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 -*-#!python3import reimport jsonfrom bs4 import BeautifulSoupimport pandas as pdimport requestsimport osfrom pandas.io.json import json_normalizeclass 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.htmldef 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")