Question

使用Pandas文档

http://pandas.pydata.org/pandas-docs/version/0.13.1/generated/pandas.DataFrame.pct_change.html

我正在尝试创建此函数来计算percentage_change。我把两个参数传递给它

 def PCT(df,n):
        d = df['Close'].pct_change(n)

即使以不同的方式重写相同的代码也会给我同样的错误

 P = pd.Series(df['Close'].pct_change(n), name = 'PCT_' + str(n))

数据帧
我希望％更改的窗口

抛出错误

  File "D:\Python Scripts\TA_Liabrary.py", line 15, in PCT
    d = df['Close'].pct_change(n)
TypeError: 'NoneType' object has no attribute '__getitem__'

有人可以帮助我吗

示例数据

Index   open    high    low close   volume  adj.
1/01/2014   54.97   54.97   54.97   54.97   0   49.31993
2/01/2014   55.1    55.95   54.86   55.08   216100  49.41862
3/01/2014   54.5    55  54.16   55  392600  49.34685
6/01/2014   54.82   55.47   54.62   55.14   344500  49.47245
7/01/2014   55.06   55.17   54.27   54.35   677400  48.76365
8/01/2014   54.64   54.88   53.87   54.38   587500  48.79057
9/01/2014   54.57   54.8    54.05   54.48   466800  48.88029

Answer 1

为什么不能使用文档中的功能？

a = [10,12,13]
b = [12,11,14]
d = {'open': a, 'close': b}

df = DataFrame(data=d)
print df

  close  open
0     12    10
1     11    12
2     14    13

print df.pct_change(1)

使用一个函数，这将是：

def PCT(dataf,n):
        return dataf.pct_change(n)

print PCT(df, 1)

两者都将返回：

      close      open
0       NaN       NaN
1 -0.083333  0.200000
2  0.272727  0.083333

您的示例数据print PCT(df['close'], 1)将返回：

Index         close
2014-01-01         NaN
2014-02-01    0.002001
2014-03-01   -0.001452
2014-06-01    0.002545
2014-07-01   -0.014327
2014-08-01    0.000552
2014-09-01    0.001839

Answer 2

pct_change仅适用于单列，可以在多列数据框中进行如下操作

df = pd.DataFrame({
    'open': [54.97,55.1,54.5,54.82],
    'high': [54.97,55.95,55,55.47],
    'low': [54.97,54.86,54.16,54.62],
    'close': [54.97,53.08,55,55.14]},
    index=['2014-01-01', '2014-02-01', '2014-03-01','2014-04-01'])

            open    high    low     close
2014-01-01  54.97   54.97   54.97   54.97
2014-02-01  55.10   55.95   54.86   53.08
2014-03-01  54.50   55.00   54.16   55.00
2014-04-01  54.82   55.47   54.62   55.14

仅将pct_change应用于“关闭”

df.close = df.close.pct_change(periods = 1)

            open    high    low     close
2014-01-01  54.97   54.97   54.97   NaN
2014-02-01  55.10   55.95   54.86   -0.034382
2014-03-01  54.50   55.00   54.16   0.036172
2014-04-01  54.82   55.47   54.62   0.002545

应用于以下多个列

# apply pct_change to 'open' and 'close'
df[['open','close']] = df[['open','close']].pct_change(periods = 1)

            open        high    low     close
2014-01-01  NaN         54.97   54.97   NaN
2014-02-01  0.002365    55.95   54.86   -0.034382
2014-03-01  -0.010889   55.00   54.16   0.036172
2014-04-01  0.005872    55.47   54.62   0.002545

pct_change为列值

2 个答案: