尝试将列表转换为 numpy 数组时出现 KeyError：0

Question

我正在尝试实现一个简单的 RNN 来预测整数序列中的下一个整数。所以，我有一个数据集如下：

Id  Sequence
1   1,0,0,2,24,552,21280,103760,70299264,5792853248,587159944704
2   1,1,5,11,35,93,269,747,2115,5933,16717,47003,132291,372157,1047181,2946251,8289731,23323853,65624397,184640891,519507267,1461688413,4112616845,11571284395,32557042499,91602704493,257733967693
4   0,1,101,2,15,102,73,3,40,16,47,103,51,74,116,4,57,41,125,17,12,48,9,104,30,52,141,75,107,117,69,5,148,58,88,42,33,126,152,18,160,13,38,49,55,10,28,105,146,31,158
5   1,4,14,23,42,33,35,34,63,66,87,116,84,101,126,164,128,102,135,143,149,155,203,224,186,204,210,237,261,218,219,286,257,266,361,355,336,302,374,339,371,398,340,409,348,388,494,436,407,406
6   1,1,2,5,4,2,6,13,11,4,10,10,12,6,8,29,16,11,18,20,12,10,22,26,29,12,38,30,28,8,30,61,20,16,24,55,36,18,24,52,40,12,42,50,44,22,46,58,55,29,32,60,52,38,40,78,36,28,58,40,60,30,66,125,48,20,66,80,44,24
9   0,31,59,90,120,151,181,212,243,273,304,334,365,396,424,455,485,516,546,577,608,638,669,699,730,761,789,820,850,881,911,942,973,1003,1034,1064,1095,1126,1155,1186,1216,1247,1277,1308,1339,1369,1400,1430
10  1,1,2,5,13,36,111,347,1134,3832,13126,46281,165283,598401,2202404,8168642,30653724,116082962,442503542,1701654889,6580937039,25603715395,100223117080,394001755683,1556876401398,6178202068457,24608353860698,98421159688268,394901524823138,1589722790850089
12  0,0,0,0,112,40286,5485032,534844548,45066853496,3538771308282,267882021563464,19861835713621616,1453175611052688600,105278656040052332838,7564280930105061931496

我的代码：

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import math
from keras.models import Sequential
from keras.layers import Dense
from keras.layers import SimpleRNN
from sklearn.preprocessing import MinMaxScaler
from sklearn.metrics import mean_squared_error
from keras.preprocessing.sequence import pad_sequences

def stoarray(data = [], sep = ','):
    return data.map(lambda x: np.array(x.split(sep), dtype=float))

def create_dataset(dataset, window_size=1):
    dataX, dataY = [], []
    for i in range(len(dataset)-window_size-1):
        a = dataset[i:(i+window_size)]
        dataX.append(a)
        dataY.append(dataset[i + window_size]) #gives the ValueError : Can only tuple index with multi index
    return np.array(dataX), np.array(dataY)

# fix random seed for reproducibility
np.random.seed(7)

# loading data
colna = ['id', 'seq']
train_data = pd.read_csv('G:/Python/integer_sequencing/testfile.csv', header=1)
train_data.columns = colna
dataset = train_data['seq']
#print(dataset)
window_size = 1
X_train, Y_train = create_dataset(dataset, window_size)


#X_train = X_train.reshape((len(X_train), 1, 1))
#Y_train = Y_train.reshape((len(Y_train), 1, 1))


print('X_ train \n'  % (X_train))
print('Y_ train \n'  % (Y_train))

我试图以 X_train 作为输入来拆分每个序列，该输入包含除最后一项之外的完整集，并且 Y_train 被视为输出将仅包含最后一个数字。 回溯调用是：

Using TensorFlow backend.
Traceback (most recent call last):
  File "MyTest.py", line 37, in <module>
    X_train, Y_train = create_dataset(dataset, window_size)
  File "MyTest.py", line 25, in create_dataset
    return np.array(dataX), np.array(dataY)
  File "C:\Users\sarah\Anaconda3\envs\keras_tf\lib\site-packages\pandas\core\series.py", line 601, in __getitem__
    result = self.index.get_value(self, key)
  File "C:\Users\sarah\Anaconda3\envs\keras_tf\lib\site-packages\pandas\core\indexes\base.py", line 2477, in get_value
    tz=getattr(series.dtype, 'tz', None))
  File "pandas\_libs\index.pyx", line 98, in pandas._libs.index.IndexEngine.get_value (pandas\_libs\index.c:4404)
  File "pandas\_libs\index.pyx", line 106, in pandas._libs.index.IndexEngine.get_value (pandas\_libs\index.c:4087)
  File "pandas\_libs\index.pyx", line 154, in pandas._libs.index.IndexEngine.get_loc (pandas\_libs\index.c:5126)
  File "pandas\_libs\hashtable_class_helper.pxi", line 759, in pandas._libs.hashtable.Int64HashTable.get_item (pandas\_libs\hashtable.c:14031)
  File "pandas\_libs\hashtable_class_helper.pxi", line 765, in pandas._libs.hashtable.Int64HashTable.get_item (pandas\_libs\hashtable.c:13975)
KeyError: 0

(keras_tf) G:\Python\integer_sequencing>

有人可以解释为什么我在这里得到 KeyError 吗？

Answer 1

我的猜测是您正在混合使用 pandas 和 numpy 索引。请尝试以下操作：

(...)
X_train, Y_train = create_dataset(dataset.value, window_size)
(...)

dataset.value 是一个numpy array