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 colormaps
import pandas as pd
df.corrwith(dfa.iloc[0], axis=1)