import h5py
import pandas as pd

file = "ltcc_current.h5"

# Dict to hold DFs 'sex', 'iso' & 'spid'
dfs_by_sex_iso_spid = {}

with h5py.File(file, "r") as h5_file:
    for eid in h5_file.keys():
        attributes = h5_file[eid].attrs
        sex = attributes.get("sex")
        iso = attributes.get("iso")
        spid = attributes.get("spid")

        # Creates a unique key for dict based on sex, iso & spid
        key = f"{sex}_{iso}_{spid}"

        if key not in dfs_by_sex_iso_spid:
            dfs_by_sex_iso_spid[key] = pd.DataFrame()

        row_data = {"experiment_id": eid, "sex": sex, "iso": iso, "spid": spid}
        temp_df = pd.DataFrame([row_data])

        # Append the DF to the appropriate dict entry
        dfs_by_sex_iso_spid[key] = pd.concat(
            [dfs_by_sex_iso_spid[key], temp_df], ignore_index=True
        )

for key, df in dfs_by_sex_iso_spid.items():
    print(f"DataFrame for {key}:")
    print(df)
    print()