correlation python
import numpy as np
import scipy.stats
x = np.arange(15, 20)
y = np.arange(5, 10)
stat, p = scipy.stats.pearsonr(x, y)correlation python
import numpy as np
import scipy.stats
x = np.arange(15, 20)
y = np.arange(5, 10)
stat, p = scipy.stats.pearsonr(x, y)correlation analysis of dataframe python
import seaborn as sns
#load the dataset
df = sns.load_dataset('iris')
#calculate correlation
corr_matrix = df.corr('pearson') #kind of correlation-> ‘pearson’, ‘kendall’, ‘spearman’
#plot correlation
corr_matrix.style.background_gradient(cmap='coolwarm')
# 'RdBu_r', 'BrBG_r', & PuOr_r are other good diverging colormapsCopyright © 2021 Codeinu
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