Is there a way to enable HDF4 support in GDAL?
The HDF4 libraries depend on libz library. If you build HDF4 from sources, you most likely use libz library already installed in your system. Then, when you run GDAL ./configure script using option –with-libz=internal requesting GDAL to use its internal version of libz, you may notice that HDF4 support is not enabled as you expected.
How to read HDF4 data in Python using PANDAS?
Once you’ve got the file in HDF5 (you should not lose any data here as HDF4 attributes translate directly to HDF5) you’ve got a number of options in Python for working with the data. Your best bet is to install PyTables and Pandas and use the inbuilt HDFStore object to read in the data, which might look something like:
Is the HDF4 library compatible with NetCDF?
The HDF4 libraries include an implementation of the netcdf api which can access hdf files. If building with HDF4 and NetCDF it is necessary to build the HDF library with this disabled. If using Ubuntu/Debian? dev packages you must make sure that the libhdf4-alt-dev package is installed instead of the libhdf4-dev package.
Which is the best way to read HDF4 data?
Your best bet is to install PyTables and Pandas and use the inbuilt HDFStore object to read in the data, which might look something like: Printing the store gives you a list of the series and frames stored in the dataset: And from there you’ve got a complete dataframe object where you can do what you like, eg:
What’s the difference between HDF4 and HDF5?
There are two HDF formats, HDF4, and HDF5 which each have their own libraries and drivers. HDF4 is more common, but HDF5 is the next generation format. http://www.gdal.org/frmt_hdf4.html – hdf4 driver docs
Where can I download the NCSA HDF library?
NCSA HDF library can be downloaded from the The NCSA HDF Home Page at the the National Center for Supercomputing Applications. HDF 4.2r1 is generally the preferred version if working from source.