"Value Error: x and y must be same size" error. Multiple Linear Regression

user_15524294 0
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import numpy as np
import matplotlib.pyplot as plt
import pandas as pd

dataset=pd.read_csv("Marketing_Data.csv")
X = dataset.iloc[:, :-1].values
y = dataset.iloc[:, -1].values

from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 1/3, random_state = 0)

from sklearn.linear_model import LinearRegression
regressor = LinearRegression()
regressor.fit(X_train, y_train)
lin_reg = LinearRegression()
lin_reg.fit(X,y)

y_pred = regressor.predict(X_test)
np.set_printoptions(precision = 2)
plt.scatter(X, y, color = 'red')
plt.plot(X, lin_reg.predict(X), color = 'blue')
plt.title("Sales")
plt.show()

I am trying to write a multiple linear regression. There are three independent variables and one dependent variable. I get a

Value Error: x and y must be same size

and an empty matplotlib graph.

Tracebak:

  File "||file path comes here||\untitled0.py", line 20, in <module>
    plt.scatter(X, y, color = 'red')

  File "C:\Anaconda\lib\site-packages\matplotlib\pyplot.py", line 2890, in scatter
    __ret = gca().scatter(

  File "C:\Anaconda\lib\site-packages\matplotlib\__init__.py", line 1438, in inner
    return func(ax, *map(sanitize_sequence, args), **kwargs)

  File "C:\Anaconda\lib\site-packages\matplotlib\cbook\deprecation.py", line 411, in wrapper
    return func(*inner_args, **inner_kwargs)

  File "C:\Anaconda\lib\site-packages\matplotlib\axes\_axes.py", line 4441, in scatter
    raise ValueError("x and y must be the same size")
linear-regression machine-learning python
2 Answers

plt.scatter expects both x and y to be of shape (n, ), so if your X is 2-or-higher dimensional it won't work.

Since you are doing multiple linear regression and your X has many dimensions, you'll need something other than a scatterplot. (Or just pick one dimension of X to be the x-axis for the plot.)

user_117513600

I think you are getting the error because of how you are using .iloc for variables X and Y. Do not know what your csv data looks like so apologies if this is not what you are looking for...

Your X .iloc returns an NxN array, kind of like a matrix (pandas/numpy treats it as an array), and returns all rows in your dataset minus the last column (you are telling it to ignore the last column with :-1).

Your y .iloc returns 1xN array and will return the last column of your dataset.

It looks like:

x = dataset.iloc[:, :-1].values

>>> [['Col1Row1_val', 'Col2Row1_val']
     ['Col1Row2_val', 'Col2Row2_val']]

y = dataset.iloc[:, -1].values 

>>> ['lastColRow1_val', 'lastColRow2_val']

The x and y .iloc should be similar or composed in a way where x and y are both, for example, a 1xN array or NxN array.

Or use a plot other than scatter

user_152431370
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