如何从不一致中获得一致性输出答案

【问题标题】：How to get consistency output from inconsistency如何从不一致中获得一致性输出
【发布时间】：2021-12-31 10:28:28
【问题描述】：

我想一次获取所有 name 和 price 键，但所有第一个 dict 键的顺序不同，我无法迭代，这就是为什么我必须进行一些预处理但输出不一致的原因。

电流输出：

                        Name                                              Price
0  Half-Life: Opposing Force  [{'id': 32, 'discount_block': '<div class="dis...
1                  Half-Life  [{'id': 34, 'discount_block': '<div class="dis...
2                Half-Life 2  [{'id': 36, 'discount_block': '<div class="dis...
3   Half-Life 2: Episode Two  [{'id': 516, 'discount_block': '<div class="di...
4                    Cuphead  [{'id': 35659, 'discount_block': '<div class="...
5           Steam Controller                                                 []
6                  PCMark 10  [{'id': 125001, 'discount_block': '<div class=...
7     Kerbal Space Program 2                                                 []
8    Hollow Knight: Silksong

预期输出：

               name           price
0 Half-Life: Opposing Force     59
1                  Half-Life    109
2                Half-Life 2    109
3   Half-Life 2: Episode Two    89
4                    Cuphead    573
5           Steam Controller    []# meaning None
6                  PCMark 10    157
7     Kerbal Space Program 2    []
8    Hollow Knight: Silksong    []

脚本：

import re
import json
import requests
import pandas as pd

url = 'https://store.steampowered.com/wishlist/id/zorro4/#sort=order'
wishlist_url =  json.loads( re.findall(r'g_strWishlistBaseURL = (".*?");', requests.get(url).text)[0] )
#print(wishlist_url)

data = requests.get(wishlist_url + 'wishlistdata/?p=0').json()

#print(wishlist_url + 'wishlistdata/?p=0')

# jsn_data=json.dumps(data, indent=4)
# with open('da.json','w') as f:
#     f.write(jsn_data)
names = [d['name'] for d in data.values()]
# print(names)

out = list(map(lambda x: x['subs'], data.values()))
p=[]
for i in out:
    for t in i:
        q=t['price']
        p.append(q)
        #print(q)

df = pd.DataFrame(data=list(zip(names, out)), columns=['Name', 'Price'])
print(df)

【问题讨论】：

标签： python python-3.x pandas web-scraping beautifulsoup

【解决方案1】：

遍历data，您可以在list 中提取数据使用index 位置，它给出html 标签现在使用bs4 查找到目前为止，我已经采取了discount_final_price 的具体价格输出。

并将您的数据附加到lst，以便返回值列表和使用pandas 创建df 并将数据作为lst 和列作为您想要

import numpy as np
lst=[]
for key,value in data.items():
    try:
        name=value['name']
        price_data=value['subs'][0]['discount_block']
        soup=BeautifulSoup(price_data,"html.parser")
        price=soup.find("div",class_="discount_final_price").get_text().split(" ")[-1]
    except:
        price=np.nan
    lst.append([name,price])

输出：

                name          price
0   Half-Life: Opposing Force   39
1   Half-Life                   69
2   Half-Life 2                 69
3   Half-Life 2: Episode Two    59
4   Cuphead                     395
5   Steam Controller            NaN
6   PCMark 10                   104
7   Kerbal Space Program 2      NaN
8   Hollow Knight: Silksong     NaN

【讨论】：