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。