
Zapisz się tutaj
- –
- 2 Days
- Online via Teams
- Stata
Overview
Accessing and retrieving online data is increasingly vital for researchers and analysts. This two-day, interactive online seminar explores how to use Python—within Stata—to scrape and structure online data for analysis.
Participants will learn how to identify, extract, and convert online data (e.g., HTML tables or embedded content) into formats compatible with Stata (.txt, .csv). The course covers the basics of Python and HTML parsing, progressing to hands-on coding sessions. No prior coding experience is required, though a basic understanding of Stata or Python is beneficial.
Course Aims & Objectives
-
Introduce data scraping techniques using Python embedded within STATA.
-
Provide foundational knowledge of Python programming and HTML structure.
-
Equip participants with skills to identify and extract online data for quantitative analysis.
Key Skills Acquired
By the end of the course, students will understand:
-
Systems of linear equations and solution methods.
-
Matrix operations, transposition, determinants, and inverses.
-
Vector spaces, eigenvalues, and quadratic forms.
-
Calculus basics: derivatives, differentials, concavity/convexity.
-
Techniques in unconstrained optimisation for functions of a single variable.
Learning Outcomes
-
Technical Fluency: Gain practical experience with Python inside STATA, focusing on scripting for web scraping.
-
Data Acquisition Skills: Learn to extract useful, structured data from unstructured web pages.
-
Problem-Solving: Develop the ability to troubleshoot typical data scraping challenges and adapt code to new data sources.
-
Application-Oriented Learning: Build transferable skills applicable to academic, policy, and private-sector research projects.
Course Structure
Format: Two-day online seminar
Daily Sessions: 10:00–12:00 & 14:00–16:00 (BST)
Q&A: 1-hour concluding session on Day 2
Total contact time: 8 hours of instruction + 1 hour Q&A
Agenda
Day 1:
Lecture 1: Python Basics
- Introduction to variables, lists, functions and loops
- Understanding syntax and logic in Python
Lecture 2: Web Structure and HTML Fundamentals
- Exploring the structure of a webpage
- How Python reads and parses HTML
- Identifying data elements to be scraped
Day 2:
Lecture 3: Extracting and Saving Data
- Retrieving specific elements (tables, tags, text)
- Saving scraped data to .txt or.csv for Stata import
Lecture 4: Writing Efficient Python Code for Web Scraping
- Scraping data from multiple pages
- Automating repetitive scraping tasks
- Best practices for scaleable and clean code
Prerequisites
No specific readings are required. A basic knowledge of Stata and Python is useful but not essential.
Validate your login
Zaloguj
Stwórz nowe konto