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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.
Read more
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.
Read more
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
Show steps
Create a resource that can be used as a quick reference for Python functions and syntax
Browse courses on
Python
Show steps
-
Gather a list of essential Python functions and syntax
-
Organize the functions and syntax
-
Create a cheat sheet
Python for Data Analysis
Show steps
This book provides a comprehensive overview of the Python programming language and its applications in data analysis
View
Python for Data Analysis
on Amazon
Show steps
-
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
Show steps
Gain hands-on experience and apply your skills to real-world projects
Browse courses on
GIS
Show steps
-
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
Expand to see all activities and additional details
Show all eight activities
Peer Code Review
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Refine your coding skills and understanding through peer review
Browse courses on
Python
Show steps
-
Find a peer
-
Exchange code
-
Review each other's code
-
Provide feedback
Complete tutorials from plotly
Show steps
Familiarity with plotting libraries will greatly enhance your ability to visualize data
Browse courses on
Plotting
Show steps
-
Visit the plotly website
-
Review the tutorials
-
Complete the interactive tutorials
Build a Web Mapping Application
Show steps
Combine the core concepts of Python data science and geospatial analysis by building a web mapping application
Browse courses on
Development
Show steps
-
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
Show steps
Improve your coding skills and problem-solving abilities
Browse courses on
Python
Show steps
-
Find a coding challenge website
-
Select a challenge
-
Attempt to solve the challenge
-
Review the solution
Create a data visualization dashboard
Show steps
Develop your skills in data visualization and dashboard creation
Browse courses on
Data Visualization
Show steps
-
Gather a dataset
-
Clean and prepare the dataset
-
Create visualizations
-
Create a dashboard
Create a cheat sheet of Python functions and syntax
Show steps
Create a resource that can be used as a quick reference for Python functions and syntax
Browse courses on
Python
Show steps
Show steps
Show steps
- Gather a list of essential Python functions and syntax
- Organize the functions and syntax
- Create a cheat sheet
Python for Data Analysis
Show steps
This book provides a comprehensive overview of the Python programming language and its applications in data analysis
View
Python for Data Analysis
on Amazon
Show steps
Show steps
Show steps
- 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
Show steps
Gain hands-on experience and apply your skills to real-world projects
Browse courses on
GIS
Show steps
Show steps
Show steps
- 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
Expand to see all activities and additional details
Show all eight activities
Peer Code Review
Show steps
Refine your coding skills and understanding through peer review
Browse courses on
Python
Show steps
Show steps
Show steps
- Find a peer
- Exchange code
- Review each other's code
- Provide feedback
Complete tutorials from plotly
Show steps
Familiarity with plotting libraries will greatly enhance your ability to visualize data
Browse courses on
Plotting
Show steps
Show steps
Show steps
- Visit the plotly website
- Review the tutorials
- Complete the interactive tutorials
Build a Web Mapping Application
Show steps
Combine the core concepts of Python data science and geospatial analysis by building a web mapping application
Browse courses on
Development
Show steps
Show steps
Show steps
- 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
Show steps
Improve your coding skills and problem-solving abilities
Browse courses on
Python
Show steps
Show steps
Show steps
- Find a coding challenge website
- Select a challenge
- Attempt to solve the challenge
- Review the solution
Create a data visualization dashboard
Show steps
Develop your skills in data visualization and dashboard creation
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- 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 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.
GIS Developer
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.
Data Scientist
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.
Machine Learning Engineer
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.
GIS Specialist
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.
Spatial Data Scientist
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.
Statistician
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.
Business Analyst
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.
Remote Sensing 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.
Data Engineer
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.
Data Analyst
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.
Financial 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.
Operations Research 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.
Web Developer
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.
Software Engineer
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.
For more career information including salaries, visit:
OpenCourser.com/course/1yontx/survey
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.
Provides a comprehensive overview of data science concepts and techniques. It covers data cleaning, feature engineering, model building, and evaluation from scratch.
Serves as an introduction to the key principles of data analysis in Python. It provides a conceptual foundation for data exploration, manipulation, and visualization.
Save
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.
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.
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.
Save
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.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/1yontx/survey
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Effort
13.5 total hours
Via
Udemy
Good to know
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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