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hpr_transcripts/hpr1655.txt

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+Episode: 1655
+Title: HPR1655: 43 - LibreOffice Calc - Creating Pivot Tables
+Source: https://hub.hackerpublicradio.org/ccdn.php?filename=/eps/hpr1655/hpr1655.mp3
+Transcribed: 2025-10-18 06:26:56
+
+---
+
+It's Friday 5th of December 2014.
+This is an HBR episode 1655 entitled 43 Libra Office Calk, creating pivot tables and
+in part of the series, Libra Office.
+It is hosted by AYUKA and is about 16 minutes long.
+Feedback can be sent to Wilnicat and Wilnic.com or by leaving a comment on this episode.
+The summary is how to create a pivot table.
+This episode of HBR is brought to you by an honesthost.com.
+With 15% discount on all shared hosting with the offer code HBR15, that's HBR15.
+Better web hosting that's honest and fair at An Honesthost.com.
+Hello, this is AYUKA, welcoming you to Hacker Public Radio and another exciting episode
+in our ongoing series on Libra Office.
+We are continuing on our investigation of Calk and getting to something that I think
+will be of some interest to a lot of people.
+It's something that spreadsheets have made very easy to do but can be a little bit frightening
+to people and that is pivot tables.
+On this one I want to talk about how you create a pivot table.
+Pivot tables are extremely useful.
+I have seen people say that that was one of the big reasons that Excel replaced Lotus
+1-2-3 as the spreadsheet of choice.
+I think there were probably several things going on there, but still it does illustrate
+how important they are.
+They're also very confusing the most spreadsheet users.
+I think part of the reason for that is that they are very flexible and powerful, which
+means that it is easy to get confused.
+The term pivot is actually a clue to how you can use them.
+Imagine a table of summary data where you can rotate the table so that rows become columns
+depending on your needs.
+That's what the pivot part refers to.
+The other thing you want to pay attention to here is that the power of pivot tables comes
+from using raw data, not summarized data.
+As an example, the biostatistics data we used in the previous tutorials was raw data.
+You had an individual row for each observation and multiple measurements were made for each
+individual covering a variety of variables.
+But for this analysis, I'm going to use another data set which I found at the University
+of South Florida.
+It contains fictional data of sales at a company and this is the canonical example of using
+pivot tables.
+Note that each row of the data set is for an individual order.
+I have a link to download this that is in the show notes, so please feel free to download
+the data set and take a look and follow along with what we're doing.
+Now the rules for using pivot tables are not too bad, but pay attention.
+First, you cannot have any empty rows or columns.
+These people insert blanks for formatting purposes.
+In fact, I've often done that myself on spreadsheets, but if you wish to use pivot tables, they
+must be removed.
+The reason for this is that count searches in all four directions from the cell you selected
+to locate your data.
+And if it encounters a completely blank row or column, it treats that as a signal of the
+end of the data.
+Secondly, always select only one cell when starting the pivot table.
+The program will automatically infer the whole range using the algorithm I just mentioned.
+It's going to look in all four directions.
+If you select more than one cell, it will assume you're putting in a list and the sorting
+will be mixed up.
+Finally, the data must have simple, linear structure, in other words, the normal form.
+For instance, you cannot have data divided into different columns that is essentially the
+same data.
+In our data set, we would not want to have sales for the Northeast region in one column,
+sales for the South in another column, et cetera.
+You put all the sales in one column and then have a variable that says what region in
+a different column.
+Also while it is possible to use external data sources for this kind of analysis, I will
+stick to doing this with data that is already in a spreadsheet.
+Starting to access external data sources is a more advanced topic we may get to that
+at some future date.
+Now creating the pivot table, you've got a spreadsheet, you've got a bunch of data.
+Click on a cell anywhere in that data, just one cell, and then go to the data menu, then
+select pivot table, then select create.
+And this is going to pop up a window that is going to allow you to start sticking your
+variables in various rectangular spaces here.
+Now note that along the right side of this window is a list of all of your fields, generally
+based on columns.
+But for some reason you don't get all of your fields, highlight all of the columns you
+want before you create the pivot table, and that should take care of it.
+Now this window is called the data pilot dialogue.
+Now to set your different fields in the pivot table, you just drag and drop each field to
+the appropriate area in this window.
+Page fields is the first category.
+This is a place to potentially limit the data to one value in one of your columns.
