python - 合并财务数据

Question

我试图弄清楚如何从雅虎财经获取财务信息(损益表、 Assets 负债表和现金流量)。我有一个名为符号的列表，其中包含所有股票代码(请参阅下面的代码)。最终我想要最终得到一个 csv，其中包含 4 年(2018 年、2017 年、2016 年、2015 年)连接的行。'''我可以手动执行此操作，但我想做的是自动执行此操作，以便我可以返回包含所有相关信息的 .csv 文件(77 列和 4*#ticker 符号行) 将上图变成:

我已经弄清楚如何使用抓取工具从雅虎抓取数据。

from lxml import html
from lxml import html
import requests

import numpy as np

import pandas as pd
def scrape_table(url):
    page = requests.get(url)
    tree = html.fromstring(page.content)
    table = tree.xpath('//table')
    assert len(table) == 1

    df = pd.read_html(lxml.etree.tostring(table[0], method='html'))[0]

    df = df.set_index(0)
    df = df.dropna()
    df = df.transpose()
    df = df.replace('-', '0')

    # The first column should be a date
    df[df.columns[0]] = pd.to_datetime(df[df.columns[0]])
    cols = list(df.columns)
    cols[0] = 'Date'
    df = df.set_axis(cols, axis='columns', inplace=False)

    numeric_columns = list(df.columns)[1::]
    df[numeric_columns] = df[numeric_columns].astype(np.float64)

    return df



def merge_IS_BS_CF(df_IS, df_BS, df_CF):
    #merge the three financial statements - Income statement, balance sheet, cash flow into one dataframe
    #return the dataframe
    df_merge_IS_BS = pd.merge(df_IS, df_BS, on='Date')
    df_merge_IS_BS_CF = pd.merge(df_merge_IS_BS, df_CF, on='Date')
    return df_merge_IS_BS_CF

symbols = ['AAPL', 'MFT.NZ']

financials = {}
#create a dictionary of ticker names and their respective statements' urls
for symbol in symbols:
    financials[symbol] = ['https://finance.yahoo.com/quote/' + symbol + '/financials?p=' + symbol, 'https://finance.yahoo.com/quote/' + symbol + '/balance-sheet?p=' + symbol, 'https://finance.yahoo.com/quote/' + symbol + '/cash-flow?p=' + symbol]
print (financials['AAPL'][0])
data = pd.DataFrame([])

我得到的结果是它没有将下一个股票行情数据连接到 pandas 数据框中。感谢您的帮助。

Answer 1

抱歉，这是我自己想出来的。对于下一个人，我的错误是没有意识到我必须保存附加的数据框。

symbols = ['AAPL', 'MFT.NZ']
financials = {}
#create a dictionary of ticker names and their respective statements' urls
for symbol in symbols:
    financials[symbol] = ['https://finance.yahoo.com/quote/' + symbol + '/financials?p=' + symbol, 'https://finance.yahoo.com/quote/' + symbol + '/balance-sheet?p=' + symbol, 'https://finance.yahoo.com/quote/' + symbol + '/cash-flow?p=' + symbol]
print (financials['AAPL'][0])
data = pd.DataFrame()

for f in financials:
    print (f)
    df_income_statement = scrape_table(financials[f][0])
    df_balance_sheet = scrape_table(financials[f][1])
    df_cash_flow = scrape_table(financials[f][2])
    oldmerge = merge_IS_BS_CF(df_income_statement, df_balance_sheet, df_cash_flow)
    #print (oldmerge)
    data = data.append(oldmerge)