Question

我使用BeautifulSoup进行网页抓取。所以我需要分析这个表：Google Finance
正如您所看到的那样，＆＃34;年度数据＆＃34;和＆＃34;季度数据＆＃34;。当我提取表python只返回季度数据但我不知道如何提取年度。有人知道吗？下面是代表此链接的HTML代码。

＆＃13;

<div class="g-unit g-first">
View:
<a id="interim" class="id-interim nac" target="_blank">Quarterly Data</a>&nbsp;|&nbsp;
<a id="annual" class="id-annual ac" target="_blank">Annual Data</a>
</div>

＆＃13;

这是我的代码：

import requests
from bs4 import BeautifulSoup
import pandas as pd

raw_data = {'Param': ['Total Revenue', 'Cost of revenue', 'Gross profit', 
                      'Operating expenses','Research Development'],
             '2016': [123, 234343, 3423, 343, 323],
             '2015': [3432423, 2342, 2342342, 356856, 36934],
             '2014': [42, 52, 36, 24, 73],
             '2013': [42, 52, 36, 24, 73]}

url = 'https://www.google.com/finance?q=NASDAQ%3AAAPL&fstype=ii&ei=JQHoWMjKCcjDsAHAhqS4DA'

r = requests.get(url)
soup = BeautifulSoup(r.text, 'lxml')
raw_df = pd.DataFrame(raw_data, columns = ['Param', '2016', '2015', '2014','2013'])

# Find all the <tr> tag pairs, skip the first one, then for each.

for row in table.find_all('tr')[1:]:
    col = row.find_all('td')
    column_1 = col[0].string.strip()
    Revenue.append(column_1)

    column_2 = col[1].string.strip()
    _2016_.append(column_2)

    column_3 = col[2].string.strip()
    _2015_.append(column_3)

    column_4 = col[3].string.strip()
    _2014_.append(column_4)

    column_5 = col[4].string.strip()
    _2013_.append(column_5)

columns = {'In Millions of USD': Revenue, '52 weeks ending 2016': _2016_, '52 weeks ending 2015': _2015_, '52 weeks ending 2014': _2014_, '52 weeks ending 2013': _2013_}
df = pd.DataFrame(columns)

Answer 1

您的代码无效，但我知道您真正想要的是什么。您希望将年度数据汇总到熊猫数据框中。希望这可以帮助。

import requests
from bs4 import BeautifulSoup
import pandas as pd

params, _2016_, _2015_, _2014_, _2013_ = [], [], [], [], []
url = 'https://www.google.com/finance?q=NASDAQ%3AAAPL&fstype=ii&ei=JQHoWMjKCcjDsAHAhqS4DA'

r = requests.get(url)
soup = BeautifulSoup(r.text, 'lxml')
#print(soup)                                             #to get an idea on the class id
table = soup.find("div", {"class": "id-incannualdiv"})   #this is the table for annual data report
rows = [t.text for t in table.find_all("td")]            #get all rows then convert rows into columns
i=0
for r in rows:
    if i%5 == 0:
        params.append(r.rstrip("\r\n"))
    if i%5 == 1:
        _2016_.append(r)
    if i%5 == 2:
        _2015_.append(r)
    if i%5 == 3:
        _2014_.append(r)
    if i%5 == 4:
        _2013_.append(r)
    i+=1
df = pd.DataFrame(list(zip(params, _2016_, _2015_, _2014_, _2013_)), \
 columns=['In Millions of USD', '52 weeks ending 2016', '52 weeks ending 2015', '52 weeks ending 2014', '52 weeks ending 2013'])
df.head()

Answer 2

只需将表数组添加为包含年度，夸脱数据表

import requests
from bs4 import BeautifulSoup
import pandas as pd

raw_data = {'Param': ['Total Revenue', 'Cost of revenue', 'Gross profit', 
                      'Operating expenses','Research Development'],
             '2016': [123, 234343, 3423, 343, 323],
             '2015': [3432423, 2342, 2342342, 356856, 36934],
             '2014': [42, 52, 36, 24, 73],
             '2013': [42, 52, 36, 24, 73]}

url = 'https://www.google.com/finance?q=NASDAQ%3AAAPL&fstype=ii&ei=JQHoWMjKCcjDsAHAhqS4DA'

r = requests.get(url)
soup = BeautifulSoup(r.text, 'lxml')
raw_df = pd.DataFrame(raw_data, columns = ['Param', '2016', '2015', '2014','2013'])
Revenue,_2016_,_2015_,_2014_,_2013_=[],[],[],[],[]
# Find all the <tr> tag pairs, skip the first one, then for each.
table=soup.find_all('table')[1:3]
for tab in table:
    for row in tab.find_all('tr')[1:]:
        col = row.find_all('td')
        column_1 = col[0].string.strip()
        Revenue.append(column_1)

        column_2 = col[1].string.strip()
        _2016_.append(column_2)

        column_3 = col[2].string.strip()
        _2015_.append(column_3)

        column_4 = col[3].string.strip()
        _2014_.append(column_4)

        column_5 = col[4].string.strip()
        _2013_.append(column_5)

columns = {'In Millions of USD': Revenue, '52 weeks ending 2016': _2016_, '52 weeks ending 2015': _2015_, '52 weeks ending 2014': _2014_, '52 weeks ending 2013': _2013_}
df = pd.DataFrame(columns)

网络抓取。在Python中如何使用活动链接进行操作？

2 个答案: