- pandas - numpy - paths: - ./data/clean_honda_sell_data.csv - ./data_manipulation.py import pandas as pd import numpy as np import js from pyodide.http import open_url from data_manipulation import get_filtered_cars clean_df = pd.read_csv(open_url("./data/clean_honda_sell_data.csv"))

YOUR RELIABLE HONDA

What is your budget?

Fuel Type?

Transmission Preference?

Drivetrain Preference?

Minimum Prefered MPG?

Done, Now Submit

Description: Get Your Recommended Honda Models Based on Your Selection of Car Preferances. All Data is Retrieved From cars.com. For More Information on The Data Itself Click Below. Link: Tableau Link: Kaggle
from js import document from pyodide import create_proxy from js import getInfo, placeHondaModels try: import simplejson as json except (ImportError,): import json def getVariableData(*args, **kwargs): variable_info = getInfo() variable_list = json.loads(variable_info) variable_list[0] = int(variable_list[0]) variable_list[-1] = int(variable_list[-1]) model_list = get_filtered_cars(clean_df, variable_list[0], variable_list[1], variable_list[2], variable_list[3], variable_list[4]) placeHondaModels(json.dumps(model_list)) function_proxy = create_proxy(getVariableData) document.getElementById("submit").addEventListener("click", function_proxy)