[Python] Linear Regression y_pred2 does not work properly

I want to make 2 different linear regressions for 2 diferent graphs (on the same figure). I have a problem with the y1_pred because it does not go for all the y axis where are scatters.

model1 = LinearRegression().fit(x, y)
r_sq1 = model1.score(x, y)
intercept1 = model1.intercept_
slope1 = model1.coef_
print(r_sq1)

y1_pred = intercept1 + slope1 * x

model2 = LinearRegression().fit(x2, y2)
r_sq2 = model2.score(x2, y2)
intercept2 = model2.intercept_
slope2 = model2.coef_
print(r_sq2)

y2_pred = intercept2 + slope2 * x2


axs[0].scatter(x, y, marker='o', color='aqua', label='1980-2000', edgecolors = 'black', linewidths = 1, s=500, zorder=4)
axs[1].scatter(x2, y2, marker='o', color='magenta', label='2000-2024', edgecolors = 'black', linewidths = 1, s=500, zorder=4)

axs[0].plot(x2, y2_pred, color='red', linewidth=4)
axs[1].plot(x, y1_pred, color='red', linewidth=4)


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