Question

我正在尝试创建Pandas DataFrame，每列都是个别股票的百分比变化，按日期编制索引。我在修改百分比时遇到问题，将其添加到空DataFrame并将该列命名为股票代码。

import pandas as pd
import pandas.io.data as web
from pandas import Series, DataFrame

stocks = {'xom': '2014-01-01', 'dvn': '2013-01-01', 'aapl': '2013-01-01'}
for key in stocks:
    L = []
    price = web.get_data_yahoo(key, stocks[key])['Adj Close']
    change = price.diff().cumsum()
    perChange = change / price.iloc[0]

到目前为止，一切都按计划进行......

    L.append(perChange)
    df = pd.DataFrame(L)
    df.columns = keys

Answer 1

将L移到循环之外，因此不会在每次迭代时重新实例化。如果您将L设为dict，那么dict的键将成为df = pd.DataFrame(L)形成的DataFrame的列：

import pandas as pd
import pandas.io.data as web

stocks = {'xom': '2014-01-01', 'dvn': '2013-01-01', 'aapl': '2013-01-01'}
L = dict()
for stock, date in stocks.items():
    price = web.get_data_yahoo(stock, date)['Adj Close']
    change = price.diff().cumsum()
    perChange = change / price.iloc[0]
    L[stock] = perChange
df = pd.DataFrame(L)
print(df.head())

产量

                aapl       dvn  xom
Date                               
2013-01-02       NaN       NaN  NaN
2013-01-03 -0.012622  0.017728  NaN
2013-01-04 -0.040125  0.040412  NaN
2013-01-07 -0.045772  0.040793  NaN
2013-01-08 -0.043203  0.033359  NaN

迭代字典以创建一个DataFrame，列名是字典键

1 个答案: