All articles with 'sumifs' Tag
Excel has hundreds of formulas. But as a new learner or user, you may want to just focus on top 10 formulas to get the most out of it. Assuming you already know the basics (check out Beginner Excel page if you are complete newbie), here is a list of top 10 Excel formulas for you.Continue »
Excel SUMIFS function is used to calculate the sum of values that meet any criteria. For example, you can calculate the total sales in east zone for product Pod Gun using SUMIFS formula.
In this article, you will learn:
- What is SUMIFS function and how to use it?
- Syntax for SUMIFS
- Using SUMIFS() with tables and structural references
- SUMIFS examples – simple, wild card
- Using SUMIFS() with date & time values
- Free sample file for SUMIFS formula
- More formulas for data analysis
I believe in frugal living and paying yourself first. One of the simple ways to achieve this is by using a budget. You know how much money you get. Once you can track (or estimate) how much you are spending, it is easy to see how much you are paying your future self and what wiggle room you have. So in the spirit of making you awesome in life, not just Excel, let me share a simple but elegant household budget spreadsheet.
Here is a screenshot of the budget.
We recently went on a road trip around parts of New Zealand’s north island. We have been to Taupo, Rotorua, East Cape and Napier. It took us 2 weeks, we drove more than 2,000 km and spent almost NZ $3,000 on the trip. Of course, being a data nerd, I made a plan of the trip in Excel and that helped us budget for this.
After getting back to home, I thought it would be fun to polish the planner workbook and share it with you all so you too can plan a fabulous road trip. So here we go.Continue »
We know how to use SUMIFS function to answer questions like, “What is the sum of values for ‘A’?” But how would you answer questions like,
- What is the sum of values that are neither “A” nor “B”?
We can still use SUMIFS, but it will get awfully long. So let’s turn our attention to other functions in Excel.Continue »
This is part two of our three part series on how to analyze half a million customer complaints. Read part 1 here.
Analyzing Regional Trends
As introduced in part 1, our complaints dataset has geographical information too. We know the state & zip code for each complaint. Please note that zip codes are partial or missing for a 10% of the data.
In this article, let’s explore three ways to analyze regional trends.
- Regional trends by state, product & issue
- Complaints per million by state
- Complaints by zip code
Lets look at how to apportion sales according to multiple criteriaContinue »
Here is an interesting twist on the good old VLOOKUP. How to find the pricing applicable for given quantity of a product?
Something like above.
Looks interesting? Then read on…Continue »
Imagine you are the head of training department at ACME Inc. You arrange training programs round the year to empower your team. It is hard work, coordinating between employees, trainers, department heads, venues and coffee machines. What if there is something to help you keep track of all this? I am not talking about getting you a shiny new iPad, you silly. I am talking about a tracker & calendar built in Excel that ties everything together (well, almost everything, you still have to fill the coffee machine.)
We are going to build a training program tracker & calendar using Excel.Continue »
In the 30th session of Chandoo.org podcast, let’s learn how to uncover fraud in data.
What is in this session?
In the wake of hedge fund scams, accounting frauds and globalization, We, analysts are constantly second guessing every source of data. So how do you answer a simple question like, “am I being lied to?” while looking at a set of numbers your supplier has sent you.
That is our topic for this podcast session.
In this podcast, you will learn
- Quick announcements about 50 ways & 200k BRM
- Introduction to fraud detection
- 5 techniques for detecting fraud
- Benford’s law
- Auto correlation
- Discontinuity at zero
- Analysis of distribution
- Learning systems & decision trees
- Implementing these techniques in Excel
- A word of caution
Who is the most consistent of all?
Imagine you are a category manager at a large e-commerce company. Your site offers various products, but you don’t really make these products. You list products made by other vendors on your site. Every day, these vendors would send you invoices for the amount of product they have sold. Above is a snapshot of such invoices.
Looking at this list, you have a few questions.
- Who is the best seller?
- Who is the most active seller?
- Who is the most consistent seller?
- Which seller has fewest invoices?
Let’s go ahead and answer these using Excel. Shall we?Continue »
Occasionally we deal with data that is so uncooperative that we might as well give up and go back to calculators & ledger books.
Recently I found myself in such a situation and learned something new.
Introducing … data that won’t play nice
Drum roll please. Here is a data-set that I got from somewhere.
The problem – build a lookup formula
And the problem. Oh, simple. Write a lookup formula to find how many customer walk-ins we have on any given day.
But how?Continue »
This is a guest post by Sohail Anwar.
Let’s not bore you with an intro. You are about to learn a VLOOKUP trick that Lucifer himself would not want you to know. It’s so absurdly powerful that it was developed in a lab and had to be tested on Rocky’s arch nemesis Ivan Drago.
Presenting the Multiple criteria VLOOKUP!
…boring…pass, we’ve seen it.
Oh, have you? Not like this you haven’t. This will change the way you work with Excel.
Let me start with an easy example. Here’s some data and we would love to know what Bb and Dd is.Continue »
Recently, I saw this chart on Economist website.
It is trying to depict how various cities rank on livability index and how they compare to previous ranking (2014 vs 2009).
As you can see, this chart is not the best way to visualize “Best places to live”.
Few reasons why,
- The segregated views (blue, gray & red) make it hard to look for a specific city or region
- The zig-zag lines look good, but incredibly hard to understand % changes (or absolute changes)
- Labels are all over the place, thus making data interpretation hard.
- Some points have no labels (or ambiguous labels) leading to further confusion.
After examining the chart long & hard, I got thinking.
Its no fun criticizing someones work. Creating a better chart from this data, now thats awesome.Continue »
Ok people. Let me tell you that this post is almost not about Excel. It is about how one Excel blogger’s (yours truly) dream of long distance cycling came true. So sit back, grab your favorite drink and read between sips.
So what is this all about?
Last Sunday (27th July) & Monday (28th), I finished my first ever 200KM bicycle ride. I rode for a little more than 12 hours, burned 5,179 calories & rode 206 kilometers.
It is definitely one of the most memorable, tiresome & uplifting experiences in my life. So naturally, I want to share the story with you.Continue »