data_process_gcam_category_emotions_v3.py

import csv
import reverse_geocoder as rg
import json

def find_nth(haystack, needle, n):
    start = haystack.find(needle)
    while start >= 0 and n > 1:
        start = haystack.find(needle, start+len(needle))
        n -= 1
    return start

def word_freq():
    category_map = {}
    with open('CategoryList.csv') as csvfile:
        reader = csv.DictReader(csvfile)
        for row in reader:
            category_name = row['Name']
            countries_map = {}
            with open('countries_medialist.csv') as csvfile:
                reader = csv.DictReader(csvfile)
                for row in reader:
                    s = row['country']
                    countries_map[s.strip()] = {'Sad': 0, 'Happy': 0, 'Anger': 0, 'Hatred': 0, 'Fear': 0}
            category_map[category_name] = countries_map

    map = {}
    c15_reader = []
    new_map = {}
    new_map['Anger'] = 0
    new_map['Sad'] = 0
    new_map['Hatred'] = 0
    new_map['Happy'] = 0
    new_map['Fear'] = 0

    #print(countries_map)

    with open('whitelist.csv') as csvfile:
        reader = csv.DictReader(csvfile)
        for row in reader:
            s = row['Emotion']
            t = row['c15']
            if len(t) > 0:
                c15_reader.append(t)
            map[t] = s

    with open('FinalData_emotions.csv') as csvfile:
        reader = csv.DictReader(csvfile, delimiter = '\t')
        for row in reader:
            s = row['GCam']
            u = row['Locations']
            event_counts = row['EventCounts']
            if (len(event_counts) != 0):
                category = event_counts[0:event_counts.index('#')]

            #print(category)
            if category not in category_map.keys():
                continue

            fourth_index = find_nth(u, "#", 4) + 1
            fifth_index_1 = find_nth(u, "#", 5)
            fifth_index_2 = fifth_index_1 + 1
            sixth_index = find_nth(u, "#", 6)
            if(len(u[fourth_index:fifth_index_1]) != 0):
                lat = float(u[fourth_index:fifth_index_1])
            if(len(u[fifth_index_2:sixth_index]) != 0):
                long = float(u[fifth_index_2:sixth_index])

            y = s.strip().split(",")
            max_key = ""
            max_val = 0
            for i in y:
                if((i[0] != 'w' and i[0] != 'v' and len(i) != 0)):
                    try:
                        word = i.split(':')[0]
                        val = i.split(':')[1]
                        if (len(word) > 0 and len(val) > 0):
                            if word in c15_reader:
                                if (float(val) > float(max_val)):
                                    max_val = val
                                    max_key = word
                    except IndexError:
                        pass

            if len(max_key) > 0:
                add = rg.search((lat, long))[0]['cc']
                #print(add)
                try:
                    #print(category_map[category][add][map[max_key]])
                    #print("Max Val " + max_val)
                    category_map[category][add][map[max_key]] = category_map[category][add][map[max_key]] + float(max_val)
                    #print(category_map[category][add][map[max_key]])
                    #print(category_map[category][add])
                    #print(category_map[category])
                    #new_map[map[max_key]] = new_map[map[max_key]] + float(max_val)
                except KeyError:
                    pass

    json.dump(category_map, open("map_dump.txt", 'w'))

word_freq()