Finding Stories in Spreadsheets

1.Introduction

2.Stories about change, stories in context: basic calculations

1. Cell references
2. Calculating a change
3. Calculating a proportion
4. Ratios: calculating a proportion as ‘1 in 10’
5. Combining both: calculating what proportion a change is
6. Recap
7. Find the story: are there more drunk and disorderly arrests?

3.Saving time to hit a deadline: repeating and fixing a calculation across cells

1. Shortcut: repeating a calculation down hundreds of cells with one double-click
2. What if I want to fix the cell reference so it doesn’t change when pasted?
3. Recap
4. The last chapter’s story: are there more drunk and disorderly arrests?
5. Find the story: drunk and disorderly arrests

4.How much did it cost? How many people were affected? The first function: adding a series of cells with SUM

1. Functions in different languages
2. If functions are recipes, arguments are the ingredients
3. When there’s more than one ingredient: commas and semicolons
4. Recap
5. Find the story: drunk and disorderly arrest totals

5.Who’s top, who’s bottom? MAX, MIN, and sorting

1. MAX and MIN
2. Recap
3. The last chapter’s story: drunk and disorderly arrest totals

6.Detour: getting to know the spreadsheet - useful shortcuts and tips to avoid mistakes

1. Keyboard shortcuts to explore your data quickly
2. Changing your data: remove empty rows before the headings
3. Recap

7.Hitting the deadline: understanding and formatting the data - number or text

1. Numbers
2. Text
3. Recap

8.Best sellers and averages: MEDIAN, AVERAGE and MODE

1. Calculating an average: AVERAGE, MEDIAN or MODE?
2. Man made or natural?
3. Recap
4. Find the story: political donations

9.How many payments? How many people? Counting, not adding up: COUNT

1. The story is what’s missing: COUNTBLANK
2. Recap
3. The last chapter’s story: political donations
4. Find the story: missing donations data?

10.Only count if… setting criteria for a formula: COUNTIF

1. Counting something specific
2. Looking for cells containing words within sentences: the wildcards
3. Trial and error: the single-cell test
4. Counting against combined criteria: COUNTIFS
5. Recap
6. The last chapter’s story: missing donations data?
7. Find the story: how many donations fit the bill?

11.If… continued: setting criteria for a sum: SUMIF

1. Recap
2. The last story: how many donations fit the bill?
3. Find the story: what proportion of donations came from small donors?

12.Putting the story into context, or looking from a fresh angle: merging data from different tables using VLOOKUP

1. Dry run: two small tables on the same sheet
2. Using VLOOKUP on data in different sheets
3. Those pesky #N/A results
4. Recap
5. The last chapter’s story: what proportion of donations came from small donors?
6. Find the story: baby names - which are the biggest risers and fallers?

13.My data is dirty! Basic cleaning using TRIM, CLEAN and SUBSTITUTE

1. Those pesky spaces
2. Getting rid of ‘non printing’ characters: CLEAN
3. And or ampersand? Substituting particular words or characters
4. Case study: generating URLs to speed up a name search
5. Recap
6. The last chapter’s story: baby name trends

14.Detour: generating consecutive numbers or dates

1. Other number sequences
2. Text sequences: days and months
3. Getting more control over your ranges - the Fill Series option

15.Using more than one function at a time: nested functions

1. Nesting functions
2. Recap
3. Find the story: simplifying names to make them consistent with another dataset

16.Generating categories and other extra data: IF

1. Testing more than one thing - nested IF
2. Hello operators: comparing beyond ‘greater than’ or ‘less than’
3. Testing text: combining IF with other functions
4. Recap
5. The last chapter’s story: simplifying names to make them consistent with another dataset
6. Find the story: converting restaurant ratings into categories

17.Detour: testing whether something is TRUE or FALSE

1. Logical tests with text
2. Adding up TRUE and FALSE
3. Functions which return logical results
4. Recap

18.Finding errors or missing data - and testing data types: ISERR, ISBLANK, ISTEXT and others

1. Functions for testing data types
2. Functions that look for errors, or types of errors
3. Using IS functions in practice: an error-checking column
4. Recap
5. The last chapter’s story: converting restaurant ratings into categories
6. Find the story: classifying non-rated hygiene reports

19.Testing two things at once: AND, OR and NOT

1. Finding outliers at the top or bottom: OR
2. Finding one of a series of possible text values: OR
3. Finding numbers in the middle, or in a particular range: AND
4. Applying criteria across multiple columns
5. Combining with IF to avoid multiple IF tests
6. Making multiple negative tests
7. Recap
8. The last chapter’s story: classifying non-rated hygiene reports
9. Find the story: which outlets have consistently bad scores?

