How can I do this problem about pandas index ?

Traceback (most recent call last):
  File "C:/Users/USER/PycharmProjects/KKOP/neuralN.py", line 10, in <module>
    X = data[:284,0:43]
  File "C:\Users\USER\AppData\Local\Programs\Python\Python37\lib\site-packages\pandas\core\frame.py", line 2899, in __getitem__
    indexer = self.columns.get_loc(key)
  File "C:\Users\USER\AppData\Local\Programs\Python\Python37\lib\site-packages\pandas\core\indexes\base.py", line 2889, in get_loc
    return self._engine.get_loc(casted_key)
  File "pandas\_libs\index.pyx", line 70, in pandas._libs.index.IndexEngine.get_loc
  File "pandas\_libs\index.pyx", line 75, in pandas._libs.index.IndexEngine.get_loc
TypeError: '(slice(None, 284, None), slice(0, 43, None))' is an invalid key

<pre><pre lang="Python">

import pandas as pd

data = pd.read_csv('bin_data.csv',sep=';')
print(data)
X = data[:284,0:43]
print(X)
Y = data[:284,43]

model = Sequential()

model.add(Dense(20, input_dim=9, init='uniform', activation='relu'))
model.add(Dense(12, init='uniform', activation='relu'))
model.add(Dense(9, init='uniform', activation='sigmoid'))
model.add(Dense(1, init='uniform', activation='sigmoid'))
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])

model.fit(X, Y, nb_epoch=150, batch_size=10,  verbose=2)
scores = model.evaluate(X,Y)
print("%s: %.2f%%" % (model.metrics_names[1], scores[1]*100))