How to create and use indexes for HDF5 files?

I have a very large DataFrame that needs to be saved in the hdf5 file. Generate_data() is the function of generating data. In the read_unique_date() function, store.df.date.drop_duplicates() needs to be executed for 5 seconds. Also after using mysql, execute select distinct date from table only takes 80ms.

How can I create and use an index in the HDF5 file?

My code is as follows:

import pandas as pd
import numpy as np
from itertools import product
from time import time


def generate_data():
    np.random.seed(202108)

    date = pd.date_range(start="19900101", end="20210723", freq="D")
    date = pd.DataFrame(date, columns=["date"])

    code = pd.DataFrame(range(5000), columns=["code"])

    # generate product of the two columns:
    df = pd.DataFrame(product(date["date"], code["code"]), columns=["date", "code"])
    df['data'] = np.random.random(len(df))
    return df


def save_data(filename, df):
    store = pd.HDFStore(filename)
    store['df'] = df
    store.close()
    return


def read_unique_date(file_name):
    store = pd.HDFStore(file_name)
    start = time()
    df = store.df.date.drop_duplicates()
    store.close()
    stop = time()
    print(stop - start)
    return df


def main():
    path = 'd:\\'
    file = 'large data.h5'
    file_name = path + file
    df = generate_data()
    save_data(file_name, df)
    df1 = read_unique_date(file_name)
    return


if __name__ == '__main__':
    main()

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