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import numpy as np import matplotlib.pyplot as plt from scipy.stats import linregress import matplotlib.animation as animation # Zadanie 1 years = np.array([2000, 2002, 2005, 2007, 2010]) percentages = np.array([6.5, 7.0, 7.4, 8.2, 9.0]) slope, intercept, _, _, _ = linregress(years, percentages) # Zadanie 3 def predicted_percentage(year): return slope * year + intercept year = 2000 while predicted_percentage(year) <= 12: year += 1 print("Year when unemployment rate exceeds 12%:", year) # Zadanie 4 fig, ax = plt.subplots() ax.scatter(years, percentages, label='Actual data') line, = ax.plot([], [], color='red', label='Regression line') def init(): line.set_data([], []) return line, def animate(i): x = np.linspace(years[0], years[-1], 1000) y = slope * x + intercept line.set_data(x[:i], y[:i]) return line, ani = animation.FuncAnimation(fig, animate, init_func=init, frames=len(years), interval=500, blit=True) plt.xlabel('Year') plt.ylabel('Unemployment Percentage') plt.title('Linear Regression Animation') plt.legend() plt.show()
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