Showing Error while using train_test_Split method to on Kaggle kernal. Help appreciated










0















Can any one expalin what is the error and how to aviod?
The same code actually works in my Jupyter and Spider environment. Also
I didn't understand why this isn't working on kaggle kernel.



Below is my code.



# Prepare X and y objects for sikitlearn
X = df.iloc[:, 1:5].values
y = df.iloc[:,-1].values

# Splitting the Dataset into the training set and the test set
X_train, X_test, y_train, y_test = train_test_split(X,y, test_size = 0.3, random_state =4)


Error Details:



 ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)

<ipython-input-49-5647b5a0596a> in <module>()
1 # Splitting the Dataset into the training set and the test set
2 from sklearn.model_selection import train_test_split
----> 3 X_train, X_test, y_train, y_test = train_test_split(X,y, test_size = 0.3, random_state =4)

/opt/conda/lib/python3.6/site-packages/sklearn/model_selection/_split.py in train_test_split(*arrays, **options)
2100
2101 return list(chain.from_iterable((safe_indexing(a, train),
-> 2102 safe_indexing(a, test)) for a in arrays))
2103
2104

/opt/conda/lib/python3.6/site-packages/sklearn/model_selection/_split.py in <genexpr>(.0)
2100
2101 return list(chain.from_iterable((safe_indexing(a, train),
-> 2102 safe_indexing(a, test)) for a in arrays))
2103
2104

/opt/conda/lib/python3.6/site-packages/sklearn/utils/__init__.py in safe_indexing(X, indices)
183 indices.dtype.kind == 'i'):
184 # This is often substantially faster than X[indices]
--> 185 return X.take(indices, axis=0)
186 else:
187 return X[indices]

TypeError: take_nd() got an unexpected keyword argument 'axis'









share|improve this question
























  • Looks like you have encountered this issue. Try updating your scikit-learn, numpy and pandas. Show the dtypes for the df. Are any of the columns of categorical type in pandas DataFrame?

    – Vivek Kumar
    Nov 15 '18 at 7:23












  • I find the solution , I just removed ".values" from my code and it works for me.

    – Ravi Varma
    Nov 17 '18 at 4:18
















0















Can any one expalin what is the error and how to aviod?
The same code actually works in my Jupyter and Spider environment. Also
I didn't understand why this isn't working on kaggle kernel.



Below is my code.



# Prepare X and y objects for sikitlearn
X = df.iloc[:, 1:5].values
y = df.iloc[:,-1].values

# Splitting the Dataset into the training set and the test set
X_train, X_test, y_train, y_test = train_test_split(X,y, test_size = 0.3, random_state =4)


Error Details:



 ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)

<ipython-input-49-5647b5a0596a> in <module>()
1 # Splitting the Dataset into the training set and the test set
2 from sklearn.model_selection import train_test_split
----> 3 X_train, X_test, y_train, y_test = train_test_split(X,y, test_size = 0.3, random_state =4)

/opt/conda/lib/python3.6/site-packages/sklearn/model_selection/_split.py in train_test_split(*arrays, **options)
2100
2101 return list(chain.from_iterable((safe_indexing(a, train),
-> 2102 safe_indexing(a, test)) for a in arrays))
2103
2104

/opt/conda/lib/python3.6/site-packages/sklearn/model_selection/_split.py in <genexpr>(.0)
2100
2101 return list(chain.from_iterable((safe_indexing(a, train),
-> 2102 safe_indexing(a, test)) for a in arrays))
2103
2104

/opt/conda/lib/python3.6/site-packages/sklearn/utils/__init__.py in safe_indexing(X, indices)
183 indices.dtype.kind == 'i'):
184 # This is often substantially faster than X[indices]
--> 185 return X.take(indices, axis=0)
186 else:
187 return X[indices]

TypeError: take_nd() got an unexpected keyword argument 'axis'









share|improve this question
























  • Looks like you have encountered this issue. Try updating your scikit-learn, numpy and pandas. Show the dtypes for the df. Are any of the columns of categorical type in pandas DataFrame?

    – Vivek Kumar
    Nov 15 '18 at 7:23












  • I find the solution , I just removed ".values" from my code and it works for me.

    – Ravi Varma
    Nov 17 '18 at 4:18














0












0








0


1






Can any one expalin what is the error and how to aviod?
The same code actually works in my Jupyter and Spider environment. Also
I didn't understand why this isn't working on kaggle kernel.



Below is my code.



