hpr-knowledge-base/hpr_transcripts/hpr1665.txt

Episode: 1665
Title: HPR1665: 44 - LibreOffice Calc - Working With Pivot Tables
Source: https://hub.hackerpublicradio.org/ccdn.php?filename=/eps/hpr1665/hpr1665.mp3
Transcribed: 2025-10-18 06:38:12

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It's Friday 19th of December 2014.
This is an HBR episode 1665 entitled, 44, Libra Office Calk, working with Bivart tables,
and is part of the series, Libra Office.
It is hosted by AYUKA, and is about 11 minutes long.
Feedback can be sent to Muilnik at Muilnik.com, or by leaving a comment on this episode.
The summary is, when you have a Bivart table, what are some of the things you can do with
it to analyze your nature.
This episode of HBR is brought to you by AnanasThost.com.
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Hello, this is AYUKA, welcoming you to Hacker Public Radio, and another exciting episode
in our series on Libra Office Calk, and I want to build on what we did last time.
Now in our last episode, we talked about how to create a Bivart table.
Once you've created it, what are some of the things you can do with it, and that's really
what I want to talk about this time.
So, let's assume that you've created one.
If not, you could certainly download the spreadsheet that I have put on the website.
There's a link in the show notes for you to do that.
Then you can see the one that I created, just downloaded off of my website.
So in our sample data set that we created last time, we had three regions, 11 sales representatives
and five products.
The resulting pivot table displayed the data for all of them.
But you have filter options to reduce the display to a narrower set.
In our best pivot table, we had item as the column field and representative as the row field.
We said this was best because it allowed us to easily get sub-totals by item or by representative.
And of course, the data field was total, which here meant the total amount for each order.
You can always filter on page field, column field, and row field by clicking on the drop down next to each label.
They are showing all when you start.
But if you only wanted to see sales for the Northeast region, you could go to the drop down next to region.
And you'd see a window pop up that would have Northeast, South, and West with checkmarks in all three.
And also in the bottom, there's a little checkbox that says all, and that is also checked.
So the region Northeast, because it's the very first one, what by default would be highlighted,
that makes it making it the current item, you could manually uncheck everything else and just show Northeast.
But there is a button at the bottom, actually two useful buttons.
The first says show only the current item.
And if you click this, you would uncheck every other region for you.
The other button is hide only the current item and does precisely the opposite.
If you clicked this, it would remove Northeast from your table and leave the other regions.
And for the variables item and rep, you have a similar window for filtering.
Now this is the kind of simple filtering we have seen previously, but suppose you want to do more.
There is a cell at the top, A1, which has the word filter.
If you click on it, you get a window that looks very similar to the standard filter window we saw previously,
when we looked at filtering data in count.
Well, you shouldn't be at all surprised that it looks similar to people who put Libra Office together,
really hate reinventing the wheel.
So if you've already solved a problem once, just keep using that solution.
That is the open source way.
So with that window open, you can create a filter that uses multiple criteria to simultaneously filter the data.
And you can use conditions, such as only showing orders where the total was greater than $100.
Now we covered this kind of filtering in more detail in our episode on data manipulation to standard and advanced filters.
So you can go back and check that one if you need a little more help in using this particular filter.
Now the same drop down that we used for filtering can also be used for sorting if you are working with a row or a column field.
On the top of the window, you have the usual sort ascending and sort descending options.
There is also a custom sort that uses the sort lists we discussed in our episode fills and introduction,
which you can consult for more information.
In short, this lets you take things like the names of days of the week or months and sort them in the logical order by time.
And you can create custom sort lists as needed.
Drilling.
By design, the data in a pivot table gets summarized by the row and column fields.
But sometimes you may want to see the details that make up the summarized total.
This is known as drilling.
For example, if I look at the representative named Gill, I can see that this person had sales of $1,132.74 for binders.
But what went into that?
If I double click on the cell that displays $1,132.74 on new sheet opens that tells me it came from an order on January 15th of 2011 for $413.54.
And another order on May 31st, 2011 for $719.20.
You could also get this result by going to data, group, and outline show details.
But I think double clicking on the cell is somewhat easier.
I suppose you want to edit the table to some degree.
Not the end of our last tutorial, we saw that you can reopen the data pilot window to change your layout.
That is the most reliable way, and in some cases the only way to make major changes.
But you can do something just by dragging fields around in the table itself.
For example, when we did the creating a pivot table, our very first pass, we put rep and item both as row fields.
But saw that this was not really the best way to do the analysis.
Now, we could solve that by reopening the data pilot, but there's a quicker way.
At the top of the column for item is the column for item is the column label, which is the cell that says item, of course.
You can click and drag this column label to a new position.
If you click on it, you will see your cursor become a horizontal rectangle in gray.
This is an indication that it is a row field because rows are horizontal.
But drag this one place to the right and it becomes a vertical rectangle, which means that if you release it, it will become a column field.
If you keep dragging it, it becomes a black X indicating that you cannot move it here.
If you release it in the column field position, the pivot table becomes just like our second example from the last tutorial.
You can also drag a row or column off of the pivot table altogether, which removes that field completely.
But that is a permanent change. You can re-add the field only by going back to the data pilot and adding the field there.
Now finally, what about refreshing the data?
The pivot table contains the data that was in the original spreadsheet at the time it was created.
But sometimes you make changes or add data to a spreadsheet.
Depending on which it is, you have two choices.
If you added or removed records from the original data set, the only thing you can do is recreate the pivot table.
Now, I hope you saw from the last tutorial that creating a pivot table is not that hard, really.
But if you merely changed a value in one of your records, you can right-click within the results area of the pivot table and it will recalculate.
For example, take a quantity from one of the existing orders, change it, and then refresh. You should see the change.
Now, this is an introduction to a very useful technique. It's really just an introduction.
But we've seen a number of useful principles, such as once again, understanding the distinction between qualitative and quantitative variables, knowing how to use each one of them appropriately.
And so, with that in mind, I'd encourage you to spend a little bit of time working with pivot tables, get to know them.
I think you'll find they're a very handy tool. But it's time to move on.
So, next, we're coming up with an old friend of ours, styles and templates. Yes, they really have a role to play even in spreadsheets.
And so, with that, this is Ahuka for Hacker Public Radio, signing off and reminding you as always to support free software. Bye-bye.
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