Question

我正在尝试使用第一行股票价格来规范化我的数据框。以下是我的规范化功能。

def get_data(symbols, dates, addSPY=True, colname = 'Adj. Close'):
"""Read stock data (adjusted close) for given symbols from CSV files."""
##df = pd.DataFrame(index=dates)

for symbol in symbols:
    save_place = get_data(symbol)
    df = pd.read_csv(save_place, index_col='Date',
        parse_dates=True, usecols=['Date', colname], na_values=['nan'])
    df_temp = df_temp.rename(columns={colname: symbol})
    df = df.join(df_temp)

return df

def normalize_data(df):
    """Normalize stock price using the first row of dataframe """
    print(df)
    return df/df[0,:]
     Adj. Close

Date                       
2016-06-09           153.42
2016-06-08            154.0
2016-06-07           153.33
2016-06-06           152.73
2016-06-03           152.89
2016-06-02            153.5
2016-06-01           152.51
2016-05-31           153.74
2016-05-27           152.84
2016-05-26           152.44
2016-05-25           151.69

错误是：

  File "util.py", line 40, in normalize_data
    return df/df[0,:]
  File "C:\Users\fange\AppData\Local\Continuum\Anaconda2\lib\site-packages\pandas\core\frame.py", line 1992, in __getitem__
    return self._getitem_column(key)
  File "C:\Users\fange\AppData\Local\Continuum\Anaconda2\lib\site-packages\pandas\core\frame.py", line 1999, in _getitem_column
    return self._get_item_cache(key)
  File "C:\Users\fange\AppData\Local\Continuum\Anaconda2\lib\site-packages\pandas\core\generic.py", line 1343, in _get_item_cache
    res = cache.get(item)
TypeError: unhashable type

Answer 1

假设您开始使用pd.DataFrame column，'Adj.Close'：

s = pd.to_numeric(df.squeeze()) # alternatively to df.squeeze(), you could use df.loc[:, 'Adj. Close']

            Adj. Close
Date                  
2016-06-09      153.42
2016-06-08      154.00
2016-06-07      153.33
2016-06-06      152.73
2016-06-03      152.89
2016-06-02      153.50
2016-06-01      152.51
2016-05-31      153.74
2016-05-27      152.84
2016-05-26      152.44
2016-05-25      151.69

使用

s.div(s.iloc[0])

的产率：

            Adj. Close
Date                  
2016-06-09    1.000000
2016-06-08    1.003780
2016-06-07    0.999413
2016-06-06    0.995503
2016-06-03    0.996545
2016-06-02    1.000521
2016-06-01    0.994069
2016-05-31    1.002086
2016-05-27    0.996220
2016-05-26    0.993612
2016-05-25    0.988724

尝试规范化数据，但得到TypeError：unhashable类型

1 个答案: