如何在dataframe中取出列索引名稱

Question

                     Open     High    Low    Close   Volume      Adj Close
Date                        
1990-01-02 00:00:00  35.25   37.50   35.00   37.25   6555600     8.70
1990-01-03 00:00:00  38.00   38.00   37.50   37.50   7444400     8.76
1990-01-04 00:00:00  38.25   38.75   37.25   37.63   7928800     8.79
1990-01-05 00:00:00  37.75   38.25   37.00   37.75   4406400     8.82
1990-01-08 00:00:00  37.50   38.00   37.00   38.00   3643200     8.88

如何刪除上述dataframe的Date索引名稱？ 它應該與其他列名稱在同一行，但不會導致問題。

謝謝

Answer 1

嘗試使用reset_index方法將DataFrame的索引移動到一列中（我想這就是你想要的）。

Answer 2

簡短的回答：你不能並且不清楚為什么這會“導致問題”。 “日期”名稱命名為DataFrame的索引，該索引與任何列都不同。 它會特別打印出這種偏移，因此您不會將其與框架的一列混淆。 您不會按照以下方式使用DataFrame['Date'] ：

>>> import numpy as np; import pandas; import datetime

>>> dfrm = pandas.DataFrame(np.random.rand(10,3), 
... columns=['A','B','C'], 
... index = pandas.Index(
... [datetime.date(2012,6,elem) for elem in range(1,11)],
... name="Date"))

>>> dfrm
                   A         B         C
Date                                    
2012-06-01  0.283724  0.863012  0.798891
2012-06-02  0.097231  0.277564  0.872306
2012-06-03  0.821461  0.499485  0.126441
2012-06-04  0.887782  0.389486  0.374118
2012-06-05  0.248065  0.032287  0.850939
2012-06-06  0.101917  0.121171  0.577643
2012-06-07  0.225278  0.161301  0.708996
2012-06-08  0.906042  0.828814  0.247564
2012-06-09  0.733363  0.924076  0.393353
2012-06-10  0.273837  0.318013  0.754807

>>> dfrm['Date']
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/local/lib/python2.7/dist-packages/pandas/core/frame.py", line 1458, in __getitem__
    return self._get_item_cache(key)
  File "/usr/local/lib/python2.7/dist-packages/pandas/core/generic.py", line 294, in _get_item_cache
    values = self._data.get(item)
  File "/usr/local/lib/python2.7/dist-packages/pandas/core/internals.py", line 625, in get
    _, block = self._find_block(item)
  File "/usr/local/lib/python2.7/dist-packages/pandas/core/internals.py", line 715, in _find_block
    self._check_have(item)
  File "/usr/local/lib/python2.7/dist-packages/pandas/core/internals.py", line 722, in _check_have
    raise KeyError('no item named %s' % str(item))
KeyError: 'no item named Date'

更長的回答：

如果您希望以這種方式打印索引， 可以通過將索引添加到自己的列中來更改DataFrame。 例如：

>>> dfrm['Date'] = dfrm.index

>>> dfrm
                   A         B         C        Date
Date                                                
2012-06-01  0.283724  0.863012  0.798891  2012-06-01
2012-06-02  0.097231  0.277564  0.872306  2012-06-02
2012-06-03  0.821461  0.499485  0.126441  2012-06-03
2012-06-04  0.887782  0.389486  0.374118  2012-06-04
2012-06-05  0.248065  0.032287  0.850939  2012-06-05
2012-06-06  0.101917  0.121171  0.577643  2012-06-06
2012-06-07  0.225278  0.161301  0.708996  2012-06-07
2012-06-08  0.906042  0.828814  0.247564  2012-06-08
2012-06-09  0.733363  0.924076  0.393353  2012-06-09
2012-06-10  0.273837  0.318013  0.754807  2012-06-10

在此之后，您可以簡單地更改索引的名稱，以便不打印任何內容：

>>> dfrm.reindex(pandas.Series(dfrm.index.values, name=''))
                   A         B         C        Date

