[SOLVED] 3d Surface plot from linear model with matplotlib in Python

3d Surface plot from linear model with matplotlib in Python

The following code was working fine. But now it is throwing the following error:

AttributeError: 'Series' object has no attribute 'reshape'

Code:

from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import statsmodels.formula.api as sm
from matplotlib import cm

csv = pd.read_csv('http://www-bcf.usc.edu/~gareth/ISL/Advertising.csv', index_col=0)
print(csv)
model = sm.ols(formula='sales ~ TV + radio', data = csv)
fit = model.fit()

fit.summary()

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

x_surf = np.arange(0, 350, 20)                # generate a mesh
y_surf = np.arange(0, 60, 4)
x_surf, y_surf = np.meshgrid(x_surf, y_surf)

exog = pd.core.frame.DataFrame({'TV': x_surf.ravel(), 'radio': y_surf.ravel()})
out = fit.predict(exog = exog)
ax.plot_surface(x_surf, y_surf,
                out.reshape(x_surf.shape),
                rstride=1,
                cstride=1,
                color='None',
                alpha = 0.4)

ax.scatter(csv['TV'], csv['radio'], csv['sales'],
           c='blue',
           marker='o',
           alpha=1)

ax.set_xlabel('TV')
ax.set_ylabel('Radio')
ax.set_zlabel('Sales')

plt.show()

Solution

You have to call the reshape function on the "values" attribute of the "out" Series object:

out = fit.predict(exog = exog)
ax.plot_surface(x_surf, y_surf,
                out.values.reshape(x_surf.shape),
                rstride=1,
                cstride=1,
                color='None',
                alpha = 0.4)