Last modified on 24 Jun 2020.
Hierarchical Data Format (HDF)
- Designed to store and organize large amounts of data.
- Store multiple data files in a single data file!
- Different types of information.
- Self describing (metadata included in the file)
- Datasets (numpy arrays): fast slicing, compression.
- Group (dictionaries): nesting, POSIX path syntax.
- Attributrs (metadata): datasets/group, key-value.
- HDF5 is row based and really effient than csv for very large file size[ref] .
- Tool: HDFView
- Example[ref] :
An example HDF5 file structure which contains groups, datasets and associated metadata.
import h5py f = h5py.File('mytestfile.hdf5', 'r') # read a file # h5py.File acts like Python dict dset = f['mydataset'] dset.attrs # attribute
•Notes with this notation aren't good enough. They are being updated. If you can see this, you are so smart. ;)