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Expected 2D array, got 1D array

Simple Digit Recognition OCR in OpenCV-PythonUnderstanding Keras LSTMsSKlearn reshape warning for X and YI am having the same dataset as other person and same code but I m getting error of expecting 2D arrayPrint predict ValueError: Expected 2D array, got 1D array insteadExpected 2D array, got 1D array instead errorExpected 2D array, got 1D array instead, any solution?Expected 2d array but got scalar array insteadHow to use Numpy reshape?ValueError on sklearn's linear_model.predict

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0

I'm running the following code from github, but I'm getting an error. What's wrong?

https://github.com/susanli2016/Machine-Learning-with-Python/blob/master/Time%20Series%20ANN%20%26%20LSTM%20VIX.ipynb

Cell:

# scale train and test data to [-1, 1]
scaler = MinMaxScaler(feature_range=(-1, 1))
train_sc = scaler.fit_transform(train)
test_sc = scaler.transform(test)

Error:

ValueError: Expected 2D array, got 1D array instead:
array=[17.24 18.190001 19.219999 ... 10.47 10.18 11.04 ].
Reshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample.

python pandas numpy keras sklearn-pandas

share|improve this question

asked Mar 26 at 23:33

grcgrc

4199 bronze badges

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Try to make your data in proper order.
  
  – lifeisshubh
  Mar 26 at 23:40
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  What is train? pd.Series? np.array? If it's a series, just use .to_frame(). If it's np array, reshape it as suggested .reshape(-1,1)
  
  – rafaelc
  Mar 27 at 0:17
  

  
  
  
  

add a comment | 

0

I'm running the following code from github, but I'm getting an error. What's wrong?

https://github.com/susanli2016/Machine-Learning-with-Python/blob/master/Time%20Series%20ANN%20%26%20LSTM%20VIX.ipynb

Cell:

# scale train and test data to [-1, 1]
scaler = MinMaxScaler(feature_range=(-1, 1))
train_sc = scaler.fit_transform(train)
test_sc = scaler.transform(test)

Error:

ValueError: Expected 2D array, got 1D array instead:
array=[17.24 18.190001 19.219999 ... 10.47 10.18 11.04 ].
Reshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample.

python pandas numpy keras sklearn-pandas

share|improve this question

asked Mar 26 at 23:33

grcgrc

4199 bronze badges

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Try to make your data in proper order.
  
  – lifeisshubh
  Mar 26 at 23:40
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  What is train? pd.Series? np.array? If it's a series, just use .to_frame(). If it's np array, reshape it as suggested .reshape(-1,1)
  
  – rafaelc
  Mar 27 at 0:17
  

  
  
  
  

add a comment | 

I'm running the following code from github, but I'm getting an error. What's wrong?

https://github.com/susanli2016/Machine-Learning-with-Python/blob/master/Time%20Series%20ANN%20%26%20LSTM%20VIX.ipynb

Cell:

# scale train and test data to [-1, 1]
scaler = MinMaxScaler(feature_range=(-1, 1))
train_sc = scaler.fit_transform(train)
test_sc = scaler.transform(test)

Error:

ValueError: Expected 2D array, got 1D array instead:
array=[17.24 18.190001 19.219999 ... 10.47 10.18 11.04 ].
Reshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample.

python pandas numpy keras sklearn-pandas

share|improve this question

asked Mar 26 at 23:33

grcgrc

4199 bronze badges

# scale train and test data to [-1, 1]
scaler = MinMaxScaler(feature_range=(-1, 1))
train_sc = scaler.fit_transform(train)
test_sc = scaler.transform(test)

ValueError: Expected 2D array, got 1D array instead:
array=[17.24 18.190001 19.219999 ... 10.47 10.18 11.04 ].
Reshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample.

share|improve this question

asked Mar 26 at 23:33

grcgrc

4199 bronze badges

share|improve this question

asked Mar 26 at 23:33

grcgrc

4199 bronze badges

asked Mar 26 at 23:33

grcgrc

4199 bronze badges

asked Mar 26 at 23:33

grcgrc

4199 bronze badges

2 Answers
2

active

oldest

votes

2

The person who made that notebook was using a really old version of sklearn. In short, your features were of the form [row_1, row_2...row_n], when they should have been of the form [[row_1], [row_2]...[row_n]].

Accordingly, use this:

new_shape = (len(train), 1)

train_sc = scaler.fit_transform(np.reshape(train, new_shape))
test_sc = scaler.transform(np.reshape(test, new_shape))

share|improve this answer

edited Mar 27 at 1:11

answered Mar 26 at 23:37

gmdsgmds

13.9k33 gold badges1111 silver badges3838 bronze badges

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Thanks! But I got a new error: TypeError: len() takes exactly one argument (2 given)
  
  – grc
  Mar 26 at 23:57
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  @grc probably gmds meant (len(train), 1)
  
  – rafaelc
  Mar 27 at 0:15
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  @grc @RafaelC Yup, moved new_shape out into a separate statement and forgot to shift the brackets. Edited.
  
  – gmds
  Mar 27 at 1:12
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Thanks. Now it returns this ERROR: Data must be 1-dimensional
  
  – grc
  Mar 29 at 22:19
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  If I write like this, it works, but the "test_sc" is not working. scaler = MinMaxScaler(feature_range=(-1, 1)) train = train.reshape(1,-1) train_sc = scaler.fit_transform(train)
  
  – grc
  Mar 29 at 22:36
  
  

  
  
  
  

add a comment | 

0

Solved the problem adding the methods below, which apparently transform train and test objects to numpy arrays. Is that correct?

scaler = MinMaxScaler(feature_range=(-1, 1))
train_sc = scaler.fit_transform(train.values.reshape(-1, 1))
test_sc = scaler.transform(test.values.reshape(-1,1))

share|improve this answer

answered Apr 9 at 0:43

grcgrc

4199 bronze badges

add a comment | 

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2

The person who made that notebook was using a really old version of sklearn. In short, your features were of the form [row_1, row_2...row_n], when they should have been of the form [[row_1], [row_2]...[row_n]].

