# train_test_split() error: Found input variables with inconsistent numbers of samples

Fairly new to Python but building out my first RF model based on some classification data. I've converted all of the labels into int64 numerical data and loaded into X and Y as a numpy array, but I am hitting an error when I am trying to train the models.

Here is what my arrays look like:

>>> X = np.array([[df.tran_cityname, df.tran_signupos, df.tran_signupchannel, df.tran_vmake, df.tran_vmodel, df.tran_vyear]])

>>> Y = np.array(df['completed_trip_status'].values.tolist())

>>> X
array([[[   1,    1,    2,    3,    1,    1,    1,    1,    1,    3,    1,
3,    1,    1,    1,    1,    2,    1,    3,    1,    3,    3,
2,    3,    3,    1,    1,    1,    1],
[   0,    5,    5,    1,    1,    1,    2,    2,    0,    2,    2,
3,    1,    2,    5,    5,    2,    1,    2,    2,    2,    2,
2,    4,    3,    5,    1,    0,    1],
[   2,    2,    1,    3,    3,    3,    2,    3,    3,    2,    3,
2,    3,    2,    2,    3,    2,    2,    1,    1,    2,    1,
2,    2,    1,    2,    3,    1,    1],
[   0,    0,    0,   42,   17,    8,   42,    0,    0,    0,   22,
0,   22,    0,    0,   42,    0,    0,    0,    0,   11,    0,
0,    0,    0,    0,   28,   17,   18],
[   0,    0,    0,   70,  291,   88,  234,    0,    0,    0,  222,
0,  222,    0,    0,  234,    0,    0,    0,    0,   89,    0,
0,    0,    0,    0,   40,  291,  131],
[   0,    0,    0, 2016, 2016, 2006, 2014,    0,    0,    0, 2015,
0, 2015,    0,    0, 2015,    0,    0,    0,    0, 2015,    0,
0,    0,    0,    0, 2016, 2016, 2010]]])

>>> Y
array(['NO', 'NO', 'NO', 'YES', 'NO', 'NO', 'YES', 'NO', 'NO', 'NO', 'NO',
'NO', 'YES', 'NO', 'NO', 'YES', 'NO', 'NO', 'NO', 'NO', 'NO', 'NO',
'NO', 'NO', 'NO', 'NO', 'NO', 'NO', 'NO'],
dtype='|S3')

>>> X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.3)


Traceback (most recent call last):

  File "<stdin>", line 1, in <module>
File "/Library/Python/2.7/site-packages/sklearn/cross_validation.py", line


2039, in train_test_split arrays = indexable(*arrays) File "/Library/Python/2.7/site-packages/sklearn/utils/validation.py", line 206, in indexable check_consistent_length(*result) File "/Library/Python/2.7/site-packages/sklearn/utils/validation.py", line 181, in check_consistent_length " samples: %r" % [int(l) for l in lengths])

ValueError: Found input variables with inconsistent numbers of samples: [1, 29]

• In the future, please post programming questions to stackoverflow. This Q&A is about data science, not programming. Aug 23 '18 at 21:21

You are running into that error because your X and Y don't have the same length (which is what train_test_split requires), i.e., X.shape[0] != Y.shape[0]. Given your current code:

>>> X.shape
(1, 6, 29)
>>> Y.shape
(29,)


To fix this error:

1. Remove the extra list from inside of np.array() when defining X or remove the extra dimension afterwards with the following command: X = X.reshape(X.shape[1:]). Now, the shape of X will be (6, 29).
2. Transpose X by running X = X.transpose() to get equal number of samples in X and Y. Now, the shape of X will be (29, 6) and the shape of Y will be (29,).
• Amazing this worked for me! Thanks Tuomastik! I really appreciate the guidance :) Jul 13 '17 at 12:45

Isn't train_test_split expecting both X and Y to be a list of same length? Your X has length of 6 and Y has length of 29. May be try converting that to pandas dataframe (with 29x6 dimension) and try again?

Given your data, it looks like you have 6 features. In that case, try to convert your X to have 29 rows and 6 columns. Then pass that dataframe to train_test_split. You can convert your list to dataframe using pd.DataFrame.from_records.

• Thanks for the help Sal! You're right, I just had to convert it to the same lengths. My X.shape was (1, 6, 29) and Y.shape was (29, ). I just had to reshape them and it all worked fine for me :) Jul 13 '17 at 12:47