Python基于pandas实现json格式转换成dataframe的方法

本文实例讲述了Python基于pandas实现json格式转换成dataframe的方法。分享给大家供大家参考，具体如下：

# -*- coding:utf-8 -*-
#!python3
import re
import json
from bs4 import BeautifulSoup
import pandas as pd
import requests
import os
from pandas.io.json import json_normalize
class image_structs():
 def __init__(self):
   self.picture_url = {
     "image_id": '',
     "picture_url": ''
   }
class data_structs():
 def __init__(self):
   # columns=['title', 'item_url', 'id','picture_url','std_desc','description','information','fitment'])
   self.info={
     "title":'',
     "item_url":'',
     "id":0,
     "picture_url":[],
     "std_desc":'',
     "description":'',
     "information":'',
     "fitment":''
   }
# "https://waldoch.com/store/catalogsearch/result/index/?cat=0&limit=200&p=1&q=nerf+bar"
# https://waldoch.com/store/new-oem-ford-f-150-f150-5-running-boards-nerf-bar-crew-cab-2015-w-brackets-fl34-16451-ge5fm6.html
def get_item_list(outfile):
 result = []
 for i in range(6):
   print(i)
   i = str(i+1)
   url = "https://waldoch.com/store/catalogsearch/result/index/?cat=0&limit=200&p="+i+"&q=nerf+bar"
   web = requests.get(url)
   soup = BeautifulSoup(web.text,"html.parser")
   alink = soup.find_all("a",class_="product-image")
   for a in alink:
     title = a["title"]
     item_url = a["href"]
     result.append([title,item_url])
 df = pd.DataFrame(result,columns=["title","item_url"])
 df = df.drop_duplicates()
 df["id"] =df.index
 df.to_excel(outfile,index=False)
def get_item_info(file,outfile):
 DEFAULT_FALSE = ""
 df = pd.read_excel(file)
 for i in df.index:
   id = df.loc[i,"id"]
   if os.path.exists(str(int(id))+".xlsx"):
     continue
   item_url = df.loc[i,"item_url"]
   url = item_url
   web = requests.get(url)
   soup = BeautifulSoup(web.text, "html.parser")
   # 图片
   imglink = soup.find_all("img", class_=re.compile("^gallery-image"))
   data = data_structs()
   data.info["title"] = df.loc[i,"title"]
   data.info["id"] = id
   data.info["item_url"] = item_url
   for a in imglink:
     image = image_structs()
     image.picture_url["image_id"] = a["id"]
     image.picture_url["picture_url"]=a["src"]
     print(image.picture_url)
     data.info["picture_url"].append(image.picture_url)
   print(data.info)
   # std_desc
   std_desc = soup.find("div", itemprop="description")
   try:
     strings_desc = []
     for ii in std_desc.stripped_strings:
       strings_desc.append(ii)
     strings_desc = "\n".join(strings_desc)
   except:
     strings_desc=DEFAULT_FALSE
   # description
   try:
     desc = soup.find('h2', text="Description")
     desc = desc.find_next()
   except:
     desc=DEFAULT_FALSE
   description=desc
   # information
   try:
     information = soup.find("h2", text='Information')
     desc = information
     desc = desc.find_next()
   except:
     desc=DEFAULT_FALSE
   information = desc
   # fitment
   try:
     fitment = soup.find('h2', text='Fitment')
     desc = fitment
     desc = desc.find_next()
   except:
     desc=DEFAULT_FALSE
   fitment=desc
   data.info["std_desc"] = strings_desc
   data.info["description"] = str(description)
   data.info["information"] = str(information)
   data.info["fitment"] = str(fitment)
   print(data.info.keys())
   singledf = json_normalize(data.info,"picture_url",['title', 'item_url', 'id', 'std_desc', 'description', 'information', 'fitment'])
   singledf.to_excel("test.xlsx",index=False)
   exit()
   # print(df.ix[i])
 df.to_excel(outfile,index=False)
# get_item_list("item_urls.xlsx")
get_item_info("item_urls.xlsx","item_urls_info.xlsx")

这里涉及到的几个Python模块都可以使用pip install命令进行安装，如：

pip install BeautifulSoup4

pip install xlrd

pip install openpyxl

PS：这里再为大家推荐几款比较实用的json在线工具供大家参考使用：

在线JSON代码检验、检验、美化、格式化工具：
http://tools.jb51.net/code/json

JSON在线格式化工具：
http://tools.jb51.net/code/jsonformat

在线XML/JSON互相转换工具：
http://tools.jb51.net/code/xmljson

json代码在线格式化/美化/压缩/编辑/转换工具：
http://tools.jb51.net/code/jsoncodeformat

在线json压缩/转义工具：
http://tools.jb51.net/code/json_yasuo_trans

更多Python相关内容感兴趣的读者可查看本站专题：《Python操作json技巧总结》、《Python编码操作技巧总结》、《Python数据结构与算法教程》、《Python函数使用技巧总结》、《Python字符串操作技巧汇总》、《Python入门与进阶经典教程》及《Python文件与目录操作技巧汇总》

希望本文所述对大家Python程序设计有所帮助。

来源：https://blog.csdn.net/zn505119020/article/details/78964111