All articles with 'array formulas' Tag

Writing advanced formulas is a lot like LEGO. Use what you already have and combine them in creative ways. Let me demo with 5 examples.

Howdy folks. Almost the end of August here. Let’s wrap it up with a nice little challenge, inspired from my recent consulting gig. Say you are looking at few job titles that look similar and want to match them to correct title.

Risk comes from not knowing what you are doing. Warren Buffet If you ever ask a project manager what they are up to, they will tell you “I have no idea“. So risks are quite common in project management. That is why I made this awesome free Excel risk map template to keep track and […]

We all know that VLOOKUP can find first match and return the results. But what if you want all the matches? Use this simple trick instead.

We all know VLOOKUP (or INDEX+MATCH) as an indispensable tool in our Excel toolbox. But what if you want the lookups to be a little gentler, nicer and relaxed?

Let’s say you want to lookup the amount $330.50 against a list of payments. There is no exact match, but if we look 50 cents in either direction, then we can find a match. Here is a demo of what I mean.

Unfortunately, you can’t convince VLOOKUP to act nice.

Hey VLOOKUP, I know you are awesome and all, but can you cut me some slack here? 

VLOOKUP is tough, reliable and has a cold heart. Or is it?

In this post, let’s learn how to do lenient lookups.

Let’s say you have data like this in a spreadsheet. Don’t roll your eyes, I am 102% sure, right at this moment, someone is (ab)using Excel to create similar messy data.

How do you reshape it to one column?

You could use formulas, VBA or Power Query. Let’s examine all these methods to see what is best. All these methods assume your data is in a range aptly named myrange.

Game for some charting awesomeness?

Off late, I have been doing a lot of data analysis and visualization on performance ratings, salary hike, gender pay equality etc. Today let me share you an awesome way to visualize massive amounts of data.

Scenario: Your organization of 3,686 people recently went thru annual performance ratings & review process. At the end of it, everyone was offered some salary increase (from $0 to $24,000 per year). You have 7 business groups. How do you tell the story of all these salary hikes in one chart?

How about the one above?

Ready to know how to create this in Excel? Read on.

Let’s say you have some employee data in employee name, manager name format. But the data is all in one column, with odd rows containing employee names & even rows containing manager names. Something like above.

And you want to find out who is the boss for a given employee. Say, “Andrea Nichols”.

Your regular MATCH() formula for Andrea over the data range returns wrong answer as it will find first occurrence of Andrea (which in this case happens to be on even row, hence a manager record).

So how would you write the lookup formula?

First a quick personal update: There has been a magnitude 7.8 earth quake in NZ on 14th November 2016 early morning. It is centered in Kaikoura, which is about 250 km away from Wellington. We did feel several shakes and after shocks. It has been an interesting and often scary experience. But my family is safe. I feel very sad for the all the damage and the loss for families in NZ. If you suffered from this quake, My prayers and thoughts are with you.

Yesterday, a friend asked me an interesting question. He has school distance data, like above. He wants to know which is the closest school for each school.

There are a few ways to answer this question. Let’s examine two approaches – formulas & pivot tables and see the merits of both.

Imagine you work at MI5 as a HR officer. You want to find all agents who have license to kill (licence 7). Your data looks like above.

How would you go about it? 

If you filter the list or use FIND() or SEARCH() formulas, you will end up with agents who also have licenses 77, 17 or not7. So how would you solve this problem?

Of course, you do what any smart person does. You summon Excel and ask it nicely by using some wicked pattern matching logic.

Over the weekend, I got an email from Mr. E, one of my students. Mr. E works at a police department in California and as part of his work, he was looking at calls received by police. Whenever police get a call for help, multiple teams can respond to the call and go to the location. All of these dispatches are recorded. So a single call can have several such dispatches. And Mr. E wanted to findout which team responded the first. The problem?

Finding the first responded team is tricky.

Today let’s take up this problem as a case study and understand various methods to solve it.  We are going to learn about writing better lookups, pivot tables, power pivot and optimization. Put on your helmets, cause this is going to be mind blowingly awesome.

Okay, this is an extension of the Neither “A” Nor “B” sum problem we discussed few days back.

Imagine you have a table named mydata with a few columns and a stop list named stop.list as shown above.

How would you calculate,

• Sum of Hours for all activities excluding those in stop list?
• Sum of all Regular hours for activities not in stop list?

So go ahead and post your answers in the comments.

Today is Friday the 13th. If you are a raging friggatriskaidekaphobiac, I suggest you to stop reading this post. For the rest of you, I have something fun.

Given a year in cell C3, let’s find out all the months with Friday the 13th. Something like above.

Okay, time for another challenge.

Imagine you have some data like this. Each cell contains 3 numbers separated by line break  – CHAR(10) and you need to extract the number that is 10 digits long.

Go ahead and solve this riddle.

This is the final part of our series on how to analyze half a million customer complaints. Click below links to read part 1 & 2.

1. Complaint reason analysis – Part 1
2. Regional trends & analysis – Part 2

Customer satisfaction scorecard

In the previous parts of this case study, we understood what kind of complaints were made and where they came from (states). For the customer satisfaction scorecard, let’s focus on individual companies.