PCA

 import pandas as pd
 from sklearn.datasets import load_iris
 from sklearn.preprocessing import StandardScaler
 from sklearn.decomposition import PCA
 import seaborn as sns
 import matplotlib.pyplot as plt
 df=pd.read_csv("iris.csv")
 print(df.head())
 print(df.isnull().sum())
 #df.fillna(df.mean(),inplace=True)
 df_encoded=pd.get_dummies(df,columns=['Species'],drop_first=True)
 print(df_encoded.head())
 x=df_encoded
 x_scaled=StandardScaler().fit_transform(x)
 pca=PCA(n_components=2)
 x_pca=pca.fit_transform(x_scaled)