title: getting ValueError : "Can only tuple-index with a MultiIndex "
body: <p>I am trying to implement a simple RNN to predict the next integer in an integer sequence. So, I have a data set that is as below:</p>
  
  <pre><code>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
  </code></pre>
  
  <p>My code so far is:</p>
  
  <pre><code>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), 0]
          dataX.append(a)
          dataY.append(dataset[i + window_size, 0]) #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)
  
  print(X_train.head(5))
  print(Y_train.head(5))
  </code></pre>
  
  <p>I am trying to split each sequence with X_train as input that consists the complete set except the last term and Y_train be treated as an output will consist only the last digit.
  But when I run the code, I get the ValueError : Can only tuple-index with a MultiIndex.
  Can anybody explain what it means with respect to my code and what must I do to resolve it. </p>
  
  <p>The traceback call:
  <a href="https://i.stack.imgur.com/nxAQ5.png" rel="noreferrer"><img src="https://i.stack.imgur.com/nxAQ5.png" alt="enter image description here"></a></p>
  
  <p>PS - I am new to stack overflow and deep learning, so I would be very grateful if you could suggest and help me with formatting of my question.</p>