Introduction to Data Manipulation with Excel
This online course provides a practical introduction to the most important ideas in data manipulation which is a fundamental part of data analysis.
This course isn’t just about learning a skill; it’s about gaining a practical set of tools that can make a real difference in your work with data. It has been created by data analysts who have collectively spent thousands of hours themselves preparing data, and who understand the most important techniques to develop, the pitfalls to avoid, and the enjoyment of manipulating data.
This online course has been developed by The Data Lab, in partnership with the Bayes Centre at the University of Edinburgh, effini and the DDI Data Skills Gateway. Please note: we are running this course as a pilot, so it is a requirement for learners to provide feedback on the course.
How is this course delivered?
Dates: 6th May to 1st July.
This course is delivered online and runs over a 6 week period. Learners can work through the course at their own pace but it is expected to take around 25 hours to complete.
There are also weekly live tutorials on Thursdays from 3pm – 4pm which provide the opportunity to consolidate learning and ask any questions.
What will I learn
By the end of the course, you will be able to:
- Describe the purpose of data manipulation and state where data manipulation fits within the data analysis process.
- Explain why Excel is a useful software tool for data manipulation.
- Describe the difference between structured, semi-structured and unstructured data.
- Describe common display formats.
- Use Excel to select, reorder and reformat columns.
- Use Excel to filter, sort and deduplicate rows.
- Use Excel to subset data to choose the parts you are interested in.
- Use Excel to create new variables by extracting data; combining data; and performing calculations, including using conditional formulas to do so.
- State ways of handling missing or zero values when creating variables.
- Use Excel to drop rows and columns that are not needed.
- State common naming conventions commonly used to name variables.
- Rename variables using Excel.
- Remove metadata from a dataset.
- Explain the differences between left, right, inner and outer joins.
- Explain some common causes of issues when combining datasets.
- Use Power Query in Excel to append rows to a dataset.
- Use Power Query in Excel to perform left, right, inner and outer joins.
How to Apply
If you would like to participate in the pilot for this course please contact Isobel.Dew@ed.ac.uk.
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