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Articles tagged with #data-science
Here are examples using the dataprep library for data preparation tasks: 1. Loading and Cleaning Data from dataprep.datasets import load_dataset from dataprep.clean import clean_headers # Load dataset df = load_dataset("titanic") # Clean column he...
1. Introduction to Scrapy What is Scrapy? Scrapy is an open-source web scraping framework for Python. It is designed for fast and efficient extraction of data from websites, handling large-scale scraping projects with ease. Features and Advantages ...
Introduction to Web Scraping with BeautifulSoup Using BeautifulSoup to Parse HTML Here’s how you can fetch and parse a webpage using requests and BeautifulSoup: from bs4 import BeautifulSoup import requests # Step 1: Fetch the HTML content url = "ht...
Suppose we have a dataset about students, with features like study hours ( \( x_1 \) ), attendance rate ( \( x_2 \) ), and previous grades ( \( x_3 \) ), and we want to predict whether they will pass an exam ( \( y = 1 \) for "pass" and \( y = 0 \) f...
Suppose we have a dataset containing information about passengers on the Titanic and whether they survived. The features include class ( \( x_1 \) : Pclass), sex ( \( x_2 \) ), age ( \( x_3 \) ), and fare paid ( \( x_4 \) ). Based on these features, ...
Ridge and Lasso Regression with House Price Example Suppose we have a dataset showing the relationship between the size of a house ( \( x \) , in square feet) and its price ( \( y \) , in thousands of dollars). To add complexity, let’s include additi...