+For instance, if we look at the region field, we may want to look individually at each region,
+so putting this field in page fields will let us do that.
+Then data fields.
+This area must contain at least one variable.
+columns in this area are aggregated, and the obvious candidate for that in our sample
+data set is the total field that records total sales on each order.
+The idea is that you are going to add up the sales for some set of values to be defined
+in the row and column fields.
+Column fields, whatever you put here, will be a column in the resulting pivot table.
+As a general rule, if you have two possible fields to use, make one a column field and
+one a row field.
+And finally, row fields will be rows in the resulting pivot table.
+So here is an example.
+You can take a look, and I created a spreadsheet that has this, which you can download, and you
+can see what I'm referring to, and it uses that data set that I told you I got from
+University of South Florida.
+So I created with region as the page field, total as the data field, and rep and item as
+the row fields.
+And no column fields were used in this particular example, and you can see I get a particular kind
+of a pivot table.
+With little practice, you can see how to use these fields.
+The page field allows you to select one, several, or all categories of the selected field.
+Since looking at regions is a pretty reasonable thing to do, it makes sense to use this.
+Total is the only field that you would want to aggregate.
+By this, I mean that you are adding together all of the individual orders that fit the classification.
+As an example, looking at representative Andrews, we see a total of $298.65 in pencil sales.
+But looking at the raw data, we see that this came from three separate orders.
+I don't see any other field here where you want to do that kind of a calculation.
+That's why we put total into that data field.
+Note also that you could have gotten this answer laboriously by going through the orders,
+sorting them, and adding up the individual orders to get the totals.
+But the pivot table does this almost effortlessly.
+Now the remaining questions about row and or column fields.
+The fields that are suitable for this kind of thing are in one sense similar to the page field options.
+You will note that an old friend of ours has returned, and that is the distinction between qualitative and quantitative variables.
+Data fields will pretty much need to be quantitative variables, and we only have two of those here, total and units.
+Either one can be used in some types of analysis, but that depends on the rest of your fields as to which makes sense.
+Given the page field and row fields we already chose, units would make no sense because the numbers are not comparable.
+How do you add the number of pencils to the number of binders and get a meaningful total you can't?
+But that is partly because we started out to compare sales by region anyway.
+But page fields, row fields, and column fields will all be qualitative.
+We have three good candidates here, region, rep, and item, and we used all of them in our analysis.
+But they could be interchanged depending on the analysis we want to focus on, as to whether they should be rows or columns that is simply a matter of presentation.
+For example, I did a second view of the pivot table, except that now I've moved item into being a column field.
+This probably is a better presentation than the first one.
+It's definitely easier to read.
+And the second reason is to get sub-totals by both of your fields.
+You can see total sales for each rep.
+And since I left rep as a row field, the very last column gives the total for each representative.
+And then the total sales for each item.
+Now since item is column fields now, if I look at the very last row, it gives the total for each of those columns.
+I can see the total sales for binders, the total sales for desks, the total sales for pens, and so on.
+So that's a good thing to remember.
+The final option here, creating a pivot table with both ref and item as column fields produces a pivot table that is very wide and just about unreadable.
+Now, suppose you put fields in the wrong area and did not realize it until after you create the pivot table.
+Well, that's an easy fix.
+Note that in the top left cell, which on my sample spreadsheet is cell A1, it has the word filter.
+If you right-click on that cell, a menu of options opens, and the very first item in this menu is edit layout.
+If you click on this, the data pilot window will open again, and you change things by simply dragging fields to where you want them.
+You can drag a field from one layout area to another.
+You can add a field you didn't have before, or you can remove a field by just dragging it outside the layout area.
+So you have a lot of flexibility here.
+OK, so this is kind of hard.
+I realize a lot of this stuff is hard to visualize just listening to an audio program.
+And that's why I created these sample spreadsheet files that you can download.
+So if you take a look at the show notes, you can see that I have created one that has these pivot tables, the different variations that I talk about in this particular podcast.
+You can see as separate tabs in the spreadsheet, so you can compare them and take a look at them and see why.
+For instance, making both of those fields as row fields was not as good as making one row and one column.
+And I think when you look at that, you'll understand right away why that makes so much sense.
+So I encourage you to download and play with it.
+And remember that pivot tables really are a very important and powerful use of spreadsheets.
+And it's probably worth taking a look at it.
+So this is Ahuka for Hacker Public Radio, signing off and reminding you as always to support free software. Bye bye.
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