Plotting Multiple Linear Regression Model in Python

Question

I am trying to plot results of Multiple Linear Regression model in python but the output is wrong as salary values are all zero here. Salary is a dependent variable which depends on age, Years of Experience, etc.

Salary values should be from 30000 to 50000. However, the results tell a different story. What am I missing?

# all required libraries 
import pandas as pd 
import warnings  
import numpy as np  

# For data visualizing   
import seaborn as sns  

#%matplotlib notebook
import matplotlib.pyplot as plt  
from mpl_toolkits.mplot3d import Axes3D  
#%matplotlib inline 
%matplotlib widget

 
# For building the required model  
from sklearn import linear_model  


df = pd.read_csv('ml_data_salary.csv')

# Plotting a 3-D plot for visualizing the Multiple Linear Regression Model  
  
# Preparing the data  
X = df[['age', 'YearsExperience']].values.reshape(-1,2)  
Y = df['Salary']  
  
# Create range for each dimension
x = X[:, 0]
y = X[:, 1]
z = Y

xx_pred = np.linspace(25, 40, 30)  # range of age values
yy_pred = np.linspace(1, 10, 30)  # range of experience values
xx_pred, yy_pred = np.meshgrid(xx_pred, yy_pred)
model_viz = np.array([xx_pred.flatten(), yy_pred.flatten()]).T

# Predict using model built on previous step
ols = linear_model.LinearRegression()
model1 = ols.fit(X, Y)
predicted = model1.predict(model_viz)

# Evaluate model by using it's R^2 score 
r2 = model.score(X, Y)

# Plot model visualization
plt.style.use('default')

fig = plt.figure(figsize=(12, 4))

ax1 = fig.add_subplot(131, projection='3d')
ax2 = fig.add_subplot(132, projection='3d')
ax3 = fig.add_subplot(133, projection='3d')

axes = [ax1, ax2, ax3]

for ax in axes:
    ax.plot(x, y, z, color='k', zorder=15, linestyle='none', marker='o', alpha=0.5)
    ax.scatter(xx_pred.flatten(), yy_pred.flatten(), predicted, facecolor=(0,0,0,0), s=20, edgecolor='#70b3f0')
    ax.set_xlabel('Age', fontsize=12)
    ax.set_ylabel('Experience', fontsize=12)
    ax.set_zlabel('Salary', fontsize=12)
    ax.locator_params(nbins=4, axis='x')
    ax.locator_params(nbins=5, axis='x')

ax1.view_init(elev=27, azim=112)
ax2.view_init(elev=16, azim=-51)
ax3.view_init(elev=60, azim=165)

fig.suptitle('Multi-Linear Regression Model Visualization ($R^2 = %.2f$)' % r2, fontsize=15, color='k')

fig.tight_layout()

Answer 1

The data I was using was messed up. I used the Kaggle dataset and it worked fine. Thank you ands.