preprocessing.py

import pandas as pd




# Function to read the CSV file into a DataFrame
def read_csv():
    # read the shopping.csv file using pandas library and return it
    df = pd.read_csv("shopping.csv")
    return df




# Function to check for duplicate rows in the DataFrame
def check_duplicates():
    # do not edit the predefined function name
    df = read_csv()
    # Calculate the number of duplicate rows using the duplicated() method and sum them
    return df.duplicated().sum()
    




# Function to drop duplicate rows from the DataFrame
def drop_duplicates():
    # do not edit the predefined function name
    df = read_csv()
    # Drop duplicate rows using the drop_duplicates() method with inplace=True
    df = df.drop_duplicates()
    return df




# Function to check for null (missing) values in the DataFrame
def check_null_values():
    # do not edit the predefined function name
    df = drop_duplicates()
    # Check for null values using the isnull() method and sum them for each column
    return df.isnull().sum()



# Function to remove rows containing null values from the DataFrame
def remove_null_values():
    # do not edit the predefined function name
    df = drop_duplicates()
    
    # Drop rows containing null values using the dropna() method with inplace=True
    df = df.dropna()
    return df



# Function to rename specific columns in the DataFrame
def rename_columns():
    # do not edit the predefined function name
    df = remove_null_values()
    # Rename columns 'reviews.text', 'reviews.title', and 'reviews.date' to 'reviews_text', 'reviews_title', and 'reviews_date' respectively
    df = df.rename(columns = {'reviews.text':'reviews_text', 'reviews.title':'reviews_title', 'reviews.date':'reviews_date'})
    return df