7.1 this code have problem. meybe is my error but i need someone helping me. thanks thanks thanks.

[Usxcy]

this is codes

Plot

fig, ax = plt.subplots()
ax.scatter(us_change["Income"], us_change["y"], c="k")
ax.plot(us_change["Income"],
mf.forecast_fitted_values()["LinearRegression"])

Customize the plot

ax.set_xlabel("Income (quarterly % change)")
ax.set_ylabel("Consumption (quarterly % change)")
plt.show()

this is error
NameError Traceback (most recent call last) Cell In[4], line 4 2 fig, ax = plt.subplots() 3 ax.scatter(us_change["Income"], us_change["Consumption"], c="k") ----> 4 ax.plot(us_change["Income"], mf.forecast_fitted_values()["LinearRegression"]) 6 # Customize the plot 7 ax.set_xlabel("Income (quarterly % change)") NameError: name 'mf' is not defined

[mergenthaler]

Hi @Usxcy, thanks so much for the question. From just looking at your code you might be forgetting to instantiate the MLForecast object.

from mlforecast import MLForecast
from sklearn.linear_model import LinearRegression

# Create the MLForecast object
mf = MLForecast(models=LinearRegression() , freq="QS-OCT")

# Fit the model
mf.fit(us_change)

# Predict
predictions = mf.predict(7)


# Now you can plot 

Here is a complete guide: https://nixtlaverse.nixtla.io/mlforecast/index.html#visualize-results

[mergenthaler]

@Usxcy, was the answer helpful or did I perhaps misunderstood your point?

[mergenthaler]

@Usxcy, I will proceed and mark this as closed. Feel free to reopen if necessary.

[Usxcy]

it is you help that my problem have been solved. think again.