Correlação de Pearson

import numpy as np 
import matplotlib.pyplot as plt
from scipy.stats import pearsonr
import pandas as pd

N = 100
X = np.linspace(-1,1,N)
erro = np.random.uniform(-1,1,N) # ruido a ser inlcuido
for sigma in np.arange(0,2,0.2)
  Y = -0.8*X + erro*sigma
  plt.plot(X,Y,'ro')
  corr, p_value = pearson(X,Y)
  corr = int(corr*100)/100
  string = "corr ="+ str(corr)
  plt.xlim(-1.5,1.5)
  plt.ylim(-2,2)
  plt.text(0.6,1.7, string , fontsize=15)
  plt.show(True)

data = pd.read_csv('data/iris.csv', header=(0))
corr2 = data.corr()
plt.figure(figsize=(7,5))
plt.imshow(corr2, cmap='Blues', interpolation='none', aspect='auto')
plt.colorbar()
plt.xticks(range(len(corr)), corr.columns, rotation='vertical')
plt.yticks(range(len(corr)), corr.columns); plt.suptitle('Correlation between variables'), fontsize=15, fontweight='bold')
plt.grid(False)
plt.show()