Load the breast cancer dataset and plots it

load dataset and plot

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import io
from sklearn.datasets import load_breast_cancer
def do_plot():
    # Loading 
    data = load_breast_cancer()
    breast_cancer_df = pd.DataFrame(data['data'])
    breast_cancer_df.columns = data['feature_names']
    breast_cancer_df['target'] = data['target']
    breast_cancer_df['diagnosis'] = [data['target_names'][x] for x in data['target']]
    feature_names= data['feature_names']

    corr = breast_cancer_df[list(feature_names)].corr(method='pearson')

    f, ax = plt.subplots(figsize=(11, 9))
    cmap = sns.diverging_palette(220, 10, as_cmap=True)
    mask = np.zeros_like(corr, dtype=np.bool)
    mask[np.triu_indices_from(mask)] = True

    sns.heatmap(corr, mask=mask, cmap=cmap, vmax=.3, center=0,
                square=True, linewidths=.5, cbar_kws={"shrink": .5})

    # here is the trick save your figure into a bytes object and you can afterwards expose it via flas
    bytes_image = io.BytesIO()
    plt.savefig(bytes_image, format='png')
    bytes_image.seek(0)
    return bytes_image