What You Will Learn!
- Use and manipulate complex and simple data structures
- Harness the full potential of DataFrames and numpy .array at run time
- Perform web scraping with BeautifulSoup4 and html5lib
- Execute advanced string search and manipulation with RegEX
- Handle outliers and perform data imputation with Pandas
- Use descriptive statistics and plotting techniques
- Practice data wrangling and modeling using data generation techniques
Description
For data to be useful and meaningful, it must be curated and refined. Data Wrangling with Python teaches you the core ideas behind these processes and equips you with knowledge of the most popular tools and techniques in the domain.
The course starts with the absolute basics of Python, focusing mainly on data structures. It then delves into the fundamental tools of data wrangling like NumPy and Pandas libraries. You'll explore useful insights into why you should stay away from traditional ways of data cleaning, as done in other languages, and take advantage of the specialized pre-built routines in Python. This combination of Python tips and tricks will also demonstrate how to use the same Python backend and extract/transform data from an array of sources including the Internet, large database vaults, and Excel financial tables. To help you prepare for more challenging scenarios, you'll cover how to handle missing or wrong data, and reformat it based on the requirements from the downstream analytics tool. The course will further help you grasp concepts through real-world examples and datasets.
By the end of this course, you will be confident in using a diverse array of sources to extract, clean, transform, and format your data efficiently.
About the Author
Samik Sen is currently working with R on Machine Learning. He has done his Ph.D. in Theoretical Physics. He has Tutored Classes for High-Performance Computing postgraduates and Lecturer at International Conferences. He has experience of using Perl on data, producing plots with gnuplot for visualization and latex to produce reports. He, then, moved to finance/football and online education with videos.
Dr. Tirthajyoti Sarkar works as a senior principal engineer in the semiconductor technology domain, where he applies cutting-edge data science/machine learning techniques for design automation and predictive analytics. He writes regularly about Python programming and data science topics. He holds a Ph.D. from the University of Illinois and certifications in Artificial Intelligence and Machine learning from Stanford and MIT.
Shubhadeep Roychowdhury works as a senior software engineer at a Paris-based cybersecurity startup, where he is applying the state-of-the-art computer vision and data engineering algorithms and tools to develop cutting-edge products. He often writes about algorithm implementation in Python and similar topics. He holds a master's degree in computer science from West Bengal University Of Technology and certifications in machine learning from Stanford.
Who Should Attend!
- Data Wrangling with Python is designed for developers, data analysts, and business analysts who are keen to pursue a career as a full-fledged data scientist or analytics expert.
