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)