Python Regular Expressions - Real-Life Use Cases
Let's tackle some of the use cases of regular expressions together, such as web scraping, data analysis or web scraping.
- No slides, no boring theory, no rambling, no chitchat. Just coding
- Coding exercises, notebooks and real-life examples are included
- Certificate of completion is included!
What others have to say about my courses?
- "What an incredible value and learning experience!" by Sean A.
- "Excellent material. Kudos to a great instructor with a vast level of creativity." by Anthony W.
- "The instructor is an excellent professional, skillful and engaging." by Georgios T.
Why would you take this course?
- Do you want to polish your Regular Expressions skills without spending money on books and boring theoretical courses?
- Have you ever been confused by how and where are Regular Expressions used in real-life scenarios and applications?
- Would you like to be able to perform Intermediate to Advanced pattern matching tasks using the power of Python?
"As a Python beginner, I find this course is concise, easy to understand and structured. Also, Mihai responds to my questions during the course promptly. I highly recommend this training course." by Johnny Wang
What are the steps you're going to take from Intermediate to Advanced level skills?
- Section 1 - Introduction
- Section 2 - Regular Expressions in Excel Spreadsheets: Filtering Employee Data
- Section 3 - Regular Expressions in Data Analysis: Filtering HTML Page Data
- Section 4 - Regular Expressions in Web Scraping: Scraping & Filtering Data
- Section 5 - Final Section
"I can say this man is going on smoothly and perfectly, explaining in the most empirical way." by Kolapo A.
Important information before you enroll!
- In case you're not happy with the course, don't forget you are covered by a 30-day money back guarantee, full refund.
- Once enrolled, you have unlimited, 24/7, lifetime access to the course (unless you drop the course during the first 30 days).
- You will benefit from my full support regarding any question and your course colleagues will help you, as well.
"Very thorough course. Includes plenty of details and examples without being boring. Explanations are given at a very practical level." by Gary Scarr
Let's get started! Enroll now and I'll see you in the first lecture!
My name is Mihai and I am the founder and main Python instructor at EpicPython.io.
I have a BS degree in Telecommunications and Information Technology from University Politehnica of Bucharest, Romania and also the CCNP, CCNA, CCDA, JNCIA and ISTQB CTFL certifications.
✔ What are my credentials?
▪ Work experience in Networking and Quality Assurance Engineering.
▪ Used Python vastly in Network Automation and Test Automation.
▪ Certified professional: Cisco, Juniper and ISTQB certifications.
▪ Teaching courses on various e-learning platforms since 2015.
▪ Tens of thousands of satisfied students, 4.6 / 5 average course rating.
✔ What are my students saying about the kind of courses I create?
"What an incredible value and learning experience!" by Sean A.
"Excellent material. Kudos to a great instructor with a vast level of creativity." by Anthony W.
"I can say this man is going on smoothly and perfectly, explaining in the most empirical/foundational way." by Kolapo A.
I am constantly improving my content and teaching methods, providing my students with the best learning experience possible, helping thousands to take the next step in their careers.
I'll see you inside the courses!
StartBuilding the setup for this section (2:30)
StartDownload the Necessary Resources
StartLoading and Handling an Excel Workbook in Python (8:03)
StartNotebook - Preparing the Data for Filtering
StartScenario number 1 - Filtering Data in Excel Files (8:15)
StartScenario number 2 - Filtering Data in Excel Files (6:46)
StartScenario number 3 - Filtering Data in Excel Files (4:47)
StartScenario number 4 - Filtering Data in Excel Files (3:57)
StartScenario number 5 - Filtering Data in Excel Files (4:03)
StartNotebook - Solutions for the scenarios
StartBuilding the setup for this section (8:22)
StartNotebook - Introduction to Pandas
StartWorking with HTML content using Pandas (9:02)
StartNotebook - Initial Code
StartScenario number 1 - Filtering Data in Pandas DataFrames (6:58)
StartScenario number 2 - Filtering Data in Pandas DataFrames (3:56)
StartScenario number 3 - Filtering Data in Pandas DataFrames (3:52)
StartScenario number 4 - Filtering Data in Pandas DataFrames (3:20)
StartScenario number 5 - Filtering Data in Pandas DataFrames (4:18)
StartNotebook - Solutions for the scenarios