Point NCPlot at a netCDF file, an OPeNDAP URL, or an xarray dataset. It works out the variables, dimensions and coordinates for you, and builds an interactive plot — in a notebook, a browser, or straight from the terminal.
view("file.nc")
ds.ncplot.view()
ncplot file.nc
from ncplot import view view( "https://psl.noaa.gov/thredds/dodsC/Datasets/COBE2/sst.mon.ltm.1981-2010.nc", vars="sst", coast=True, ) # -> an interactive map, no other setup needed
NCPlot turns viewing a netCDF file into a single function call, so you spend time looking at your data instead of writing plotting code.
A local path, an OPeNDAP/THREDDS URL, a directory of files, or an already-open xarray Dataset/DataArray.
view()NCPlot inspects each variable's dimensions and coordinates and picks a sensible plot automatically — map, cross-section, or time series.
Pan, zoom and read off values in your notebook or browser, or save the result as a shareable, self-contained HTML file.
Built for anyone who just wants to see what's inside a netCDF file — so the defaults are sensible and nothing needs configuring first.
Install from conda-forge or pip and plot your first file the same minute — no setup, no boilerplate.
Local files, directories of files, or remote OPeNDAP/THREDDS URLs — NCPlot reads them all the same way.
Maps, vertical sections and time series are chosen based on each variable's dimensions — no chart type to pick.
Register the accessor once and call ds.ncplot.view() or da.ncplot.view(), just like xarray's own .plot().
ncplot file.nc opens an interactive view straight from the terminal — no Python session required.
Pass out="figure.html" to save any plot as a self-contained file you can send to a colleague.
Every view() call inspects the file or dataset you give it, decides how best to represent each variable, and renders an interactive, pannable, zoomable plot — in a notebook cell, a browser tab, or embedded in an HTML report.
# install conda install -c conda-forge ncplot # view every variable in a file, from Python... from ncplot import view view("example.nc") # ...or straight from the command line ncplot example.nc
Works from Python, a Jupyter notebook, the xarray accessor, or the terminal — pick whichever fits how you already work with your data. No project setup, no configuration file.