"Expecting 2D Array Error" while Working with Sklearn in Python

Question

I started learning Sklearn today and wanted to set up a simple regression model using one X value, then use that model to predict the next 5 Y values.

I keep getting the following error:

ValueError: Expected 2D array, got 1D array instead:
array=[ 1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20].
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.

This is all of the code I currently have:

import numpy as np
from sklearn.linear_model import LinearRegression
from sklearn import datasets
from sklearn import linear_model
from sklearn.metrics import mean_squared_error, r2_score

histYlist = [65.98685126, 56.78302597, 94.79205606, 20.70468985, 90.25959717, 60.6194846, 27.08425346, 15.8715957, 69.41508813, 7.362478092, 82.45058027, 53.44812953, 32.52252966, 43.1278569, 91.2854072, 99.80998002, 89.02868447, 45.31115274, 98.65222136, 70.56292757]
histY = np.array(histYlist)
histY.reshape(-1,1)
histXlist = list()
i = 1
for items in histY :
    histXlist.append(i)
    i = i + 1

histX = np.array(histXlist)
histX.reshape(-1,1)
print(histX.shape, histY.shape)
#print(histX)
#rint(len(histX))

model = linear_model.LinearRegression()

model.fit(histX,histY)

X_pred = list()
newPredicts = 5
j = 1
while j <= newPredicts :
    X_pred.append(len(histX) + j)
    j = j + 1
#print(predictX)

Y_pred = model.predict(X_pred)
print(Y_pred)

Hopefully you can help or lead me in the right direction thanks!

I believe you have to reshape X_pred too, just like you did for histX and histY. — Mario Ishac
– Mario Ishac, Commented Aug 8, 2020 at 19:30
@MarioIshac from what I can gather the: "model.fit(histX,histY)" line is causing a traceback — Lazed
– Lazed, Commented Aug 8, 2020 at 19:35

caiobaguida · Accepted Answer · 2020-08-08 19:45:39Z

1

The np.array.reshape() method only returns the reshaped array without updating its object. If you want to use the reshaped object you should store in a new variable or update the original variable. I tried the former with your code and it now works.

So instead of:

histX.reshape(-1,1)

You should do:

histX = histX.reshape(-1,1)

And the same for the variables histY and X_pred.

For the documentation, see: numpy.reshape, where it states

numpy.reshape(a, newshape, order='C')[source]

Gives a new shape to an array without changing its data.

answered Aug 8, 2020 at 19:45

caiobaguida

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2 Comments

Lazed Over a year ago

Jesus, I'm an idiot. Sometimes it's nice to have another pair of eyes look over your code.

caiobaguida Over a year ago

(Almost) nothing that the documentation can't solve.

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