def clean_data(df: pd.DataFrame) -> pd.DataFrame:
    """Clean and preprocess DataFrame.

    Args:
        data: Input DataFrame

    Returns:
        Cleaned DataFrame
    """
    df.drop(["Wiki Page"], axis=1, inplace=True)

    # Drop duplicates
    df = df.drop_duplicates(subset='Title', keep='first')

    # Get object columns
    col_obj = df.select_dtypes(include=["object"]).columns

    # Clean string columns
    for col in col_obj:
        # Strip whitespace
        df[col] = df[col].str.strip()

        # Replace unknown/empty values
        df[col] = df[col].apply(
            lambda x: None if pd.isna(x) or x.lower() in ["", "unknown"] 
            else x.capitalize()
        )

    # Drop rows with any null values
    df = df.dropna(how="any", axis=0)

    return df

movies = clean_data(movies).head(1000)
movies.head()