刮除选择器JSON中的所有项目并导出到新单元格

我正在从JSON响应中抓取数据。我需要帮助刮取位置。有多个位置，我想知道是否有一种方法可以刮除所有位置。使用scrapy，我们可以执行.getall（）来获取所有值，但是我不确定JSON如何工作。另外，如果我们可以将每个位置存储到具有loc_1，loc_2，loc_3等标头的新单元格，那将是很好的。

以下是位置选择器的屏幕截图：

# -*- coding: utf-8 -*-
import scrapy
import json

links_list = open('test.txt').read().split('\n')

class MainSpider(scrapy.Spider):
    name = 'main'
    start_urls = links_list

    def parse(self, response):
        resp = json.loads(response.body)
        lists = resp['results']
        for each in lists:
            try:
                links = each['url']
                if links:
                    yield response.follow(url=f'https://www.cbr.nl{links}', callback=self.parse_lists)
            except:
                pass

    
    def parse_lists(self, response):
        # scraping school's info
        schools = json.loads(response.body)
        name = schools['name']
        type_ = schools['vehicleCategory']
        lat = schools['lat']
        lng = schools['lon']

        # school's exams info
        exams_taken = schools['examInformationAllLocations']['allAttempts']
        pass_percentage = schools['examInformationAllLocations']['successfulAllAttemptsPercentage']

        # scraping school's contact info
        street_name = schools['contactInformation']['streetName']
        house_number = schools['contactInformation']['houseNumber']
        house_num_ext = schools['contactInformation']['houseNumberExtension']
        zip_code = schools['contactInformation']['zipCode']
        city = schools['contactInformation']['city']
        website = schools['contactInformation']['website']
        email = schools['contactInformation']['email']
        phone_1 = schools['contactInformation']['phone1']
        phone_2 = schools['contactInformation']['phone2']
        kvk = schools['contactInformation']['kvk']
        driving_school_num = schools['contactInformation']['drivingSchoolNumber']
        trade_associations = schools['contactInformation']['tradeAssociations']

        # scraping school's exams info
        
 

        yield {
            "Name": name if name else "N/A",
            "Vehicle Type": type_ if type_ else "N/A",
            "Latitude": lat if lat else "N/A",
            "Longitude": lng if lng else "N/A",
            "Street Name": street_name if street_name else "N/A",
            "House Number": house_number if house_number else "N/A",
            "Hourse Number Extension": house_num_ext if house_num_ext else "N/A",
            "Zip Code": zip_code if zip_code else "N/A",
            "City": city if city else "N/A",
            "Website": website if website else "N/A",
            "Email": email if email else "N/A",
            "Phone 1": phone_1 if phone_1 else "N/A",
            "Phone 2": phone_2 if phone_2 else "N/A",
            "KVK": kvk if kvk else "N/A",
            "Driving School Number": driving_school_num if driving_school_num else "N/A",
            "Trade Associations": trade_associations if trade_associations else "N/A",
            "Exams Taken": exams_taken if exams_taken else "N/A",
            "Pass Percentage": pass_percentage if pass_percentage else "N/A",
        }