python财务数据怎么抓_python - 如何使用python每季度获取和特定雅虎财务数据的日期？ - SO中文参考 - www.soinside.com...

只是好奇，但为什么先将html写入文件然后用熊猫阅读？ Pandas可以直接接受html请求：

import pandas as pd

symbol = 'AAPL'

url = 'https://finance.yahoo.com/quote/%s/financials?p=%s' %(symbol, symbol)

dfs = pd.read_html(url)

print(dfs[0])

其次，不确定为什么你的年度日期突然出现。按照上面的方式行事就是九月。

print(dfs[0])

0 ... 4

0 Revenue ... 9/26/2015

1 Total Revenue ... 233715000

2 Cost of Revenue ... 140089000

3 Gross Profit ... 93626000

4 Operating Expenses ... Operating Expenses

5 Research Development ... 8067000

6 Selling General and Administrative ... 14329000

7 Non Recurring ... -

8 Others ... -

9 Total Operating Expenses ... 162485000

10 Operating Income or Loss ... 71230000

11 Income from Continuing Operations ... Income from Continuing Operations

12 Total Other Income/Expenses Net ... 1285000

13 Earnings Before Interest and Taxes ... 71230000

14 Interest Expense ... -733000

15 Income Before Tax ... 72515000

16 Income Tax Expense ... 19121000

17 Minority Interest ... -

18 Net Income From Continuing Ops ... 53394000

19 Non-recurring Events ... Non-recurring Events

20 Discontinued Operations ... -

21 Extraordinary Items ... -

22 Effect Of Accounting Changes ... -

23 Other Items ... -

24 Net Income ... Net Income

25 Net Income ... 53394000

26 Preferred Stock And Other Adjustments ... -

27 Net Income Applicable To Common Shares ... 53394000

[28 rows x 5 columns]

对于第二部分，您可以尝试通过以下几种方式查找数据1：

1)检查XHR请求并获取所需的数据，方法是将参数包含在生成该数据的请求URL中，并以json格式返回给您(当我查找时，我无法立即找到，所以继续到下一个选项)

2)搜索

3)使用selenium模拟打开浏览器，获取表格，然后单击“Quarterly”，然后获取该表

我选择了3：

from selenium import webdriver

import pandas as pd

symbol = 'AAPL'

url = 'https://finance.yahoo.com/quote/%s/financials?p=%s' %(symbol, symbol)

driver = webdriver.Chrome('C:/chromedriver_win32/chromedriver.exe')

driver.get(url)

# Get Table shown in browser

dfs_annual = pd.read_html(driver.page_source)

print(dfs_annual[0])

# Click "Quarterly"

driver.find_element_by_xpath("//span[text()='Quarterly']").click()

# Get Table shown in browser

dfs_quarter = pd.read_html(driver.page_source)

print(dfs_quarter[0])

driver.close()