Question

我尝试从Morningstar中获取数据并合并不同的股票，但是我不知道如何正确地合并数据。我想按日期组织它，但它只是将数据堆叠在一起。

print('test')
print('testing')
#this program will read data from morningstar and interpret them using pandas

import pandas as pd
import datetime

import numpy as np
import matplotlib.pylab as plt

pd.core.common.is_list_like = pd.api.types.is_list_like

import pandas_datareader.data as web

start = datetime.datetime(2010,1,1) #datetime is (year, month, day)
end = datetime.date.today()

#Getting data from morningstar
microsoft = pd.DataFrame(web.DataReader("MSFT", "morningstar", start, end))
apple = pd.DataFrame(web.DataReader("AAPL","morningstar", start, end))
google = pd.DataFrame(web.DataReader("GOOG", "morningstar", start, end))


stocks = pd.DataFrame({"MSFT": microsoft["Volume"],
                   "AAPL": apple["Volume"],
                  "GOOG": google["Volume"]})


print(stocks)

基本上我希望数据看起来像这样：

          stock1          stock2        stock3

date1       123            345           234

date2       657            294           553

date3       786            321           933

但是事实却是这样的：

           stock1         stock2        stock3

date1       123            NaN           NaN

date2       657            NaN           NaN

date3       786            NaN           NaN

date1       NaN            345           NaN

date2       NaN            294           NaN

date3       NaN            321           NaN

date1       NaN            NaN           234

date2       NaN            NaN           553

date3       NaN            NaN           933

Answer 1

创建新的数据框时，您可以在末尾添加reset_index

stocks = pd.DataFrame({"MSFT": microsoft["Volume"].reset_index(level=0,drop=True),
                   "AAPL": apple["Volume"].reset_index(level=0,drop=True),
                  "GOOG": google["Volume"].reset_index(level=0,drop=True)})

如何进行远程数据访问（从股票市场）并将其组合为单个数据框？

1 个答案: