Master Data Cleaning: Python, Excel & Power Query
https://WebToolTip.com
Published 7/2025
Created by Ravi Singh
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 19 Lectures ( 1h 19m ) | Size: 1.32 GB
Master practical data cleaning skills with Excel formulas, Power Query automation, and Python scripts.
What you'll learn
Identify and fix messy, inconsistent, incomplete, and duplicate data across various sources.
Use functions like IF(), TRIM(), TEXT(), VLOOKUP(), and DATA VALIDATION to clean and format spreadsheets effectively.
Import messy files, transform column headers, remove blanks, filter rows, and automate repetitive cleaning using Power Query.
Use Python’s pandas library to load, clean, merge, and transform real-world datasets using functions like .dropna(), .fillna(), .str.replace(), and .groupby().
Standardize inconsistent date formats, correct column naming issues, and unify naming conventions using both Excel and code.
Identify and remove exact and near-duplicate records using Excel tools, Power Query logic, and pandas .duplicated() methods.
Build workflows that allow you to clean new data in one click using Power Query and reusable Python scripts.
Requirements
Ability to navigate files, folders, and applications confidently.
Basic understanding of Excel spreadsheets
Experience with formulas like SUM, IF, and VLOOKUP (helpful but not required)
Understanding of basic Python syntax (print(), variables, lists/dictionaries)
No advanced coding required — Python basics will be reinforced in the course
Willingness to try tools like Power Query and Python/pandas even if you're new to them.
Power Query is built-in from Excel 2016+
Python (v3.7 or later) Installed via Anaconda or Python org
Jupyter makes it easy to follow step-by-step
VS Code or any other IDE is also fine
Internet Connection Required to download data files, Python packages, or follow along with GitHub-hosted resources.