#! /usr/bin/env 

import pandas as pd
import math

# helper to calculate an overall district rating
def get_overall_rating(df: pd.DataFrame):
    '''
    Returns a DataFrame that contains the overall district scores.
        Parameters:
                df (DataFrame): 
        Returns:
                overall (DataFrame): 
    '''
    weights = {
        'e': 0.3,
        'm': 0.2,
        'h': 0.5
    }
    levels = weights.keys()
    empty_stats = {
        'e_ave': 0,
        'm_ave': 0,
        'h_ave': 0,
        'weighted_ave': 0    
    }
    overall = pd.DataFrame()

    districts = list(df.index.unique(level=0))
    for district in districts:
        scores = {}
        stats = empty_stats
        weighted_ave = 0
        schools = list(df.loc[district].index.unique(level=0))
        if len(schools) <= 1:
            continue
        for level in levels:
            scores[level] = []
            for school in schools:
                this_school = df.loc[[(district,school)]]
                codes = this_school['level-codes'].iloc[0]
                if level in codes:
                    rating = float(this_school['rating'].iloc[0])
                    if not math.isnan(rating):
                        scores[level].append(this_school['rating'].iloc[0])
            #print(district, scores)
            try:
                stats[level+'_ave'] = round(sum(scores[level])/len(scores[level]),2)
            except:
                continue
        for weight in weights.keys():
            weighted_ave += weights[weight]*stats[weight+'_ave']
        stats['weighted_ave'] = round(weighted_ave,2)
        district_dict = {'district-name': district}
        district_dict = {**district_dict, **stats}
        overall = pd.DataFrame(district_dict)
        print(overall)
        return