Getting KeyError: 0 when trying to convert a list to numpy array

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:

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

My 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)]
        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))

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. The traceback call is :

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>

Can somebody explain why I am getting KeyError here?