diff --git a/h5_data_organizer.py b/h5_data_organizer.py
new file mode 100644
index 0000000..425aa0e
--- /dev/null
+++ b/h5_data_organizer.py
@@ -0,0 +1,33 @@
+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()