20.What day did that date fall on? Which year was the worst? Extracting days, months and years from full dates

1. Extracting dates, months and years: DAY, MONTH and YEAR
2. Extracting days and months as words or years as ‘66, ‘94 etc: TEXT
3. Using the Format Cells ‘Custom’ option to do the same thing to existing dates
4. Hours and minutes: HOUR, MINUTE, SECOND and TEXT again
5. When things don’t go as you expect them to: dealing with errors in date functions
6. Recap
7. Finding the story: which outlets have consistently bad scores?
8. Find the story: what years and months are worst for hygiene inspections?

21.How old is someone? Ages and using TODAY’s date

1. Breaking down the problem
2. Calculating the years
3. Checking whether a birthday comes before or after a date
4. Making an adjustment based on the results
5. Using TODAY to calculate an age against today’s date
6. Making it easy to understand: breaking the formula back up
7. Other ways of calculating ages: the unsupported DATEDIF function
8. Watching out for leap years in other calculations
9. Recap
10. Finding the story: what years and months are worst for hygiene inspections?
11. Find the story: how old are Guantanamo prisoners?

22.Grabbing or checking the first, middle or last part of a piece of information: RIGHT, LEFT and MID

1. Grabbing characters from the beginning: LEFT
2. Grabbing characters from the end: RIGHT
3. Grabbing characters from the middle: MID
4. What if the starting position or number of characters depends? Introducing LEN
5. What if the starting position or number of characters depends? Part two: SEARCH and FIND
6. Extracting characters by getting rid of the others: REPLACE
7. Recap
8. Finding the story: how old are Guantanamo prisoners?
9. Find the story: what postcode areas are worst for hygiene inspections?

23.Case study: When you get data in sentences: using SEARCH and error handling to extract numbers from phrases

1. Break down the steps
2. Identify where the years/months are detailed: using SEARCH
3. Extract the number of years/months (and correct for problems)
4. Handling an unnecessary space
5. Converting to a common measure
6. Manual cleaning: identifying unusual words
7. Adding a ‘checking’ formulae
8. Sometimes hard work ends up left out of the story
9. Key points

24.Putting names, addresses and other data back together: CONCATENATE, & and adding special characters with CHAR

1. Adding unusual characters: CHAR
2. The alternative to CONCATENATE: &
3. Recap
4. Tell the story: finding special characters
5. Finding the story: what postcode areas are worst for hygiene inspections?

25.More data cleaning: formatting text or numbers consistently with UPPER, LOWER, PROPER and FIXED

1. Encoding and decoding text: making just the first character capitalised
2. Rounding and formatting numbers: FIXED and ROUND
3. Showing figures as millions or billions without all the zeroes
4. Recap

26.Changing rows into columns, and vice versa: TRANSPOSE

1. The TRANSPOSE function in Excel - for when you need data to always be transposed
2. The TRANSPOSE function in Google Sheets - no need for keyboard shortcuts
3. The Paste Special option: the one-off transpose
4. Recap
5. Find the story: when’s the worst time to turn up at hospital?