2012-06-01  0.283724  0.863012  0.798891  2012-06-01
2012-06-02  0.097231  0.277564  0.872306  2012-06-02
2012-06-03  0.821461  0.499485  0.126441  2012-06-03
2012-06-04  0.887782  0.389486  0.374118  2012-06-04
2012-06-05  0.248065  0.032287  0.850939  2012-06-05
2012-06-06  0.101917  0.121171  0.577643  2012-06-06
2012-06-07  0.225278  0.161301  0.708996  2012-06-07
2012-06-08  0.906042  0.828814  0.247564  2012-06-08
2012-06-09  0.733363  0.924076  0.393353  2012-06-09
2012-06-10  0.273837  0.318013  0.754807  2012-06-10

這似乎有點矯枉過正。 另一種選擇是在將Date添加為列后將索引更改為整數或其他內容：

>>> dfrm.reset_index()

或者如果您已經手動將索引移動到列中，那么就是

>>> dfrm.index = range(len(dfrm))

>>> dfrm
          A         B         C        Date
0  0.283724  0.863012  0.798891  2012-06-01
1  0.097231  0.277564  0.872306  2012-06-02
2  0.821461  0.499485  0.126441  2012-06-03
3  0.887782  0.389486  0.374118  2012-06-04
4  0.248065  0.032287  0.850939  2012-06-05
5  0.101917  0.121171  0.577643  2012-06-06
6  0.225278  0.161301  0.708996  2012-06-07
7  0.906042  0.828814  0.247564  2012-06-08
8  0.733363  0.924076  0.393353  2012-06-09
9  0.273837  0.318013  0.754807  2012-06-10

如果您關心列的顯示順序，請執行以下操作：

>>> dfrm.ix[:,[-1]+range(len(dfrm.columns)-1)]
         Date         A         B         C
0  2012-06-01  0.283724  0.863012  0.798891
1  2012-06-02  0.097231  0.277564  0.872306
2  2012-06-03  0.821461  0.499485  0.126441
3  2012-06-04  0.887782  0.389486  0.374118
4  2012-06-05  0.248065  0.032287  0.850939
5  2012-06-06  0.101917  0.121171  0.577643
6  2012-06-07  0.225278  0.161301  0.708996
7  2012-06-08  0.906042  0.828814  0.247564
8  2012-06-09  0.733363  0.924076  0.393353
9  2012-06-10  0.273837  0.318013  0.754807

添加

以下是一些有用的函數，包含在iPython配置腳本中（以便在啟動時加載它們），或者放入一個模塊，您可以在使用Python時輕松加載。

###########
# Imports #
###########
import pandas
import datetime
import numpy as np
from dateutil import relativedelta
from pandas.io import data as pdata


############################################
# Functions to retrieve Yahoo finance data #
############################################

# Utility to get generic stock symbol data from Yahoo finance.
# Starts two days prior to present (or most recent business day)
# and goes back a specified number of days.
def getStockSymbolData(sym_list, end_date=datetime.date.today()+relativedelta.relativedelta(days=-1), num_dates = 30):

    dReader = pdata.DataReader
    start_date = end_date + relativedelta.relativedelta(days=-num_dates)
    return dict( (sym, dReader(sym, "yahoo", start=start_date, end=end_date)) for sym in sym_list )                     
###

# Utility function to get some AAPL data when needed
# for testing.
def getAAPL(end_date=datetime.date.today()+relativedelta.relativedelta(days=-1), num_dates = 30):

    dReader = pdata.DataReader
    return getStockSymbolData(['AAPL'], end_date=end_date, num_dates=num_dates)
###

我還在下面寫了一個類來保存普通股的一些數據：

#####
# Define a 'Stock' class that can hold simple info
# about a security, like SEDOL and CUSIP info. This
# is mainly for debugging things and quickly getting
# info for a single security.
class MyStock():

    def __init__(self, ticker='None', sedol='None', country='None'):
        self.ticker = ticker
        self.sedol=sedol
        self.country = country
    ###


    def getData(self, end_date=datetime.date.today()+relativedelta.relativedelta(days=-1), num_dates = 30):
        return pandas.DataFrame(getStockSymbolData([self.ticker], end_date=end_date, num_dates=num_dates)[self.ticker])
    ###


#####
# Make some default stock objects for common stocks.
AAPL = MyStock(ticker='AAPL', sedol='03783310', country='US')
SAP  = MyStock(ticker='SAP',  sedol='484628',   country='DE')