Spaces:
Running
Running
import pandas as pd | |
from pathlib import Path | |
def get_dataframe_category(): | |
from src.data_loader import get_category_dataframe | |
return get_category_dataframe(processed=False) | |
def get_dataframe_language(): | |
from src.data_loader import get_language_dataframe | |
return get_language_dataframe(processed=False) | |
import json | |
def get_length_category_df(selected_category): | |
""" | |
Loads length_data.json and returns a DataFrame for the selected category. | |
Columns: Model Name, {Category} Min, {Category} Max, {Category} Med, {Category} Med Resp | |
""" | |
abs_path = Path(__file__).parent | |
json_path = abs_path / "data/length_data.json" | |
with open(json_path, "r", encoding="utf-8") as f: | |
data = json.load(f) | |
rows = [] | |
for model_name, stats in data.items(): | |
cat = stats.get(selected_category, {}) | |
row = { | |
"Model Name": model_name, | |
f"Min Len. ({selected_category})": cat.get("Min", None), | |
f"Max Len. ({selected_category}))": cat.get("Max", None), | |
f"Med. Len. ({selected_category})": cat.get("Med", None), | |
f"Med. Resp. Len. ({selected_category})": cat.get("Med Resp", None), | |
} | |
rows.append(row) | |
df = pd.DataFrame(rows) | |
return df | |
def get_length_category_list(): | |
""" | |
Returns the list of available categories in length_data.json (excluding 'Overall'). | |
""" | |
abs_path = Path(__file__).parent | |
json_path = abs_path / "data/length_data.json" | |
with open(json_path, "r", encoding="utf-8") as f: | |
data = json.load(f) | |
if not data: | |
return [] | |
# Get categories from the first model | |
first_model = next(iter(data.values())) | |
categories = [k for k in first_model.keys() if k != "Overall"] | |
return categories | |