src/load_data.py

import streamlit as st
import pandas as pd

@st.cache_data
def load_dataframe() -> pd.DataFrame:
    """
    Load dataframe from the csv file in public directory
    Returns
    dataframe: a pd.DataFrame of the average scores of the LLMs on each task
    """

    dataframe = pd.read_csv("public/datasets/models_scores.csv")
    dataframe = dataframe.drop(columns = "Unnamed: 0")
    return dataframe

@st.cache_data
def show_dataframe_top(n:int , dataframe: pd.DataFrame) -> pd.DataFrame:
    """
    read only the n-th first row
    Arguments
    -n: an integer telling the number of row
    -dataframe: the dataframe to slice
    Returns
    dataframe: a pd.DataFrame of the average scores of the LLMs on each task
    """

    return dataframe.head(n)

@st.cache_data
def sort_by(dataframe: pd.DataFrame, column_name: str, ascending:bool = False) -> pd.DataFrame:
    """
    Sort the dataframe by column_name
    
    Arguments:
    - dataframe: a pandas dataframe to sort
    - column_name: a string stating the column to sort the dataframe by
    - ascending: a boolean stating to sort in ascending order or not, default to False

    Returns:
    a sorted dataframe
    """
    return dataframe.sort_values(by = column_name, ascending = ascending )

@st.cache_data
def search_by_name(name: str) -> pd.DataFrame:
    """
    Search a model by its name

    Arguments:
    - name: the name of the model or part of it

    Returns:
    a pandas Dataframe of every row that contains name
    """
    dataframe = load_dataframe()
    indexes = dataframe["model_name"].str.contains(name)
    return dataframe[indexes]