Climate Geospatial Analysis on Python with Xarray

Offered By
Coursera Project Network
In this Guided Project, you will:

Loading, exporting and interacting with climate NetCDF datasets

Apply simple and grouped operations over multidimensional data

Navigate and visualize multidimensional geospatial data

Clock45 minutes for the guided part + 45 minutes for practice
IntermediateIntermediate
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

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.

Skills you will develop

xarrayPython ProgrammingData AnalysisGeospatial Analysismultidimensional data manipulation

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Load and getting familiar with NetCDF datasets

  2. Select and filter data through coordinates

  3. Visualize multidimensional and geospatial variables

  4. Apply simple operations over multidimensional data

  5. Apply grouped operations over multidimensional data

  6. Merge and concatenate datasets

  7. Interact with Pandas and export datasets

How Guided Projects work

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

Frequently asked questions

Frequently Asked Questions

More questions? Visit the Learner Help Center.