A brief description
Geospatial data science is a branch of data science that focuses on spatial data and the methods that go with it. We’ll do some spatial analysis and try to glean some ideas from the information. We will pave the groundwork for a future in geospatial data science in this course. The workhorse of Geospatial data science Python libraries, Geopy, Plotly, and others, will be demonstrated.
This course covers a broad range of subjects in geospatial data science, including some of the most commonly used spatial techniques. We’ll learn how to interpret, manipulate, and process spatial data with Pandas, as well as run some spatial operations.
Choropleth, Geographical Scatter diagram, Geographical Heatmap, Markers, and Geographical HeatMap are only a few of the spatial visuals covered in the course. Each video includes a description of the subject as well as a walkthrough of code examples to aid your learning.
This course is intended for the following individuals:
- Students who want to be Data Scientists should highlight these projects on their resumes.
- Students interested in taking their first steps in the field of geospatial data science.
- Python users who want to learn more about spatial data science.
- Users of Geographic Information Systems (GIS) that are new to Python and Jupyter Notebooks for Geographic Data Processing…
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