Description
Cleaning data in a basic Python tutorial. If you’re looking for better ways to prepare data for analysis, it’s time to update your skillset and rethink your approach to data cleansing. In this course, instructor Miki Tebeka will show you some of the most important features of cleaning and collecting production data, with practical coding examples using Python to test your skills. Learn about the value of quality data to an organization, develop your ability to identify common errors and quickly correct them on the fly. Along the way, Miki offers cleanup strategies to help streamline your workflow, including tips for root cause analysis and simple tools to avoid mistakes.
This course is integrated with GitHub Codespaces, an instant cloud development environment that provides all the features of your favorite IDE without the need to set up a local machine. With GitHub Codespaces, you can get hands-on training anytime, anywhere, from any computer, using tools you’re likely to encounter on the job. Watch the Using GitHub Codespaces with This Course video to learn how to get started.
What you’ll learn in Data Cleaning in Python Essential Training
- Types of errors
- Duplicates
- Human errors
- Machine errors
- Design errors
- Scheme
- Examination
- Find lost data
- Basic knowledge
- Subgroups
- Organizing data and ordering data
- Process and data quality measures
- AND…
Data cleaning details in Python Essential Training
- Publisher: LinkedIn
- Lecturer: Miki Tebeka
- Level of training: beginner
- Training duration: 1 hour 5 minutes
Course headings
course images
Example video course
installation instructions
Once extracted, watch using your favorite player.
English subtitles
Quality: 720p
Download link
Password for file(s): www.downloadly.ir
size
252 MB