Reading and writing data from HDF5

HDF stands for Hierarchical Data Format. HDF is designed to store and manage large amounts of data with high performance. It offers fast I/O processing and storage of heterogeneous data. There are various HDF file formats available, such as HDF4 and HDF5. HDF5 is the same as a dictionary object that reads and writes pandas DataFrames. It uses the PyTables library's read_hdf() function for reading the HDF5 file and the to_hdf() function for writing:

# Write DataFrame to hdf5
df.to_hdf('employee.h5', 'table', append=True)

In the preceding code example, we have written the HDF file format using the to_hdf() method. 'table' is a format parameter used for the table format. Table format may perform slower but offers more flexible operations, such as searching and selecting. The append parameter is used to append input data onto the existing data file:

# Read a hdf5 file
df=pd.read_hdf('employee.h5', 'table&apos...