Expected 2D array, got 1D array

Question

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.

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
– rafaelc, Commented Mar 27, 2019 at 0:17

gmds · Accepted Answer · 2019-03-27 01:11:48Z

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))

edited Mar 27, 2019 at 1:11

answered Mar 26, 2019 at 23:37

gmds

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5 Comments

grc Over a year ago

Thanks! But I got a new error: TypeError: len() takes exactly one argument (2 given)

rafaelc Over a year ago

@grc probably gmds meant (len(train), 1)

gmds Over a year ago

@grc @RafaelC Yup, moved new_shape out into a separate statement and forgot to shift the brackets. Edited.

grc Over a year ago

Thanks. Now it returns this ERROR: Data must be 1-dimensional

grc Over a year ago

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 · Accepted Answer · 2019-04-09 00:43:08Z

1

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))

answered Apr 9, 2019 at 0:43

grc

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