Climate Geospatial Analysis on Python with Xarray
33 ratings

Loading, exporting and interacting with climate NetCDF datasets
Apply simple and grouped operations over multidimensional data
Navigate and visualize multidimensional geospatial data
33 ratings
Loading, exporting and interacting with climate NetCDF datasets
Apply simple and grouped operations over multidimensional data
Navigate and visualize multidimensional geospatial data
By the end of this project, you will be able to load, visualize, manipulate and perform both simple and grouped operations over geospatial multidimensional data through Xarray and Python. We'll explore an dataset containing temperature, vegetation density and total precipitation over the Brazilian Amazon for the 1979-2019 period while the concepts are developed. This will enable the learner to handle and extract knowledge from complex datasets such as the ones from satellite and climate re-analysis observations. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
xarray
Python Programming
Data Analysis
Geospatial Analysis
multidimensional data manipulation
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Load and getting familiar with NetCDF datasets
Select and filter data through coordinates
Visualize multidimensional and geospatial variables
Apply simple operations over multidimensional data
Apply grouped operations over multidimensional data
Merge and concatenate datasets
Interact with Pandas and export datasets
Your workspace is a cloud desktop right in your browser, no download required
In a split-screen video, your instructor guides you step-by-step
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