Python 网页抓取问题，试图将信息获取到csv和图表中

这是我的密码。它给了我非常完整的信息。我正在整理我最喜欢的10家航天科技公司的股票价格。我想得到10个小时内的股票价格，或者我可以只运行代码10次。我不能使用api。这是一个学校项目。然后，我想用matplotlib将所有数据合并成十个一个大图表，显示这些股票价格。或者每只股票十张图表。我想用这种类型的图表

任何建议都会很棒。这是我目前的代码：

#import libraries
import pandas as pd

#scraping my top ten favorite space companies, attempted to pick compaines with pure play interest in space
urls = ['https://finance.yahoo.com/quote/GILT/', 'https://finance.yahoo.com/quote/LORL?p=LORL&.tsrc=fin-srch', 'https://finance.yahoo.com/quote/I?p=I&.tsrc=fin-srch' , 'https://finance.yahoo.com/quote/VSAT?p=VSAT&.tsrc=fin-srch', 'https://finance.yahoo.com/quote/RTN?p=RTN&.tsrc=fin-srch', 'https://finance.yahoo.com/quote/UTX?ltr=1', 'https://finance.yahoo.com/quote/TDY?ltr=1', 'https://finance.yahoo.com/quote/ORBC?ltr=1', 'https://finance.yahoo.com/quote/SPCE?p=SPCE&.tsrc=fin-srch', 'https://finance.yahoo.com/quote/BA?p=BA&.tsrc=fin-srch',]

def  parsePrice(r):
    df = pd.read_html(r)[0].T
    cols = list(df.iloc[0,:])
    temp_df = pd.DataFrame([list(df.iloc[1,:])], columns=cols)
    temp_df['url'] = r
    return temp_df
df = pd.DataFrame()
for r in urls:
   df = df.append(parsePrice(r), sort=True).reset_index(drop=True)
df.to_csv('C:/Users/n_gor/Desktop/webscape/Nicholas Final Projects/spacestocklisting.csv', index=False)
print (df.to_string())

CSV文件输出：

     52 Week Range            Ask Avg. Volume           Bid      Day's Range    Open Previous Close   Volume                                                url
0      7.32 - 9.87     8.09 x 800       23415    8.06 x 800      8.01 - 8.11    8.10           8.01     6337              https://finance.yahoo.com/quote/GILT/
1    32.14 - 42.77   32.74 x 1100       41759  32.59 x 1000    32.28 - 32.75   32.32          32.28    14685  https://finance.yahoo.com/quote/LORL?p=LORL&.t...
2     5.55 - 27.29     6.64 x 800     5746553   6.63 x 2900      6.51 - 6.68    6.64           6.65   995245  https://finance.yahoo.com/quote/I?p=I&.tsrc=fi...
3    55.93 - 97.31    72.21 x 800      281600  72.16 x 1000    71.51 - 72.80   72.26          72.32    74758  https://finance.yahoo.com/quote/VSAT?p=VSAT&.t...
4  144.27 - 220.03  215.54 x 1000     1560562  215.37 x 800  214.87 - 217.45  215.85         214.86   203957  https://finance.yahoo.com/quote/RTN?p=RTN&.tsr...
5  100.48 - 149.81   145.03 x 800     2749725  144.96 x 800  144.41 - 145.56  145.49         144.52   489169          https://finance.yahoo.com/quote/UTX?ltr=1
6  189.35 - 351.53   343.34 x 800      280325  342.80 x 800  342.84 - 346.29  344.16         343.58    42326          https://finance.yahoo.com/quote/TDY?ltr=1
7  3.5800 - 9.7900  4.1400 x 1300      778343  4.1300 x 800  4.1200 - 4.2000  4.1700         4.1500    62335         https://finance.yahoo.com/quote/ORBC?ltr=1
8     6.90 - 12.09     7.37 x 900     2280333    7.38 x 800      7.24 - 7.48    7.30           7.22   539082  https://finance.yahoo.com/quote/SPCE?p=SPCE&.t...
9  292.47 - 446.01   348.73 x 800     4420225  348.79 x 800  345.70 - 350.42  350.22         348.84  1258813  https://finance.yahoo.com/quote/BA?p=BA&.tsrc=...

我可以把股票的名字加进去吗？关于如何完成这个项目有什么建议吗？我有点迷路了。

你可以用

如果列表中有所有股票名称

stock_names = ['GILT', 'LORL', 'I', 'VSAT', 'RTN', 'UTX', 'TDY', 'ORBC', 'SPCE', 'BA']
# insert to the begining(column at index 0) of the dataFrame 
df.insert(0, "column_heading", stock_names) 

或者，您可以使用正则表达式从URL获取所有股票名称，并将其添加到df中

import re
stock_names= [re.findall('[A-Z]+',x)[0] for x in urls]
# insert to the begining(column at index 0) of the dataFrame 
df.insert(0, "column_heading", stock_names)

你可以用

如果列表中有所有股票名称

stock_names = ['GILT', 'LORL', 'I', 'VSAT', 'RTN', 'UTX', 'TDY', 'ORBC', 'SPCE', 'BA']
# insert to the begining(column at index 0) of the dataFrame 
df.insert(0, "column_heading", stock_names) 

或者，您可以使用正则表达式从URL获取所有股票名称，并将其添加到df中

import re
stock_names= [re.findall('[A-Z]+',x)[0] for x in urls]
# insert to the begining(column at index 0) of the dataFrame 
df.insert(0, "column_heading", stock_names)

---

只需解析标题标题：

#import libraries
import pandas as pd
import requests
from bs4 import BeautifulSoup

#scraping my top ten favorite space companies, attempted to pick compaines with pure play interest in space
urls = ['https://finance.yahoo.com/quote/GILT/', 'https://finance.yahoo.com/quote/LORL?p=LORL&.tsrc=fin-srch', 'https://finance.yahoo.com/quote/I?p=I&.tsrc=fin-srch' , 'https://finance.yahoo.com/quote/VSAT?p=VSAT&.tsrc=fin-srch', 'https://finance.yahoo.com/quote/RTN?p=RTN&.tsrc=fin-srch', 'https://finance.yahoo.com/quote/UTX?ltr=1', 'https://finance.yahoo.com/quote/TDY?ltr=1', 'https://finance.yahoo.com/quote/ORBC?ltr=1', 'https://finance.yahoo.com/quote/SPCE?p=SPCE&.tsrc=fin-srch', 'https://finance.yahoo.com/quote/BA?p=BA&.tsrc=fin-srch',]

def  parsePrice(r):
    response = requests.get(r)
    soup = BeautifulSoup(response.text,  'html.parser')
    titleHeader = soup.find('div', {'id':'quote-header-info'})
    title = titleHeader.find('h1').text
    comp = title.split('-')[-1].strip()
    abr = title.split('-')[0].strip()


    print (title)

    df = pd.read_html(response.text)[0].T
    cols = list(df.iloc[0,:])
    temp_df = pd.DataFrame([list(df.iloc[1,:])], columns=cols)
    temp_df['url'] = r
    temp_df['company name'] = comp
    temp_df['stock name'] = abr
    return temp_df

df = pd.DataFrame()

for r in urls:
   df = df.append(parsePrice(r), sort=True).reset_index(drop=True)


df.to_csv('C:/Users/n_gor/Desktop/webscape/Nicholas Final Projects/spacestocklisting.csv', index=False)
print (df.to_string())

---

只需解析标题标题：

#import libraries
import pandas as pd
import requests
from bs4 import BeautifulSoup

#scraping my top ten favorite space companies, attempted to pick compaines with pure play interest in space
urls = ['https://finance.yahoo.com/quote/GILT/', 'https://finance.yahoo.com/quote/LORL?p=LORL&.tsrc=fin-srch', 'https://finance.yahoo.com/quote/I?p=I&.tsrc=fin-srch' , 'https://finance.yahoo.com/quote/VSAT?p=VSAT&.tsrc=fin-srch', 'https://finance.yahoo.com/quote/RTN?p=RTN&.tsrc=fin-srch', 'https://finance.yahoo.com/quote/UTX?ltr=1', 'https://finance.yahoo.com/quote/TDY?ltr=1', 'https://finance.yahoo.com/quote/ORBC?ltr=1', 'https://finance.yahoo.com/quote/SPCE?p=SPCE&.tsrc=fin-srch', 'https://finance.yahoo.com/quote/BA?p=BA&.tsrc=fin-srch',]

def  parsePrice(r):
    response = requests.get(r)
    soup = BeautifulSoup(response.text,  'html.parser')
    titleHeader = soup.find('div', {'id':'quote-header-info'})
    title = titleHeader.find('h1').text
    comp = title.split('-')[-1].strip()
    abr = title.split('-')[0].strip()


    print (title)

    df = pd.read_html(response.text)[0].T
    cols = list(df.iloc[0,:])
    temp_df = pd.DataFrame([list(df.iloc[1,:])], columns=cols)
    temp_df['url'] = r
    temp_df['company name'] = comp
    temp_df['stock name'] = abr
    return temp_df

df = pd.DataFrame()

for r in urls:
   df = df.append(parsePrice(r), sort=True).reset_index(drop=True)


df.to_csv('C:/Users/n_gor/Desktop/webscape/Nicholas Final Projects/spacestocklisting.csv', index=False)
print (df.to_string())

---

我想得到10个小时的股票价格，或者我可能只需要运行代码10次。我不能使用api。这是一个学校项目。然后，我想用matplotlib将所有数据合并成十个一个大图表，显示这些股票价格。或者每只股票有十张图表。雅虎只提供每日股票数据，你确定你想要每小时的数据，还是过去10个交易日的每日数据？好的，这个项目只需要在周一之前交上来，这样我就可以在接下来的3天内每天做一次。我更愿意在周日晚上把它交上来，我想得到10个小时的股票价格，或者我可以只运行代码10次。我不能使用api。这是一个学校项目。然后，我想用matplotlib将所有数据合并成十个一个大图表，显示这些股票价格。或者每只股票有十张图表。雅虎只提供每日股票数据，你确定你想要每小时的数据，还是过去10个交易日的每日数据？好的，这个项目只需要在周一之前交上来，这样我就可以在接下来的3天内每天做一次。我更愿意在周日晚上交。如果你需要在messenger上聊天，我会在附近。给我发电子邮件给杰森。schvach@gmail.com@是的。太棒了。。我给你发了电子邮件。希望收到你的来信如果你需要在messenger上聊天，我会在附近。给我发电子邮件给杰森。schvach@gmail.com@是的。太棒了。。我给你发了电子邮件。希望收到你的来信