Hi. I'm trying to read a big netcdf file (445 Mb) using netcdf4-python.
The data are described as: *The GEBCO gridded data set is stored in NetCDF as a one dimensional array of 2-byte signed integers that represent integer elevations in metres. The complete data set gives global coverage. It consists of 21601 x 10801 data values, one for each one minute of latitude and longitude for 233312401 points. The data start at position 90°N, 180°W and are arranged in bands of 360 degrees x 60 points/degree + 1 = 21601 values. The data range eastward from 180°W longitude to 180°E longitude, i.e. the 180° value is repeated.* The problem is that it is very slow (or I am quite newbie). Anyone has a suggestion to get these data in a numpy array in a faster way? Thanks in advance.
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