使用python BeautifulSoup将Html抓取的数据转换为读写CSV文件

Question

>请找到以下链接：

http://www.bseindia.com/stock-share-price/stockreach_financials.aspx?scripcode=505200&expandable=0

我尝试了以下方法：

from bs4 import BeautifulSoup as soup
import csv
from pandas import read_csv
import requests
file_path=r'C:UsersPreciseT3DesktopEicherStockDetails.csv'
eicher_stock_url='http://www.bseindia.com/stock-share-price/stockreach_financials.aspx?scripcode=505200&expandable=0'
get_url=requests.get(eicher_stock_url)
target_table=soup(get_url.text,'lxml')
extracted_table_data=target_table.find('table',id='acr')
datasets=[]
col_names=[]
count=1
with open(file_path,'r+') as file:
 writer=csv.writer(file)
 col_names.append('Years')
 for years_row in extracted_table_data.find('tr').find_all('td',class_='TTHeader'):    
    if not(years_row.get_text()=='(in Cr.)'):
        print(years_row.get_text())
        col_names.append(years_row.get_text()) 
 writer.writerow(col_names)
with open(file_path,'r+') as file:
 writer=csv.writer(file)
 for row_headings in extracted_table_data.find('tr').find('td',class_='TTRow_left'):
  col_names.append(row_headings)
  for row_values in extracted_table_data.find('tr').find_all('td',class_='TTRow_right',text=lambda x:'6,188.03' in x or '3,031.22' in x or '1,702.47' in x or '1,049.26' in x or '670.95' in x):
   col_names.append(row_values.get_text())
 writer.writerow(col_names)

我的结果如下：

Years,2016,2014,2013,2012,2011,Revenue,"6,188.03","3,031.22","1,702.47","1,049.26",670.95

我的要求是：

• 而不是（（在 Cr.） 列名中，我需要将其更改为"年"

• 我需要探索它并希望将数据作为csv格式的文件（写入csv支持的文件中），并且我还想转置（T）行和列

• 我需要从另一个html页面添加一个额外的列（需要一些示例）

请帮助我。我不能再进一步了。提前谢谢。

Answer 1

我已经稍微修改了这段代码 - 但逻辑应该很简单。我使用 Cr 和 Year 作为此基本面分析数据的拆分器，但您也可以通过调整代码的"main_split"部分将其转换为百万/季度。

from bs4 import BeautifulSoup
import urllib2
import pandas as pd
url = 'http://www.bseindia.com/stock-share-price/stockreach_financials.aspx?scripcode=505200&expandable=0'
html = urllib2.urlopen(url).read()
soup = BeautifulSoup(html, "html.parser")
main = []
for tr in soup.findAll('tr'):
    mainSub = []
    for td in tr.findAll('td'):
        mainSub += [td.text]
    main += [mainSub]
splitter = []
for y in range(len(main)):
    splitter += [any('--' in x for x in main[y])]
split_index = [x for x in range(len(splitter)) if splitter[x] == True]
main_split = main[(split_index[7]+2):(split_index[8]-2)]

main_zip = zip(*main_split)
DF = pd.DataFrame(main_zip,columns=[x.replace(' ', '_') for x in main_zip.pop(0)])
print DF

希望这有帮助。干杯。