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import pandas as pd
from sklearn.model_selection import train_test_split
def load_data(file_path):
"""Load data from a CSV file."""
return pd.read_csv(file_path)
def clean_data(df):
"""Clean the dataset by handling missing values and duplicates."""
df = df.dropna()
df = df.drop_duplicates()
return df
def preprocess_data(df, target_column):
"""Preprocess the data by splitting into features and target."""
X = df.drop(columns=[target_column])
y = df[target_column]
return X, y
def split_data(X, y, test_size=0.2, random_state=42):
"""Split the data into training and testing sets."""
return train_test_split(X, y, test_size=test_size, random_state=random_state)
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