Wine Quality Prediction Web Application
About:
This Web Application is based on the Machine-Learning Technology where the Decision-Tree Algorithm is used for the prediction of the Quality of Red Wine. The quality of a wine is determined by 11 input variables:
- Fixed acidity: Most acids involved with wine or fixed or nonvolatile. (do not evaporate readily)
- Volatile acidity: The amount of acetic acid in wine, which at too high of levels can lead to an unpleasant, vinegar taste.
- Citric acid: Found in small quantities, citric acid can add 'freshness' and flavor to wines.
- Residual sugar: The amount of sugar remaining after fermentation stops, it's rare to find wines with less than 1 gram/liter.
- Chlorides: The amount of salt in the wine.
- Free sulfur dioxide: The free form of SO2 exists in equilibrium between molecular SO2 (as a dissolved gas) and bisulfite ion.
- Total sulfur dioxide: Amount of free and bound forms of S02; in low concentrations, SO2 is mostly undetectable in wine, but at free SO2.
- Density: The density of water is close to that of water depending on the percent alcohol and sugar content.
- pH: Describes how acidic or basic a wine is on a scale from 0 (very acidic) to 14 (very basic); most wines are between 3-4.
- Sulfates: A wine additive which can contribute to sulfur dioxide gas (S02) levels, which acts as an antimicrobial.
- Alcohol: The percent alcohol content of the wine
Input Fields
Covid19 Scrapper Using BeautifulSoup
What is BeautifulSoup...??
Beautiful Soup is a Python library for pulling data out of HTML and XML files. It works with your favorite parser to provide idiomatic ways of navigating, searching, and modifying the parse tree. It commonly saves programmers hours or days of work.
Follow this link for full Documentation.
Introduction
This Project is based on Python and Web Scraping. The Web Scraping Technique is used here for the extraction of the useful data website and put inside our code to get only required Information and the BeautifulSoup Library is used for the web scrapping.
The Project will give the COVID19 cases information inside India.
The data is scrapped from this website.
Code
from bs4 import BeautifulSoup as bs
from urllib.request import urlopen as uReq
from selenium import webdriver
firefox_options = webdriver.FirefoxOptions()
firefox_options.add_argument('--no-sandbox')
firefox_options.add_argument('--headless')
firefox_options.add_argument('window-size=1920,1080')
firefox_options.add_argument('--disable-gpu')
driver = webdriver.Firefox(firefox_options=firefox_options)
site_url = "https://www.coronatracker.com/country/india/"
uClient = uReq(site_url) # requesting the webpage from internet
sitePage = uClient.read() # reading the webpage
uClient.close()
site_html = bs(sitePage, "html.parser") # parsing the webpage as html
review_url = "https://www.coronatracker.com/country/india/"
driver.get(review_url)
driver.implicitly_wait(30)
source = driver.page_source
html = bs(source, "html.parser") # parsing the webpage as HTML
bigboxes = html.findAll("div", {
"class": "flex flex-wrap -mx-2"})
confirmed_cases = bigboxes[0].find("p", {
"class": "text-2xl font-bold text-red-600"}).text.strip()
recovered_cases = bigboxes[0].find("p", {
"class": "text-2xl font-bold text-green-600"}).text.strip()
death_cases = bigboxes[0].find("p", {
"class": "text-2xl font-bold text-gray-600"}).text.strip()
cases_icu = bigboxes[0].find("div", {
"class": "text-gray-900 font-bold text-2xl mb-2"}).text.strip()
print("!-----INDIA CORONA OVERVIEW-----!")
print("TOTAL CONFIRMED CASES:", confirmed_cases)
print("TOTAL RECOVERED CASES:", recovered_cases)
print("TOTAL DEATHS:", death_cases)
print("CRITICAL CASES TREATED IN ICU:", cases_icu)
message = "TOTAL CONFIRMED CASES: " + confirmed_cases + "\nTOTAL RECOVERED CASES: " + recovered_cases + "\nTOTAL DEATHS: " + death_cases + "\nCRITICAL CASES TREATED IN ICU: " + cases_icu
from win10toast import ToastNotifier
toaster = ToastNotifier()
toaster.show_toast(title="!-----INDIA CORONA OVERVIEW-----!",
msg=message,
icon_path=None,
duration=10)Output
Github Link : Click here
Thank You
