from sklearn.decomposition import PCA
from sklearn.cluster import KMeans
import pandas as pd

class FeatureEngineering:
    def __init__(self, dataframe):
        self.dataframe = dataframe

    def pca(self, n_components):
        pca = PCA(n_components=n_components)
        df_pca = pca.fit_transform(self.dataframe)
        df_pca = pd.DataFrame(df_pca)
        return df_pca

    def kmeans(self, n_clusters):
        kmeans = KMeans(n_clusters=n_clusters, random_state=42)
        cluster_labels = kmeans.fit_predict(self.dataframe)
        self.dataframe['kmeans'] = cluster_labels
        return self.dataframe