Visualizing Geospatial Data in Python faq

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Learn how to visualize geospatial data in Python! This course will teach you how to make a two-layer map by first plotting regions from a shapefile and then scatterploting location points. You'll also learn about projections and coordinate reference systems, and practise joining data spatially. Plus, you'll use three different GeoSeries attributes and methods to obtain information about the geometries in your data. You'll also use folium to create a street map layer and discover a choropleth, a type of map. Finally, you'll learn and practise choropleth construction using two different packages: geopandas and folium.

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Course Overview

❗The content presented here is sourced directly from Datacamp platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [June 30th, 2023]

This course provides an introduction to visualizing geospatial data in Python. Participants will learn how to make a two-layer map by first plotting regions from a shapefile and then scatterploting location points. They will also learn about projections and coordinate reference systems, and practise joining data spatially. Additionally, participants will learn how to use three different GeoSeries attributes and methods to obtain information about the geometries in their data. They will also learn how to use folium to create a street map layer, and discover a choropleth, a type of map. Finally, participants will learn and practise choropleth construction using two different packages: geopandas and folium.

[Applications]
The application of this course can be seen in a variety of ways. For example, it can be used to create visualizations of geospatial data for a variety of purposes, such as to analyze population density, to identify areas of environmental concern, or to track the spread of a disease. Additionally, the course can be used to create interactive maps for websites or applications, allowing users to explore the data in a more engaging way. Finally, the course can be used to create custom maps for presentations or reports, allowing the user to quickly and easily communicate their findings.

[Career Paths]
The career path recommended to learners of this course is a GIS Analyst. A GIS Analyst is responsible for analyzing and interpreting geographic data to create maps and other visualizations. They use Geographic Information Systems (GIS) software to analyze and interpret data, create maps, and develop reports. They also use GIS software to develop and maintain databases of geographic information.

The development trend of GIS Analyst is very positive. With the increasing use of GIS technology in various industries, the demand for GIS Analysts is expected to grow significantly in the coming years. GIS Analysts are in high demand in the fields of urban planning, environmental science, and natural resource management. As the use of GIS technology continues to expand, the demand for GIS Analysts is expected to increase. Additionally, GIS Analysts are increasingly being used in the fields of marketing, logistics, and transportation.

[Education Paths]
The recommended educational path for learners of Visualizing Geospatial Data in Python is a Bachelor's degree in Geographic Information Systems (GIS). This degree program focuses on the use of technology to capture, store, analyze, and present geographic data. It combines elements of computer science, cartography, and geography to create a comprehensive understanding of GIS.

The development trend of GIS is towards the integration of more sophisticated technologies such as artificial intelligence, machine learning, and big data analytics. This will enable GIS professionals to create more accurate and detailed maps, as well as to develop more powerful applications for analyzing and visualizing geospatial data. Additionally, GIS is becoming increasingly important in the fields of urban planning, environmental management, and disaster response. As such, GIS professionals are in high demand in these fields.

Course Syllabus

Building 2-layer maps : combining polygons and scatterplots

Creating and joining GeoDataFrames

GeoSeries and folium

Creating a choropleth building permit density in Nashville

Course Provider

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