熊猫的表格格式不正确答案

【问题标题】：Tables from panda is not properly formatted熊猫的表格格式不正确
【发布时间】：2020-08-14 07:03:48
【问题描述】：

我正在尝试使用 pandas 将字典项转换为表格，但问题是我没有得到想要的结果。下面是我的代码

value = new_stock(data)


dict_stocks = {i: value[i] for i in range (0, len(value))}

df = pd.DataFrame(list(dict_stocks.items()), columns =['Company Name', 'Price per share', Total valuation])

print(df)

我希望输出像

Company name                           price per share       Total valuation
Norwegian Cruise Line Holdings Ltd.', '16.41 Dollars', '3498661376 billion dollars'
Carnival Corporation & Plc', '15.5 Dollars', '10927298560 billion dollars'

但我的输出是这种格式。

Company Name                                    Price per share
0              0  (Norwegian Cruise Line Holdings Ltd., 16.41 Do...
1              1  (Carnival Corporation & Plc, 15.5 Dollars, 109...
2              2  (Noble Energy, Inc., 10.05 Dollars, 4874652160...
3              3  (Apache Corporation, 13.05 Dollars, 4925304832...
4              4  (Companhia Siderurgica Nacional, 1.66 Dollars,...
5              5  (DCP Midstream, LP, 10.03 Dollars, 2089549824 ...
6              6  (Sabre Corporation, 7.4 Dollars, 2025794432 bi...
7              7  (Sasol Limited, 5.13 Dollars, 3016778496 billi...
8              8  (Continental Resources, Inc., 15.85 Dollars, 5...
9              9  (Marathon Oil Corporation, 5.85 Dollars, 46239...
10            10  (AerCap Holdings N.V., 28.47 Dollars, 37461678...
11            11  (Penn National Gaming, Inc., 18.61 Dollars, 21...
12            12  (Royal Caribbean Cruises Ltd., 48.06 Dollars, ...
13            13  (Canadian Natural Resources Limited, 17.38 Dol...
14            14  (WPX Energy, Inc., 6.08 Dollars, 3400939008 bi...
15            15  (Ryman Hospitality Properties, Inc., 37.78 Dol...
16            16  (TechnipFMC plc, 9.27 Dollars, 4124464384 bill...
17            17  (Diamondback Energy, Inc., 44.19 Dollars, 6973...
18            18  (Santander Consumer USA Holdings Inc., 17.05 D...
19            19  (Marathon Petroleum Corporation, 33.04 Dollars...
20            20  (Air Lease Corporation, 26.72 Dollars, 3036327...
21            21  (Carnival Corporation & Plc, 16.69 Dollars, 13...
22            22  (Howmet Aerospace Inc., 13.89 Dollars, 6054915...
23            23  (Aaron's, Inc., 32.33 Dollars, 2184589824 bill...
24            24  (Tata Motors Limited, 5.88 Dollars, 3851547136...

如果提供任何帮助，我将不胜感激

******附加**** 这是剩下的部分代码

import requests
import pprint
import json
import pandas as pd


url = "https://yahoo-finance15.p.rapidapi.com/api/yahoo/ga/topgainers"

querystring = {"start":"0"}

headers = {
    'x-rapidapi-host': "yahoo-finance15.p.rapidapi.com",
    'x-rapidapi-key': "9efd0f3e52mshd859f5daf34a429p11cb2ajsn2b0e421d681e"
    }

response = requests.request("GET", url, headers=headers, params=querystring)
data = response.json()

#print(response.text)


def new_stock(data):
    new_market = []

    for item in data ['quotes']:
        new_name = item.get ('longName')
        new_price = item.get ('regularMarketPrice')
        res_price = (f'{new_price} Dollars')
        cap =item.get('marketCap')
        if cap >= 1000000000:
            cap = f'{cap} billion dollars'
        else:
            cap = f'{cap} million dollars'
        new_market.append((new_name, res_price, cap))

    return new_market

value = new_stock(data)

【问题讨论】：

你能分享变量值的一个子集吗？
请分享您的dictionary。
@MayankPorwal 更新
@datanovice 更新

标签： python pandas dictionary tuples

【解决方案1】：

我想这就是你想要的：

In [403]: value = [('Norwegian Cruise Line Holdings Ltd.', 
     ...:   '16.41 Dollars', 
     ...:   '3498661376 billion dollars'), 
     ...:  ('Carnival Corporation & Plc', '15.5 Dollars', '10927298560 billion dollars'), 
     ...:  ('Noble Energy, Inc.', '10.05 Dollars', '4874652160 billion dollars'), 
     ...:  ('Apache Corporation', '13.05 Dollars', '4925304832 billion dollars'), 
     ...:  ('Companhia Siderurgica Nacional', 
     ...:   '1.66 Dollars', 
     ...:   '1905845888 billion dollars'), 
     ...:  ('DCP Midstream, LP', '10.03 Dollars', '2089549824 billion dollars')]

In [407]: df = pd.DataFrame(value, columns=['Company name','price per share','Total valuation'])                                                                                                            

In [408]: df                                                                                                                                                                                                
Out[408]: 
                          Company name price per share              Total valuation
0  Norwegian Cruise Line Holdings Ltd.   16.41 Dollars   3498661376 billion dollars
1           Carnival Corporation & Plc    15.5 Dollars  10927298560 billion dollars
2                   Noble Energy, Inc.   10.05 Dollars   4874652160 billion dollars
3                   Apache Corporation   13.05 Dollars   4925304832 billion dollars
4       Companhia Siderurgica Nacional    1.66 Dollars   1905845888 billion dollars
5                    DCP Midstream, LP   10.03 Dollars   2089549824 billion dollars

【讨论】：