27.Repeating calculations across multiple cells or to create the ingredients of a single function: array formulae

1. Arrays in practice: back to the drunk and disorderly data
2. Changing or extending an array formula
3. Multiple calculations with one result: using an array formula in a single cell
4. Generating your own arrays
5. Array constants used in a formula
6. Use TRANSPOSE to convert horizontal arrays into vertical arrays - and vice versa
7. Recap
8. The last chapter’s story: when’s the worst time to turn up at hospital?
9. Detour: An introduction to Google Sheets - an always-connected spreadsheet tool
10. Make sure the settings are for your country

28.Grabbing data from elsewhere - IMPORT and GOOGLE functions in Google Sheets

1. Pulling data from another sheet: IMPORTRANGE
2. Grabbing data from online CSVs and TXT files: IMPORTDATA
3. Grabbing data from webpage tables and lists: IMPORTHTML
4. Grabbing data from RSS feeds: IMPORTFEED
5. Grabbing data from an XML document - or a HTML webpage: IMPORTXML
6. Using IMPORTXML to grab data from HTML webpages
7. Grabbing links and other values that are not in visible text
8. Recap
9. Exercises

29.Dealing with data in another language: GOOGLETRANSLATE and DETECTLANGUAGE

1. Detecting the language: DETECTLANGUAGE
2. Using DETECTLANGUAGE as part of GOOGLETRANSLATE
3. False friends and cognates
4. Tip: translating a term to generate search URLs in other languages
5. Recap
6. IMPORT Exercises - tips

30.Converting currency or using stock prices: GOOGLEFINANCE

1. Converting currency with GOOGLEFINANCE
2. Grabbing stock values with GOOGLEFINANCE
3. Recap

31.Publishing live data in a live chart

1. Recap
2. Exercise: grabbing and visualising live data with IMPORTHTML and live charts

32.Comparing change visually by generating sparkline charts for every row: SPARKLINE

1. Writing a SPARKLINE formula
2. Customising how the sparkline appears: bar charts
3. Keeping it relative: specifying minimum and maximum scale
4. Recap
5. Last chapter exercise: grabbing and visualising live data with IMPORTHTML and live charts

33.Asking questions (or allowing users to), SQL-style: QUERY

1. Forming the question: Select, Where and Order by
2. More complex clauses: group by and pivot
3. Writing queries with multiple or alternative criteria
4. Generating ‘hackable’ URLs which allow users to see the data their own way
5. Using a form to allow users to generate their own results pages
6. Examples of QUERY being used in code
7. Recap

34.Extracting text that matches a pattern: regular expressions in Google Sheets

1. What are regular expressions
2. Scenarios when you might use a regular expression
3. Google’s REGEX functions
4. Regular expressions as a language: regex
5. Putting this into practice with election tweets
6. Using REGEXEXTRACT with more advanced regex
7. How regex was used in the art story
8. Recap
9. Exercise: unduly lenient sentences
10. Sometimes hard work ends up left out of the story

35.Adding some randomness: spreading out locations randomly using RAND

1. RAND: Give me a number between 1 and 0
2. RANDBETWEEN: Give me a number between whatever I say!
3. Recap
4. Exercise: generate random placemarks on a map - within reason

36.Is this value ranked high or low? What value is 3rd? RANK, LARGE and SMALL

1. Using the RANK function
2. Finding values at a particular rank: LARGE and SMALL
3. Exercise: where does a region rank for youth offending?
4. Recap

37.What percentile is this at or above? PERCENTRANK and PERCENTILE

1. Percentile functions
2. What percent of values are smaller? PERCENTRANK
3. What value is at the nth percentile? PERCENTILE
4. Exercise: using both sets of functions with marathon race times
5. Recap

38.Classifying data into top, middle and bottom quarters: QUARTILE

1. Using the QUARTILE function
2. Applying quartile values to classify data into four quarters
3. Using PERCENTILE to classify data using quintiles
4. Recap

39.Cross referencing and advanced cell references: naming cells and using INDIRECT, INDEX and MATCH

1. Naming cells
2. INDIRECT
3. Cross-referencing cells based on values in other cells
4. INDEX
5. Working out which index to grab: MATCH
6. Exercise: Finding where schoolchildren go outside their area
7. Recap

40.Getting statistical: correlation with CORREL and other ways of testing data

1. How strong is the relationship between two columns of numbers?
2. Using the CORREL function
3. Once you have a result
4. Recap
5. Try it out

41.The final chapter: next steps

1. What else can Excel do? Add-ins, templates and VBA
2. Tell me your problems