Presented at School of Data training conducted in collaboration with the Open Data PH Taskforce in the Philippines, May 2014.

1. An Introduction to
data cleaning with
spreadsheets
Anders Pedersen, @anpe
School of Data

2. Spreadsheets: The beginning of
each and every data story
• Which were the top growth sectors in this
quarter?
• What was the crime in the capital region in
2013 compared to 2012?
• Is there a house bubble waiting around the
corner?

3. It is time for journalists themselves to
tame this beast called spreadsheets!

4. Spreadsheets: Excel or
google docs

5. Some basic terminology
• data is organized in rows and columns
(rows go across the page, columns go top
down)
• each field holding data is called a cell
• Rows are numbered,
• columns are referred to by letters
• each cell has column and a row, or a
specific code (e.g. A1 is the top left cell

6. Some key features to
explore today
• Sorting and filtering
• Basic formulas
• Pivot tables
Tricky bits:
- don’t include summaries in pivot table
- pivot tables cannot remember when you
change your data

7. Data sources for exercise
• Education: Secondary school enrollment for
2012 from Data.gov.ph
http://data.gov.ph/catalogue/dataset/sy-
2012-enrollment-data-secondary

8. Sorting - finding the best
and the worst
• The 10 best paid sectors
• The 10 oldest cities
• The 10 poorest countries
• …
• If excel is a tool box for journalists, sorting
is the hammer!

9. How to sort
• 1) Mark all your data
• 2) In the Data tab go to
sort range

10. Sorting...
• 3) Check the Data has
header row check box
• 4) Select the
column you want to
sort

11. Filtering - getting a better
sense of your data
• 1) Turn on Filtering
via the Data tab
(Data → Filter)

12. Filtering...
• 2) Filter options now appear at top

13. Filtering...
• 3) Now click on the
• blue triangular arrow

14. Filtering...
• 4) Select the section
you wish to filter

15. Filtering...
• 5) A green arrow
will now appear on top
of the column

16. Moving forward!
• Sorting and filtering - check!
• Basic formulas
• Pivot tables

17. Basic formulas
• Let us know try to sum up some of the
values in the dataset…
• What is it good for: when you do analysis
and when you need to check if calculations
by your colleagues are right

18. Basic formulas
• Go to column H: In the second row
(cell H2), type “=sum(f2+g2)”

19. Basic formulas
• We now have a sum
• Now try to see if this cell can be calculated
for average “=average(f2:g2)”

20. Basic formulas
• You can also copy your calculations across
cells

21. Now only Pivot tables to go
• Sorting and filtering - check!
• Basic formulas - check!
• Pivot tables

22. Pivot tables
• finding stories inside datasets
• particularly well fitting for organised
datasets with clear categories and sub-
categories

23. Pivot tables
• Mark the full area of the dataset
• Go to Data → Pivot table report

24. Pivot tables
• Pivot tables allows you to work on rows,
column values and filters
• We start by dropping
a column header into Rows
• Then we drop one of our
value columns into Values

25. Basic formulas
• We now have a nice summary of the
budget for each department

26. Filtering pivot tables
• We can now go ahead and filter the Pivot
table
• Add the column you wish
to filter by

27. Filtering pivot tables
• Then select one or more categories within
the column you
wish to keep

28. Pivot tables
• We can finally add several value columns
to the pivot table

29. Exercises
• Find the sectors of the national budget that
grew the most in percentage
• Identify the budget lines, which had the
biggest absolute increase in the budget
• Generate a pivot table based on the
national budget comparing 2014 and 2013
in specific sectors