在csv文件中排序

Question

我目前正在尝试创建一个csv文件，该文件包含人们迁移到的国家/地区，原始国家和目的地的坐标以及实际迁移的人口。我能够将这些信息输出到一个文件就好了，但我应该将输出csv从最高到最低人口排序，这是不行的。我知道我必须将所有字典附加到列表中，然后通过列表对填充计数进行排序，但我似乎无法弄清楚如何进行排序本身，然后在哪里放置代码以便它仍然输出正确的信息。换句话说，如果我把排序然后写入步骤放在我的for循环中太远了我只得到津巴布韦的信息，如果我把它放在代码中再也没有完成......任何想法都会非常感激，这是我的所有相关代码：

def edges_csv(filename, orgin_column, dest_column, count_column):
    edges_dict = defaultdict(list)
    with open(filename, 'r', newline = '') as input_file:
        # prepare to read the rows of the file using the csv packages' DictReader routines
        edges_reader = csv.DictReader(input_file, delimiter=',', quotechar ='"')

        for row in edges_reader:
            origin = row['Country Origin Name']
            dest = row['Country Dest Name']
            count = row['2000 [2000]']

            tuple = dest, count

            edges_dict[origin].append(tuple)

        for country in edges_dict:
            edge_sort = sorted(edges_dict[country], key=lambda x: x[1], reverse=True)

            edges_dict[country] = edge_sort


    return(edges_dict)

def nodes_csv(filename, country_column, lat_column, long_column):

    with open('locations.csv', 'r', newline = '') as input_file:
        # prepare to read the rows of the file using the csv packages' DictReader routines
        locations_reader = csv.DictReader(input_file, delimiter=',', quotechar ='"')
        graph = defaultdict(list)
        for row in locations_reader:
            country = row['Country Name']
            lat = row['Latitude']
            long = row['Longitude']

            tuple = lat, long

            graph[country].append(tuple)

    return (graph)

def main():

    # open the tab-delimited input data file
    with open('world_bank_country_data.txt', 'r', newline = '') as input_file:
        # prepare to read the rows of the file using the csv packages' DictReader routines
        country_data_reader = csv.DictReader(input_file, delimiter='\t', quotechar ='"')

        with open('edges.csv', 'w', newline='') as output_file_3:

            big_list = []
            row_count = 0

            # origin_dest_count = edges_csv('world_bank_migration.csv',
            #                               'origin', 'dest', 'count')

            lats_longs = nodes_csv('locations.csv',
                               'country', 'latitude', 'longitude')

            migration_outflow_graph = read_directed_graph_from_csv("world_bank_migration.csv",
                                                               "Country Origin Name", "Country Dest Name",
                                                               "2000 [2000]")
            edges_writer = csv.DictWriter(output_file_3,
                                             fieldnames=['start_country', 'end_country', 'start_lat', 'start_long', 'end_lat', 'end_long', 'count'],
                                             extrasaction='ignore',
                                             delimiter=',', quotechar='"')



            for country in migration_outflow_graph:
                edges_dict['start_country'] = country
                tuple = migration_outflow_graph[country]
                loc = lats_longs[country]
                for item in tuple:
                    edges_dict['end_country'] = item[0]
                    edges_dict['count'] = item[1]
                    count_sort = edges_dict['count']
                    end_country = edges_dict['end_country']
                    dest = lats_longs[end_country]

                    for thing in loc:
                        edges_dict['start_lat'] = thing[0]
                        edges_dict['start_long'] = thing[1]

                    for thing in dest:
                        edges_dict['end_lat'] = thing[0]
                        edges_dict['end_long'] = thing[1]
            # big_list = sorted(big_list, key = lambda x: x['count'], reverse = True)
            # print(big_list)
            # for elem in big_list:
            #     row_count = row_count + 1
            #     if row_count <= 1000:
            #         edges_writer.writerow(elem)

                        big_list.append(edges_dict)