All articles in 'Power Query' Category

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.

Let’s take a whirlwind trip to coolest little capital – Wellington. It is a windy place, so hold on to your hats and spreadsheets.

Almost everyone who spends more than 2 days in Wellington would agree that it is a windy place. But how windy is Welly? In this two part series, we will use Power Query, Excel charts and coffee to answer that question.

But, first let’s start with a joke.

What happens when you throw a boomerang in Frank Kitts Park?

You will have to buy another one, coz you are not getting that one back.

Before we begin:

Today is the last day for enrolling in our Power BI Play Date. Don’t miss out on this amazing opportunity to learn, use and benefit from Power BI at your work. Check out my online class and sign up before the doors close at midnight. Click here.

Let’s get our Simpsons on then.

D’oh, How often Homer says his favorite things?

Here is the visualization to explore Homer’s (and other character’s) favorite sayings in 27 years worth of Simpsons episode. Click on the image to play.

Introducing Data from Hell:

Watch out, its data from hell. In this new video series, we are going to examine some nutty, frustrating and fun data reshaping challenges and solve them using Excel. We will use Power Query, Formulas, VBA or other features as needed to free this data from damnation.

For our first installment, let’s reshape unevenly spaced list of values to a table.

Yesterday we saw a beautiful example of panel charts with R. Today let me show you how to create the same (or even better) with Power BI & R. What you need: Power BI Desktop and R Raw data set – rem-data.csv Creating Panel Charts in Power BI with R Load CSV data in to […]

Let’s say you got some text values and want to extract the amounts from them. Something like above.

How to go about it?

We could use a variety of techniques to extract the values.

• Formulas – not easy given the unstructured nature of data. But almost possible. See this for an example.
• VBA – possible, read this forum discussion few ways to do it.
• Power Query – at first glance it might seem tricky, but PQ makes this all too easy. Read on.

When faced with tough problems I react in one of three ways

1. Come up with ingenious solutions
2. See if a simpler cheat solution is possible
3. Sit back and ignore

For most problems, I choose 3rd reaction. Occasionally, I rely on 2nd option and very rarely the first one.

When faced with a tricky time sheet summary problem (as outlined above), after initial lethargy I wanted to solve it.

Let’s say you are the people manager at ACME Inc. You are looking staff list for the months – January and February 2017. You see that we had 4,000 employees in Jan and 4,200 employees in Feb. So what is the churn?

• Is it just 200?
• Or is it the sum of people who left and who joined?
• What if you want to find out how many people moved to new designations / departments or groups?

You see, churn is tricky to figure out.

So why not invite the pros? ie Power Query. 

Or more appropriately titled, the one where Power Query solves the problem in less time than it takes you to say Get & Transform Data.

Recently, one of my students Mr. K, sent me a pivot table problem.

Today my boss asked me “how much we paid to staff since the inception of our business with their respective date of joining?” He wanted to know, level wise summary of the last 16 years (on Quarterly / Year wise basis).

The records appended from the database month wise. Have a look to the file and give your ideas.

Mr. K’s data looked like above.

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In the 52nd session of Chandoo.org podcast, let’s discuss monkeys, Ok, I am kidding. We are going to talk about M is for Data Monkey book.

What is in this session?

In this podcast,

• Updates: Why so much gap between episodes?
• Quick introduction to Power Query
• Why you should get this book?
• What is in this book?
• A very cool example of the techniques you will learn
• Conclusions

Here is an interesting problem to keep you busy.

Transpose the address data in column A into the format indicated in C:G using either VBA, formulas or Power Query. Once done, post your answers in comments section.

Power Query (Get & Transform data in Excel 2016) is a must have tool, if you wrangle with data every day. Here is a quick introduction, in case you are new.

Let’s learn how to use Power Query to unpivot data.

Essentially, we are trying to go from left to right in the above picture.

Doing something like this thru either formulas or VBA can be very complex. But Power Query can get you unpivoted data in just a few clicks. Sounds interesting? Read on.

Power Query offers many ways to get data to Excel. One of them is to Web Data import feature. Let’s understand how this works by importing world stock exchange closing data from Google Finance website.

[Related: Introduction to Power Query]

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In the 40th session of Chandoo.org podcast, Let’s talk about Power Query. I have the pleasure and fortune to catch up with Miguel Escobar (who along with Ken Puls runs PowerQuery.Training website) and talk about this very exciting piece of technology and how it can make our life simpler.

What is in this session?

In this podcast,

• Welcome
• Miguel’s introduction, background and current projects
• What is Power Query
• How to install it
• Sample use cases of Power Query
• What is Power BI
• Resources for learning Power Query – Books & Courses