ValueError Found input variables with inconsistent numbers of samples 1 1000

Question

I am trying to create one Machine Learning model using LinearRegression model, but I am getting the below error.

import pandas as pd
data = pd.read_csv('db.csv')
x = data['TV']
y = data['Sales']
from sklearn.linear_model import LinearRegression
model = LinearRegression()
model.fit(x,y)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/user/Python.framework/Versions/3.6/lib/python3.6/site-packages/sklearn/linear_model/base.py", line 512, in fit
    y_numeric=True, multi_output=True)
  File "/user/Python.framework/Versions/3.6/lib/python3.6/site-packages/sklearn/utils/validation.py", line 531, in check_X_y
    check_consistent_length(X, y)
  File "/user/Python.framework/Versions/3.6/lib/python3.6/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, 1000]

Answer 1

Hi@akhtar,

Here you used x as your feature parameter and y as your predictor. But your feature parameter should not be 1D. So check shape of x and if it is 1D, then convert it from 1D to 2D.

$ x.shape
$ x.reshape(-1,1)

Hope this will help you.

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Comments

my x or feature variable is 2d but i also have same error .is there any other solution

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Can you share your code along with error?

Answer 2

Make sure your  data is 2 dimension and label is 1 dimension

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