# # numpy : approximations de l'action coca-cola # Vincent Legat - 2018 # Ecole Polytechnique de Louvain # from numpy import * from pandas import read_csv import matplotlib from matplotlib import pyplot as plt matplotlib.rcParams['toolbar'] = 'None' matplotlib.rcParams['lines.linewidth'] = 1 plt.rcParams['figure.facecolor'] = 'silver' def computeApproximation(X,U,n): x = linspace(X[0],X[-1]+100,100) uh = polyval(polyfit(X,U,n),x) plt.ylim((45,49)) plt.xticks([]) plt.plot(X,U,'-r') plt.plot(x,uh,'-b') # # -1- Les données # csvData = read_csv('stockCocaCola.csv') X = list(csvData["time"]) U = list(csvData["value"]) plt.figure("Coca Cola stock") plt.ylim((45,49)) plt.xticks([]) plt.plot(X,U,'-r') # # -2- Les prédictions financières # plt.figure("Predictions of Coca Cola stock value") plt.subplot(2,2,1) computeApproximation(X,U,1) plt.subplot(2,2,2) computeApproximation(X,U,4) plt.subplot(2,2,3) computeApproximation(X,U,6) plt.subplot(2,2,4) computeApproximation(X,U,8) plt.show()