Convert unevenly spaced list to table [Data from Hell]
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.
Extract currency amounts from text – Power Query Tutorial
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.
Get rid of that ugly formatting with two simple tricks
We are on a tiki tour around NZ. So far we have been to Taupo & Rotorua. And we are doing what you do when you are on a holiday – being lazy, going on walks, swimming in lakes, eating copious amounts of food and getting lost. Of course, all this means, I have very little time to access to internet & my blog. So the updates will be slow for next two weeks. Here is a quick tip (well, two of them) to keep you busy and awesome.
How to remove ugly formatting from your workbooks?
Do you have a colleague or boss (shudder) that loves to apply their special touches to every workbook their mouse lands on? Do you constantly wince and whine when you have to work on that spreadsheet.
Here are two handy ways to restore your data to its original glory.
Clear formats:
Simple, select the data you want formatting gone from, go to Home > Clear > Formats.
And Excel will weave an expelliformat spell at your data and make it clean.
Here is a quick demo.
Untrimmable Spaces – Excel Formula
Let’s talk about the untrimmable spaces.
We all know that TRIM() removes extra spaces from the beginning, ending and middle of a text.
So for example, if A1 has ” something and one more ”
TRIM(A1)
will give “something and one more”
We can use CLEAN() function to remove non-printable characters (like the ASCII codes 0 to 31). Of course, SPACE is technically a printable character, so CLEAN() won’t remove spaces.
The untrimmable spaces…?
The other day Sreekanth emailed me a sample of data and asked, “how do I remove the spaces in this list and convert them to numbers?”
Naturally I tried to TRIM().
But the data won’t budge. See above.
Hmm, let’s investigate why.
Unpivot data quickly with Power Query [tutorial]
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.
CP040: Intro. to Power Query – What is it and how to get started – with Miguel Escobar
Podcast: Play in new window | Download
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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
Looking up when data won’t play nice – few more alternatives
Recently, we discussed about the case of unwieldy data and how we lookup what we want using formulas like SUMIFS. Today, let us learn few more ways to solve the same problem.
Suitable structure spawns simple solutions
Poorly structured is the 2nd biggest problem of analysts. The first one is not enough coffee. That is why there is a dictum in the data analytics world.
Structure is everything
So, we can easily solve our lookup problem, if our data were to magically re-arranged in 2 column fashion – Data & Value.