Imagine you are looking customer data like below and want to sort them by performance. If you sort the data by any one column, you will not get full picture of performance. To understand which customers rank low on performance, you need to defined a weighed sort, the kind of sort where you assign weights to each attribute (customer age, recent purchases and rate of returns) and come up with single score to sort them all.
Sounds interesting? Watch below video to understand how to do weighted sorting in Excel.
Weighted sorting in Excel – video
You may watch this video on our YouTube channel too.
Download weighted sorting example workbook
Click here to download the weighted sort example workbook. Play with the weight formula to learn more.
More on weights & sorting data:
If you are weighed down by multi-column data sets, here are some awesome techniques to reduce your load:
- Weighted average in Excel – how to calculate it?
- Adding interactive sort features to your dashboards – tutorial
- Sorting text values using formulas in Excel
- Index charts – when data ranges all over the place
How do you handle similar sorting situations?
I use weighted sort concepts when working with multi-column data-sets. Most of the time I use simple weight calculation logic.
What about you? How do you sort multi-column data sets? What techniques do you use to calculate weights? Please share your thoughts and ideas in the comments section.
8 Responses to “Pivot Tables from large data-sets – 5 examples”
Do you have links to any sites that can provide free, large, test data sets. Both large in diversity and large in total number of rows.
Good question Ron. I suggest checking out kaggle.com, data.world or create your own with randbetween(). You can also get a complex business data-set from Microsoft Power BI website. It is contoso retail data.
Hi Chandoo,
I work with large data sets all the time (80-200MB files with 100Ks of rows and 20-40 columns) and I've taken a few steps to reduce the size (20-60MB) so they can better shared and work more quickly. These steps include: creating custom calculations in the pivot instead of having additional data columns, deleting the data tab and saving as an xlsb. I've even tried indexmatch instead of vlookup--although I'm not sure that saved much. Are there any other tricks to further reduce the file size? thanks, Steve
Hi Steve,
Good tips on how to reduce the file size and / or process time. Another thing I would definitely try is to use Data Model to load the data rather than keep it in the file. You would be,
1. connect to source data file thru Power Query
2. filter away any columns / rows that are not needed
3. load the data to model
4. make pivots from it
This would reduce the file size while providing all the answers you need.
Give it a try. See this video for some help - https://www.youtube.com/watch?v=5u7bpysO3FQ
Normally when Excel processes data it utilizes all four cores on a processor. Is it true that Excel reduces to only using two cores When calculating tables? Same issue if there were two cores present, it would reduce to one in a table?
I ask because, I have personally noticed when i use tables the data is much slower than if I would have filtered it. I like tables for obvious reasons when working with datasets. Is this true.
John:
I don't know if it is true that Excel Table processing only uses 2 threads/cores, but it is entirely possible. The program has to be enabled to handle multiple parallel threads. Excel Lists/Tables were added long ago, at a time when 2 processes was a reasonable upper limit. And, it could be that there simply is no way to program table processing to use more than 2 threads at a time...
When I've got a large data set, I will set my Excel priority to High thru Task Manager to allow it to use more available processing. Never use RealTime priority or you're completely locked up until Excel finishes.
That is a good tip Jen...