Systematic Data Cleaning in Python
IN PERSON
One of the most common problems in data science and statistics is messy data.
Missing values, misspellings, incorrect data types, multiple items in a single cell, and a range of other problems frequently plague even the best programmers.
This workshop will teach students a range of tricks to dealing with these and other data cleaning problems, offering a solid foundation for solving even the trickiest problems with messy data.
This is an intermediate-level workshop. You will need an understanding of Python and how to run Python code.
Those who have registered to take part will receive an email with full details in advance of the start time.
After taking part in this event, you may decide that you need some further help in applying what you have learnt to your research. If so, you can book a Data Surgery meeting with one of our training fellows.
More details about Data Surgeries.
If you’re new to this training event format, or to CDCS training events in general, read more on what to expect from CDCS training. Here you will also find details of our cancellation and no-show policy, which applies to this event.
If you're interested in other training on data analysis, statistics, and machine learning have a look at the following:
- Digital Method of the Month: Statistics
- Introduction to Statistics and Descriptive Statistics
- Finding Patterns Across Data
- Digital Method of the Month: Machine Learning
- Introduction to Machine Learning
- Statistical Methods: Null-hypothesis Testing with R
- Statistical Methods: Montecarlo Simulations with R
- Regression and Mixed Effects Modelling with R
- AI and Ethics
- Statistical Methods: Principal Component Analysis with R
Return to the Training Homepage to see other available events.
Digital Scholarship Centre
Digital Scholarship Centre, 6th floor
Main Library
University of Edinburgh
Edinburgh EH8 9LJ