Accordingly, use this:

new_shape = (len(train), 1)

train_sc = scaler.fit_transform(np.reshape(train, new_shape))
test_sc = scaler.transform(np.reshape(test, new_shape))

share|improve this answer

edited Mar 27 at 1:11

answered Mar 26 at 23:37

gmdsgmds

13.9k33 gold badges1111 silver badges3838 bronze badges

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Thanks! But I got a new error: TypeError: len() takes exactly one argument (2 given)
  
  – grc
  Mar 26 at 23:57
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  @grc probably gmds meant (len(train), 1)
  
  – rafaelc
  Mar 27 at 0:15
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  @grc @RafaelC Yup, moved new_shape out into a separate statement and forgot to shift the brackets. Edited.
  
  – gmds
  Mar 27 at 1:12
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Thanks. Now it returns this ERROR: Data must be 1-dimensional
  
  – grc
  Mar 29 at 22:19
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  If I write like this, it works, but the "test_sc" is not working. scaler = MinMaxScaler(feature_range=(-1, 1)) train = train.reshape(1,-1) train_sc = scaler.fit_transform(train)
  
  – grc
  Mar 29 at 22:36
  
  

  
  
  
  

add a comment | 

2

The person who made that notebook was using a really old version of sklearn. In short, your features were of the form [row_1, row_2...row_n], when they should have been of the form [[row_1], [row_2]...[row_n]].

Accordingly, use this:

new_shape = (len(train), 1)

train_sc = scaler.fit_transform(np.reshape(train, new_shape))
test_sc = scaler.transform(np.reshape(test, new_shape))

share|improve this answer

edited Mar 27 at 1:11

answered Mar 26 at 23:37

gmdsgmds

13.9k33 gold badges1111 silver badges3838 bronze badges

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Thanks! But I got a new error: TypeError: len() takes exactly one argument (2 given)
  
  – grc
  Mar 26 at 23:57
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  @grc probably gmds meant (len(train), 1)
  
  – rafaelc
  Mar 27 at 0:15
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  @grc @RafaelC Yup, moved new_shape out into a separate statement and forgot to shift the brackets. Edited.
  
  – gmds
  Mar 27 at 1:12
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Thanks. Now it returns this ERROR: Data must be 1-dimensional
  
  – grc
  Mar 29 at 22:19
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  If I write like this, it works, but the "test_sc" is not working. scaler = MinMaxScaler(feature_range=(-1, 1)) train = train.reshape(1,-1) train_sc = scaler.fit_transform(train)
  
  – grc
  Mar 29 at 22:36
  
  

  
  
  
  

add a comment | 

The person who made that notebook was using a really old version of sklearn. In short, your features were of the form [row_1, row_2...row_n], when they should have been of the form [[row_1], [row_2]...[row_n]].

Accordingly, use this:

new_shape = (len(train), 1)

train_sc = scaler.fit_transform(np.reshape(train, new_shape))
test_sc = scaler.transform(np.reshape(test, new_shape))

share|improve this answer

edited Mar 27 at 1:11

answered Mar 26 at 23:37

gmdsgmds

13.9k33 gold badges1111 silver badges3838 bronze badges

new_shape = (len(train), 1)

train_sc = scaler.fit_transform(np.reshape(train, new_shape))
test_sc = scaler.transform(np.reshape(test, new_shape))

share|improve this answer

edited Mar 27 at 1:11

answered Mar 26 at 23:37

gmdsgmds

13.9k33 gold badges1111 silver badges3838 bronze badges

answered Mar 26 at 23:37

gmdsgmds

13.9k33 gold badges1111 silver badges3838 bronze badges

answered Mar 26 at 23:37

gmdsgmds

13.9k33 gold badges1111 silver badges3838 bronze badges

0

Solved the problem adding the methods below, which apparently transform train and test objects to numpy arrays. Is that correct?

scaler = MinMaxScaler(feature_range=(-1, 1))
train_sc = scaler.fit_transform(train.values.reshape(-1, 1))
test_sc = scaler.transform(test.values.reshape(-1,1))

share|improve this answer

answered Apr 9 at 0:43

grcgrc

4199 bronze badges

add a comment | 

0

Solved the problem adding the methods below, which apparently transform train and test objects to numpy arrays. Is that correct?

scaler = MinMaxScaler(feature_range=(-1, 1))
train_sc = scaler.fit_transform(train.values.reshape(-1, 1))
test_sc = scaler.transform(test.values.reshape(-1,1))

share|improve this answer

answered Apr 9 at 0:43

grcgrc

4199 bronze badges

add a comment | 

Solved the problem adding the methods below, which apparently transform train and test objects to numpy arrays. Is that correct?

scaler = MinMaxScaler(feature_range=(-1, 1))
train_sc = scaler.fit_transform(train.values.reshape(-1, 1))
test_sc = scaler.transform(test.values.reshape(-1,1))

share|improve this answer

answered Apr 9 at 0:43

grcgrc

4199 bronze badges

scaler = MinMaxScaler(feature_range=(-1, 1))
train_sc = scaler.fit_transform(train.values.reshape(-1, 1))
test_sc = scaler.transform(test.values.reshape(-1,1))

share|improve this answer

answered Apr 9 at 0:43

grcgrc

4199 bronze badges

answered Apr 9 at 0:43

grcgrc

4199 bronze badges

answered Apr 9 at 0:43

grcgrc

4199 bronze badges