skills that may be useful to these careers:

Geospatial Analyst

Geospatial Analysts use their knowledge of geography and technology to solve problems. This course can help build a foundation in the python packages used for geospatial analysis, including Fiona, Shapely, GeoPandas, and Rasterio. These packages help Geospatial Analysts work with geospatial data and create maps and other visualizations.

See salaries and explore the career path for Geospatial Analyst

GIS Developer

GIS Developers use their programming skills to build and maintain geographic information systems (GIS). This course can help build a foundation in python, a programming language commonly used by GIS Developers. The course also covers GIS packages, including GeoPandas and Rasterio, which help GIS Developers work with geospatial data.

See salaries and explore the career path for GIS Developer

Data Scientist

Data Scientists use their knowledge of data science to solve problems. This course can help build a foundation in python, a programming language commonly used by Data Scientists. The course also covers data analysis techniques and packages, including Numpy, Pandas, and Matplotlib, all of which are used by Data Scientists for data analysis and visualization.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers design, develop, and maintain machine learning models. This course can help build a foundation in python, a programming language commonly used by Machine Learning Engineers. The course also covers data analysis techniques and packages, including Numpy, Pandas, and Matplotlib, all of which are used by Machine Learning Engineers for data analysis and visualization.

See salaries and explore the career path for Machine Learning Engineer

GIS Specialist

GIS Specialists use their knowledge of GIS to solve problems. This course can help build a foundation in the python packages used for GIS, including GeoPandas and Rasterio. These packages help GIS Specialists work with geospatial data and create maps and other visualizations.

See salaries and explore the career path for GIS Specialist

Spatial Data Scientist

Spatial Data Scientists use their knowledge of data science and spatial analysis to solve problems. This course can help build a foundation in python, a programming language commonly used by Spatial Data Scientists. The course also covers data analysis techniques and packages, including Numpy, Pandas, and Matplotlib, all of which are used by Spatial Data Scientists for data analysis and visualization.

See salaries and explore the career path for Spatial Data Scientist

Statistician

Statisticians use their knowledge of statistics to solve problems. This course can help build a foundation in python, a programming language commonly used by Statisticians. The course also covers data analysis techniques and packages, including Numpy, Pandas, and Matplotlib, all of which are used by Statisticians for data analysis and visualization.

See salaries and explore the career path for Statistician

Business Analyst

Business Analysts use their knowledge of business and data analysis to solve problems. This course can help build a foundation in python, a programming language commonly used by Business Analysts. The course also covers data analysis techniques and packages, including Numpy, Pandas, and Matplotlib, all of which are used by Business Analysts for data analysis and visualization.

See salaries and explore the career path for Business Analyst

Remote Sensing Analyst

Remote Sensing Analysts use their knowledge of remote sensing to solve problems. This course can help build a foundation in the python packages used for remote sensing, including Rasterio. Rasterio helps Remote Sensing Analysts work with raster data and create maps and other visualizations.

See salaries and explore the career path for Remote Sensing Analyst

Data Engineer

Data Engineers design, build, and maintain data pipelines. This course can help build a foundation in python, a programming language commonly used by Data Engineers. The course also covers data analysis techniques and packages, including Numpy, Pandas, and Matplotlib, all of which are used by Data Engineers for data analysis and visualization.

See salaries and explore the career path for Data Engineer

Data Analyst

Data Analysts help organizations make better decisions by collecting, cleaning, and analyzing data. This course can help build a foundation in python, a programming language commonly used by Data Analysts. The course covers data analysis techniques and packages, including Numpy, Pandas, and Matplotlib, all of which are used by Data Analysts for data analysis and visualization.

See salaries and explore the career path for Data Analyst

Financial Analyst

Financial Analysts use their knowledge of finance and data analysis to solve problems. This course can help build a foundation in python, a programming language commonly used by Financial Analysts. The course also covers data analysis techniques and packages, including Numpy, Pandas, and Matplotlib, all of which are used by Financial Analysts for data analysis and visualization.

See salaries and explore the career path for Financial Analyst

Operations Research Analyst

Operations Research Analysts use their knowledge of operations research to solve problems. This course can help build a foundation in python, a programming language commonly used by Operations Research Analysts. The course also covers data analysis techniques and packages, including Numpy, Pandas, and Matplotlib, all of which are used by Operations Research Analysts for data analysis and visualization.

See salaries and explore the career path for Operations Research Analyst

Web Developer

Web Developers design, develop, and maintain websites. This course can help build a foundation in python, a programming language commonly used by Web Developers. The course also covers object-oriented python and unit tests, which are essential for Web Developers.

See salaries and explore the career path for Web Developer

Software Engineer

Software Engineers design, develop, and maintain software applications. This course can help build a foundation in python, a programming language commonly used by Software Engineers. The course also covers object-oriented python and unit tests, which are essential for Software Engineers.

See salaries and explore the career path for Software Engineer

Reading list

We've selected six books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Survey of python for GIS applications.

Data Science from Scratch

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Provides a comprehensive overview of data science concepts and techniques. It covers data cleaning, feature engineering, model building, and evaluation from scratch.

Data Science from Scratch: First Principles with...

Paperback

Data Science from Scratch: First Principles with...

Kindle Edition

Data Science from Scratch: First Principles with...

Paperback

Python for Data Analysis

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Serves as an introduction to the key principles of data analysis in Python. It provides a conceptual foundation for data exploration, manipulation, and visualization.

Python for Data Analysis: Data Wrangling with...

Paperback

Python for Data Analysis

Kindle Edition

Python for Data Analysis: Data Wrangling with...

Paperback

$$$

Pandas 1.x Cookbook

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Offers a collection of recipes and solutions for common data analysis tasks using Pandas. It can serve as a useful reference for applying Pandas techniques covered in this course.

Pandas 1.x Cookbook - Second Edition: Practical...

Paperback

$$$

Pandas 1.x Cookbook: Practical recipes for...

Kindle Edition

Financial Theory with Python

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Even though this book is targeted specifically at data analysis in finance, its coverage of Python basics, data manipulation, and visualization could serve as valuable background for this course.

Financial Theory with Python: A Gentle Introduction

Paperback

Learning Geospatial Analysis with Python

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Focuses on geospatial analysis and visualization using Python. While not as comprehensive as some of the other books on this list, it can serve as a concise overview of relevant topics.

Learning Geospatial Analysis with Python - Fourth...

Paperback

Learning Geospatial Analysis with Python:...

Kindle Edition

Learning Geospatial Analysis With Python: An...

Paperback

Learning Geospatial Analysis with Python

Kindle Edition

Effective Python

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Provides best practices and idioms for writing efficient and maintainable Python code. While not specific to GIS applications, it can enhance the quality and readability of code written for this course.

Effective Python: 90 Specific Ways to Write Better...

Paperback

Effective Python: 59 Specific Ways to Write Better...

Paperback

Effective Python: 90 Specific Ways to Write Better...

Kindle Edition

Effective Python: 59 Specific Ways to Write Better...

Kindle Edition

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Explores essential geospatial analysis packages for Python, including NumPy, Matplotlib, Pandas, Fiona, Shapely, Geopandas, and Rasterio

Provides a strong foundation for those seeking to learn the basics of Python and apply it to geospatial data analysis

Introduces object-oriented programming concepts in Python, fostering a deeper understanding of Python's capabilities

Emphasizes practical application through Jupyter notebooks, enabling learners to apply their knowledge immediately

Provides a comprehensive introduction to PyQt, a powerful library for creating graphical user interfaces in Python

Covers unit testing, an essential practice for ensuring code quality and reliability

Share and help others discover this course.

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