[英]Unable to transform my input series and window-size into a set of input/output pairs for the RNN model
I am currently building a reccurent neural network model and i am currently stuck when i was about to transform my input data into a set on input/output for the RNN model.我目前正在构建一个循环神经网络模型,当我即将将输入数据转换为 RNN 模型的输入/输出集时,我目前陷入困境。
I have tried the windoe_tranform_series function that takes the series, window_size and the stepsize as inputs but i keep getting a KEYERROR.我尝试过将系列、window_size 和 stepsize 作为输入的 windoe_tranform_series 函数,但我一直收到 KEYERROR。
def window_transform_series(series,window_size,step_size):
inputs = []
outputs = []
ctr = 0
for i in range(window_size, len(series), step_size):
inputs.append(series[ctr:i])
outputs.append(series[i])
ctr = ctr + step_size
return inputs,outputs
window_size = 7 step_size = 5窗口大小 = 7 步长 = 5
inputs, outputs = window_transform_series(carbon_persil,window_size,step_size)
KeyError Traceback (most recent call last)
~\Anaconda3\lib\site-packages\pandas\core\indexes\base.py in get_loc(self, key, method, tolerance)
2656 try:
-> 2657 return self._engine.get_loc(key)
2658 except KeyError:
pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()
pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()
pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()
pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()
KeyError: 7
During handling of the above exception, another exception occurred:
KeyError Traceback (most recent call last)
<ipython-input-45-9810d786d8b5> in <module>
2 window_size = 7
3 step_size = 5
----> 4 inputs, outputs = window_transform_series(carbon_persil,window_size,step_size)
<ipython-input-41-82e8b484e9e9> in window_transform_series(series, window_size, step_size)
9 for i in range(window_size, len(series), step_size):
10 inputs.append(series[ctr:i])
---> 11 outputs.append(series[i])
12 ctr = ctr + step_size
13 return inputs,outputs
~\Anaconda3\lib\site-packages\pandas\core\frame.py in __getitem__(self, key)
2925 if self.columns.nlevels > 1:
2926 return self._getitem_multilevel(key)
-> 2927 indexer = self.columns.get_loc(key)
2928 if is_integer(indexer):
2929 indexer = [indexer]
~\Anaconda3\lib\site-packages\pandas\core\indexes\base.py in get_loc(self, key, method, tolerance)
2657 return self._engine.get_loc(key)
2658 except KeyError:
-> 2659 return self._engine.get_loc(self._maybe_cast_indexer(key))
2660 indexer = self.get_indexer([key], method=method, tolerance=tolerance)
2661 if indexer.ndim > 1 or indexer.size > 1:
pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()
pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()
pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()
pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()
KeyError: 7
Your series
is not long enough.你的
series
不够长。 See the following example snippet.请参阅以下示例代码段。
import numpy as np
import pandas as pd
data = np.array(['a','b','c','d'])
s = pd.Series(data) # create dummy series
Now, print (s[2])
would print 'c'
as the output.现在,
print (s[2])
将打印'c'
作为输出。
But if you try to print something out of range, it gives the KeyError
.但是,如果您尝试打印超出范围的内容,则会出现
KeyError
。
So, print (s[5])
here gives KeyError: 5
.因此,这里的
print (s[5])
给出KeyError: 5
。 In your case, you start the for loop with window_size=7
and since the length of your series
is less than 7
, it gives KeyError: 7
on line outputs.append(series[i])
.在您的情况下,您使用
window_size=7
开始 for 循环,并且由于您的series
的长度小于7
,因此它给出KeyError: 7
on line outputs.append(series[i])
。
Interestingly, this error doesn't happen when you try to slice the series with an out of range index.有趣的是,当您尝试使用超出范围的索引对系列进行切片时,不会发生此错误。
Eg if you try to do print (s[1:5])
in the example above, it would just print the following instead of the KeyError
.例如,如果您尝试在上面的示例中执行
print (s[1:5])
,它只会打印以下内容而不是KeyError
。
1 b
2 c
3 d
Therefore, the KeyError
is bypassed in your inputs.append(series[ctr:i])
line.因此,
KeyError
是在绕过inputs.append(series[ctr:i])
线。
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