import netCDF4 as nc fn = '/path/to/file.nc4' ds = nc.Dataset(fn) General File StructureĪ NetCDF file has three basic parts: metadata, dimensions and variables. For this article, I’m using a file containing climate data from Daymet. Loading a dataset is simple, just pass a NetCDF file path to netCDF4.Dataset(). To be sure your netCDF4 module is properly installed start an interactive session in the terminal (type python and press ‘Enter’). To install with anaconda (conda) simply type conda install netCDF4. I generally recommend using the anaconda Python distribution to eliminate the confusion that can come with dependencies and versioning. For this article we’ll focus strictly on netCDF4 as it is my personal preference.įor information on how to read and plot NetCDF data in Python with xarray and rioxarray check out this article. NetCDF files can be read with a few different Python modules. This article will get you started with reading data from NetCDF files using Python. NetCDF provides a solution for these challenges.

When each value is also assigned to a geographic location, data management is further complicated. With multiple measurements per day, data values accumulate quickly and become unwieldy to work with. Variables stored in NetCDF are often measured multiple times per day over large (continental) areas. Some examples of these data are temperature, precipitation, and wind speed. Network common data form (NetCDF) is commonly used to store multidimensional geographic data.

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