Python全面解析json数据并保存为csv文件

Python全面解析json数据并保存为csv文件

目录

解析json数据并保存为csv文件

完整代码

将json任意行文件转为csv文件并保存

将json格式的前3000条数据存入csv

解析json数据并保存为csv文件

首先导入两个包:

import json import pandas as pd

打开json 文件并读取:

with open('2.json', encoding='utf-8') as f:     line = f.readline()     d = json.loads(line)     f.close()

读取的json数据会以字典的形势保存,按照字典的读取方式获取自己想要的数据:

datas_x = [] datas_y = [] for dss in d:     datas_x.append(float(dss["pos"]["x"]))     datas_y.append(float(dss["pos"]["z"]))

将数据保存到列表中,然后创建pandas的DataFrame,DataFrame是由多种类型的列构成的二维标签数据结构。

path_x = pd.Series(datas_x) path_y = pd.Series(datas_y) path_df = pd.DataFrame() path_df['pathx'] = path_x path_df['pathy'] = path_y

最后将数据保存到csv中。

filepath = "E:\\python\\python\\2021\\202104\\0409\\path_data.csv" path_df.to_csv(filepath, index=False, header=False) 完整代码 import json import pandas as pd filepath = "E:\\python\\python\\2021\\202104\\0409\\path_data.csv" with open('2.json', encoding='utf-8') as f:     line = f.readline()     d = json.loads(line)     f.close() datas_x = [] datas_y = [] for dss in d:     datas_x.append(float(dss["pos"]["x"]))     datas_y.append(float(dss["pos"]["z"])) path_x = pd.Series(datas_x) path_y = pd.Series(datas_y) path_df = pd.DataFrame() path_df['pathx'] = path_x path_df['pathy'] = path_y path_df.to_csv(filepath, index=False, header=False) 将json任意行文件转为csv文件并保存 将json格式的前3000条数据存入csv

json格式类型:

{"address": "华山路31号", "addressExtend": "屯溪老街", "amenities": [1, 2, 3, 5, 10, 12], "brandName": null, "businessZoneList": null, "cityCode": 1004, "cityName": "黄山", "coverImageUrl": "https://img20.360buyimg.com/hotel/jfs/t16351/270/1836534312/106914/9b443bc4/5a68e68aN23bfaeda.webp", "districtName": "屯溪区", "geoInfo": {"distance": 3669, "name": "市中心", "type": 1, "typeName": "市中心"}, "grade": 5, "hotelId": 328618, "location": {"lat": "29.717982", "lon": "118.299707"}, "name": "黄山国际大酒店", "payMode": [1, 2], "price": 362, "priceStatus": 1, "promotion": [103], "saleType": 1, "score": 4.8, "star": 5, "themes": [3, 2, 4], "totalComments": 133} {"address": "金城镇 珠山82号", "addressExtend": "", "amenities": null, "brandName": null, "businessZoneList": [{"businessZoneId": 2384, "businessZoneName": "金门机场", "poiType": null}], "cityCode": 1174, "cityName": "泉州", "coverImageUrl": null, "districtName": null, "geoInfo": {"distance": 63229, "name": "市中心", "type": 1, "typeName": "市中心"}, "grade": 2, "hotelId": 763319, "location": {"lat": "24.396442", "lon": "118.314335"}, "name": "金门珠山82号民宿", "payMode": null, "price": null, "priceStatus": 1, "promotion": null, "saleType": 0, "score": null, "star": 0, "themes": [], "totalComments": null}

json转为csv

import csv import json import codecs ''' 将json文件格式转为csv文件格式并保存。 ''' class Json_Csv(): #初始化方法,创建csv文件。 def __init__(self): self.save_csv = open('D:/hotels_out.csv', 'w', encoding='utf-8', newline='') self.write_csv = csv.writer(self.save_csv, delimiter=',') #以,为分隔符 def trans(self,filename): with codecs.open(filename,'r',encoding='utf-8') as f: read=f.readlines() flag=True for index,info in enumerate(read): data=json.loads(info) if index <3000: #读取json文件的前3000行写入csv文件 。要是想写入全部,则去掉判断。 if flag: #截断第一行当做head keys=list(data.keys()) #将得到的keys用列表的形式封装好,才能写入csv self.write_csv.writerow(keys) flag=False #释放 value=list(data.values()) #写入values,也要是列表形式 self.write_csv.writerow(value) self.save_csv.close() #写完就关闭 if __name__=='__main__': json_csv=Json_Csv() path='D:/hotels.txt' json_csv.trans(path)

以上为个人经验,希望能给大家一个参考,也希望大家多多支持易知道(ezd.cc)。 

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