Update pages/2_Data_CLeaning_and_Preprocessing.py

pages/2_Data_CLeaning_and_Preprocessing.py

@@ -31,6 +31,30 @@ if df is not None:
     st.subheader("Shape of the Dataset:")
     st.write(df.shape)
 
+    st.markdown("### Import Necessary Libraries:")
+    st.code("""
+    import numpy as np
+    import pandas as pd
+    import matplotlib.pyplot as plt
+    import seaborn as sns
+    import plotly.express as px
+    import warnings
+    warnings.filterwarnings('ignore')
+    
+    from sklearn.linear_model import LogisticRegression
+    from sklearn.neighbors import KNeighborsClassifier
+    from sklearn.model_selection import train_test_split, cross_val_score
+    from sklearn.preprocessing import StandardScaler, LabelEncoder
+    from sklearn.metrics import accuracy_score, classification_report, confusion_matrix, log_loss
+    
+    import optuna
+    import imblearn
+    from imblearn.under_sampling import RandomUnderSampler
+    from imblearn.over_sampling import RandomOverSampler, SMOTE
+    
+    import pickle
+    """, language="python")
+
     # Visualize Numeric Data (Histograms and Boxplots in subplots)
     numeric_columns = df.select_dtypes(include=['float64', 'int64']).columns
     if len(numeric_columns) > 0: