34 lines
953 B
Python
34 lines
953 B
Python
|
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()
|