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utils.js
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utils.js
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const regression = require("regression");
const math = require("mathjs");
const sleep = (ms) => new Promise((res) => setTimeout(res, ms));
const getDatas = async ($, rows) => {
const data = rows
.map((i, row) => {
const columns = $("td", row);
const km =
parseFloat(
$(columns.get(4)).text().trim().replace(".", "").replace(",", ".")
) || 0;
const year = parseFloat($(columns.get(3)).text().trim()) || 0;
const price =
parseFloat(
$("span", columns.get(6))
.text()
.trim()
.replace("TL", "")
.trim()
.replace(".", "")
.replace(",", ".")
) || 0;
return {
price,
km,
year,
};
})
.get()
.filter((item) => item.price > 0 && item.km > 0 && item.year > 0);
return data;
};
const getHTMLContent = async (page) => {
await sleep(2000);
/*await page.screenshot({
path: +new Date().getTime() + "testresult.png",
fullPage: true,
});
*/
await page.waitForSelector(".searchResultsRowClass");
const htmlContent = await page.content();
return htmlContent;
};
const calculateIQR = (prices) => {
prices.sort((a, b) => a - b);
let q1 = prices[Math.floor(prices.length / 4)];
let q3 = prices[Math.floor((prices.length * 3) / 4)];
let iqr = q3 - q1;
return { q1, q3, iqr };
};
const calculateCorrelation = (prices, kms) => {
let meanPrice = math.mean(prices);
let meanKM = math.mean(kms);
let numerator = 0;
let denominatorPrice = 0;
let denominatorKM = 0;
for (let i = 0; i < prices.length; i++) {
let priceDiff = prices[i] - meanPrice;
let kmDiff = kms[i] - meanKM;
numerator += priceDiff * kmDiff;
denominatorPrice += priceDiff ** 2;
denominatorKM += kmDiff ** 2;
}
let denominator = Math.sqrt(denominatorPrice * denominatorKM);
return numerator / denominator;
};
const analyzeDataV2 = (carData, KM) => {
let prices = carData.map((car) => car.price);
let kms = carData.map((car) => car.km);
let mean = prices.reduce((a, b) => a + b, 0) / prices.length;
prices.sort((a, b) => a - b);
let median = prices[Math.floor(prices.length / 2)];
let { q1, q3, iqr } = calculateIQR(prices);
let regressionResult = regression.linear(
carData.map((car) => [car.km, car.price])
);
let predictedPrice =
regressionResult.equation[0] * KM + regressionResult.equation[1];
const correlation = calculateCorrelation(prices, kms);
return { mean, median, q1, q3, iqr, predictedPrice, correlation };
};
module.exports = {
getDatas,
getHTMLContent,
analyzeDataV2,
};