import warnings
warnings.filterwarnings('ignore')

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

# Scale
from sklearn.preprocessing import StandardScaler

# KMeans Clustering
from sklearn.cluster import KMeans

# Hierarchial Clustering
from scipy.cluster.hierarchy import linkage
from scipy.cluster.hierarchy import dendrogram
from scipy.cluster.hierarchy import cut_tree

df = sns.load_dataset('iris')
df.head()

df.sample(5)

df['species'].value_counts()

df.shape