Spreadsheet Skills Every Reporter Can Learn in a Weekend
You do not need to code to work with data. This guide covers sorting, filtering, pivot tables, cleaning and simple rates in a spreadsheet, with a short practice exercise.
AT A GLANCE
- 1Spreadsheets go far. Sorting, filtering and pivot tables answer many reporting questions.
- 2Clean before you analyse. Messy data is the most common source of wrong numbers.
- 3Check your own work. Simple cross-checks catch most spreadsheet errors.
Data journalism sounds intimidating, but much of it starts in a spreadsheet. If you can sort, filter, count and calculate a rate, you can find stories that others miss. This guide covers the essentials, explained without code, and ends with a short exercise you can try over a weekend.
Start by understanding the data
Before you do anything, find out where the data came from, what each column means, how it was collected and what period it covers. Look for a data dictionary or a note from the publisher. If the data was compiled by a public body, ask what is missing or approximate. Many wrong stories begin with a misunderstanding of what the numbers represent.
Clean the data
Real data is messy. Names are spelled differently, dates are formatted in several ways and some cells are blank. Make a copy of the original file and keep it untouched. Work in the copy and note every change you make.
- Remove extra spaces and fix inconsistent spellings.
- Make sure that dates and numbers are stored as dates and numbers, not text.
- Look for duplicates and decide how to handle them.
- Mark blank cells and decide whether blank means zero or unknown.
- Check for outliers, such as a value that is ten times higher than the rest.
Sort and filter
Sorting a column from largest to smallest or the reverse is the simplest and often the most useful operation. It shows you the extremes. Filtering lets you look only at rows that meet a condition, such as a particular year or place. Together they answer questions like which areas have the highest values and how they changed.
Pivot tables
A pivot table summarises data by group. You pick a category, such as a region or a type of event, and a value to count or add up. It can turn thousands of rows into a short table in seconds. Learn how to change the grouping and the calculation, and always check that the totals match the original data.
Rates, percentages and change
Raw counts can mislead. A large area will have more of almost everything than a small one. To compare fairly, use a rate, such as events per thousand people, or a percentage of the total. To describe change, calculate the difference and divide by the starting value. Be careful with small numbers, where a tiny change can look dramatic.
Most of the errors I see are not complicated. They are a wrong denominator or a column that was never cleaned. — a data editor at a regional newsroom
Check your work
- Compare your totals with the totals in the source.
- Calculate a key figure in two different ways and see if they agree.
- Look at a few rows by hand to confirm that the formula behaves as you expect.
- Ask a colleague to review your steps.
- Write down your method so that others can follow it.
Practice exercise
Find a small public dataset about a topic you know, such as local public spending or weather readings. Spend an hour cleaning it and writing down the changes. Then answer three questions: which category has the highest value, how did one category change over time, and what is the rate per thousand people for your area? Write a short paragraph describing what you found and what you could not conclude.
Common mistakes to avoid
Beginners often trust a total without checking it, mix up percentages and percentage points, or compare counts from areas of very different sizes. Another frequent error is sorting one column without the others, which scrambles the rows. To avoid it, always select the whole table before sorting, and keep a backup of your original file. A further trap is treating a pattern as proof of a cause. A spreadsheet can show that two things move together, but it cannot show why. When you suspect a cause, report it as a question and talk to experts before you state it as fact.
What this guide cannot tell you
We have not covered statistics in depth, nor the specific tools used in your newsroom. Software differs, and some tasks are easier in other programs. If your findings might be published, ask an editor or a data specialist to check your approach, particularly if it involves claims about causes.
The bottom line
Spreadsheet skills are a strong foundation. Learn to clean, sort, filter, group and calculate carefully, and always check your results. These skills help in almost every newsroom job, and they are the first step if you want to go further into data journalism.
General information for working journalists, not legal, tax or financial advice. Examples and numbers are illustrative. Spot an error? Write to [email protected].