# Prepare X and y objects for sikitlearn
X = df.iloc[:, 1:5].values
y = df.iloc[:,-1].values

# Splitting the Dataset into the training set and the test set
X_train, X_test, y_train, y_test = train_test_split(X,y, test_size = 0.3, random_state =4)


Error Details:



 ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)

<ipython-input-49-5647b5a0596a> in <module>()
1 # Splitting the Dataset into the training set and the test set
2 from sklearn.model_selection import train_test_split
----> 3 X_train, X_test, y_train, y_test = train_test_split(X,y, test_size = 0.3, random_state =4)

/opt/conda/lib/python3.6/site-packages/sklearn/model_selection/_split.py in train_test_split(*arrays, **options)
2100
2101 return list(chain.from_iterable((safe_indexing(a, train),
-> 2102 safe_indexing(a, test)) for a in arrays))
2103
2104

/opt/conda/lib/python3.6/site-packages/sklearn/model_selection/_split.py in <genexpr>(.0)
2100
2101 return list(chain.from_iterable((safe_indexing(a, train),
-> 2102 safe_indexing(a, test)) for a in arrays))
2103
2104

/opt/conda/lib/python3.6/site-packages/sklearn/utils/__init__.py in safe_indexing(X, indices)
183 indices.dtype.kind == 'i'):
184 # This is often substantially faster than X[indices]
--> 185 return X.take(indices, axis=0)
186 else:
187 return X[indices]

TypeError: take_nd() got an unexpected keyword argument 'axis'









share|improve this question
















Can any one expalin what is the error and how to aviod?
The same code actually works in my Jupyter and Spider environment. Also
I didn't understand why this isn't working on kaggle kernel.



Below is my code.



# Prepare X and y objects for sikitlearn
X = df.iloc[:, 1:5].values
y = df.iloc[:,-1].values

# Splitting the Dataset into the training set and the test set
X_train, X_test, y_train, y_test = train_test_split(X,y, test_size = 0.3, random_state =4)


Error Details:



 ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)

<ipython-input-49-5647b5a0596a> in <module>()
1 # Splitting the Dataset into the training set and the test set
2 from sklearn.model_selection import train_test_split
----> 3 X_train, X_test, y_train, y_test = train_test_split(X,y, test_size = 0.3, random_state =4)

/opt/conda/lib/python3.6/site-packages/sklearn/model_selection/_split.py in train_test_split(*arrays, **options)
2100
2101 return list(chain.from_iterable((safe_indexing(a, train),
-> 2102 safe_indexing(a, test)) for a in arrays))
2103
2104

/opt/conda/lib/python3.6/site-packages/sklearn/model_selection/_split.py in <genexpr>(.0)
2100
2101 return list(chain.from_iterable((safe_indexing(a, train),
-> 2102 safe_indexing(a, test)) for a in arrays))
2103
2104

/opt/conda/lib/python3.6/site-packages/sklearn/utils/__init__.py in safe_indexing(X, indices)
183 indices.dtype.kind == 'i'):
184 # This is often substantially faster than X[indices]
--> 185 return X.take(indices, axis=0)
186 else:
187 return X[indices]

TypeError: take_nd() got an unexpected keyword argument 'axis'






python python-3.x scikit-learn kernel






share|improve this question















share|improve this question













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edited Nov 15 '18 at 4:55







Ravi Varma

















asked Nov 15 '18 at 4:30









Ravi VarmaRavi Varma

34




34












  • Looks like you have encountered this issue. Try updating your scikit-learn, numpy and pandas. Show the dtypes for the df. Are any of the columns of categorical type in pandas DataFrame?

    – Vivek Kumar
    Nov 15 '18 at 7:23












  • I find the solution , I just removed ".values" from my code and it works for me.

    – Ravi Varma
    Nov 17 '18 at 4:18


















  • Looks like you have encountered this issue. Try updating your scikit-learn, numpy and pandas. Show the dtypes for the df. Are any of the columns of categorical type in pandas DataFrame?

    – Vivek Kumar
    Nov 15 '18 at 7:23












  • I find the solution , I just removed ".values" from my code and it works for me.

    – Ravi Varma
    Nov 17 '18 at 4:18

















Looks like you have encountered this issue. Try updating your scikit-learn, numpy and pandas. Show the dtypes for the df. Are any of the columns of categorical type in pandas DataFrame?

– Vivek Kumar
Nov 15 '18 at 7:23






Looks like you have encountered this issue. Try updating your scikit-learn, numpy and pandas. Show the dtypes for the df. Are any of the columns of categorical type in pandas DataFrame?

– Vivek Kumar
Nov 15 '18 at 7:23














I find the solution , I just removed ".values" from my code and it works for me.

– Ravi Varma
Nov 17 '18 at 4:18






I find the solution , I just removed ".values" from my code and it works for me.

– Ravi Varma
Nov 17 '18 at 4:18













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