kamath7

Price	Area	Location	No. of Bedrooms	Resale	MaintenanceStaff	Gymnasium	SwimmingPool	LandscapedGardens	JoggingTrack	RainWaterHarvesting	IndoorGames	ShoppingMall	Intercom	SportsFacility	ATM	ClubHouse	School	24X7Security	PowerBackup	CarParking	StaffQuarter	Cafeteria	MultipurposeRoom	Hospital	WashingMachine	Gasconnection	AC	Wifi	Children'splayarea	LiftAvailable	BED	VaastuCompliant	Microwave	GolfCourse	TV	DiningTable	Sofa	Wardrobe	Refrigerator
30000000	3340	JP Nagar Phase 1	4	0	1	1	1	1	1	1	1	0	1	1	0	1	0	1	1	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	0	0	0
7888000	1045	Dasarahalli on Tumkur Road	2	0	0	1	1	1	1	1	1	0	0	1	0	1	0	1	1	1	0	0	1	0	0	0	0	0	1	1	0	1	0	0	0	0	0	0	0
4866000	1179	Kannur on Thanisandra Main Road	2	0	0	1	1	1	1	1	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	0	0	0
8358000	1675	Doddanekundi	3	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0
6845000	1670	Kengeri	3	0	1	1	1	1	1	1	1	0	1	1	0	1	0	1	1	1	0	0	1	0	0	0	0	0	1	1	0	0	0	0	0	0	0	0	0
6797000	1220	Horamavu	2	0	0	1	1	1	1	1	1	0	1	1	0	1

kamath7

#Training set
from matplotlib.colors import ListedColormap
X_set, y_set = X_train, y_train
X1, X2 = np.meshgrid(np.arange(start = X_set[:, 0].min() - 1, stop = X_set[:, 0].max() + 1, step = 0.01),
                     np.arange(start = X_set[:, 1].min() - 1, stop = X_set[:, 1].max() + 1, step = 0.01))
plt.contourf(X1, X2, classifier.predict(np.array([X1.ravel(), X2.ravel()]).T).reshape(X1.shape),
             alpha = 0.75, cmap = ListedColormap(('red', 'green')))
plt.xlim(X1.min(), X1.max())
plt.ylim(X2.min(), X2.max())
for i, j in enumerate(np.unique(y_set)):

kamath7

const puppeteer = require('puppeteer');
(async()=>{
  try{
    const browser = await puppeteer.launch();
    const page = await browser.newPage();
    await page.goto('https://www.myntra.com/jeans/pepe-jeans/pepe-jeans-women-black-lara-lola-regular-fit-mid-rise-clean-look-stretchable-jeans/11280352/buy')
    // await page.waitForSelector()
    const body = await page.evaluate(()=>{
      return document.querySelector('.pdp-price').textContent;
    })

kamath7

import os

files = os.listdir()

for i in range (0,len(files)-1):
    fp = open(files[i],"r",encoding="utf-8")
    con = fp.readlines()
    newname = files[i].split(".")[0]+".txt"
    fn1 = open(newname,"w",encoding="utf-8")
    fn1.write(str(con))

kamath7

from tkinter import *
from tkinter import messagebox
from tkinter.filedialog import askopenfilename
import pandas as pd 




window = Tk() 
window.wm_title("Sampler")