This is a presentation which is used in Healthcare IT Professional (HITP) course. The goal is to show the student how data can be organized and manipulated (drill down, slice and dice..) using Excel. This part comes after introduction to data warehouse and OLAP. www.alamedaservices.com

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Healthcare IT Professional
HIT 101-3 Using Excel for Data Management (Pivot
Tables)
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Pivot Table Introduction
A Pivot Table is the name Excel gives to what is more
commonly known as a cross‐tabulation table. Such
tables can be one, two or three‐dimensional and
offer a range of summary statistics. They can be
modified interactively and can be based on data
from more than one worksheet.
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Why organize list data into a Pivot Table?
Three key • To summarize the data contained in a lengthy list
into a compact format
reasons for • To find relationships within the data that are
organizing data otherwise hard to see because of the amount of
detail
into a Pivot • To organize the data into a format that’s easy to
Table are: chart
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PRODUCT REGION SALES_REVENUE
Hard Drive East $ 20,000.00
Hard Drive West $ 10,000.00
Hard Drive South $ 12,000.00
Hard Drive North $ 40,000.00
Printer East $ 109,000.00
Printer West $ 12,100.00
Printer South $ 120,800.00
Printer North $ 120,800.00
Zip Drive East $ 14,000.00
Zip Drive West $ 22,600.00
Zip Drive South $ 27,800.00
Zip Drive North $ 13,900.00
56K Modem East $ 13,500.00
56K Modem West $ 24,800.00
56K Modem South $ 21,000.00
56K Modem North $ 32,400.00
The spreadsheet illustration above is a simple Excel list. Even looking at this simple, short list
it’s difficult to discern patterns in the data.
For example, it takes a bit of study to see that the number of Units Sold in the North region is
much greater than the number of Units Sold for any other regions. Or to find out that PRINTER
is the most popular item in all regions.
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Sum of SALES_REVENUE PRODUCT
REGION 56K Modem Hard Drive Printer Zip Drive Grand Total
East 13500 20000 109000 14000 156500
North 32400 40000 120800 13900 207100
South 21000 12000 120800 27800 181600
West 24800 10000 12100 22600 69500
Grand Total 91700 82000 362700 78300 614700
By contrast, the Pivot Table above simplifies and summarizes the data to make
relationships and patterns obvious. And, if you had much more data in the list at
left (perhaps with many additional entries for each region), you could still achieve
a condensed Pivot Table summary the same size as the one at right. The Pivot
Table also allows you to include or exclude whatever list data you like.
Sum of SALES_REVENUE PRODUCT
Two REGION 56K Modem Hard Drive Printer Zip Drive Grand Total
Regions North 32400 40000 120800 13900 207100
South 21000 12000 120800 27800 181600
Grand Total 53400 52000 241600 41700 388700
Sum of SALES_REVENUE PRODUCT
REGION 56K Modem Hard Drive Grand Total
East
North
13500
32400
20000
40000
33500
72400
Two
South 21000 12000 33000 Products
West 24800 10000 34800
Grand Total 91700 82000 173700
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You can easily chart the data organized into a Pivot Table, while to chart the
data in the list first need to restructure the data and obtain the sum for each
region. The Pivot Table simplifies the process because it obtains subtotals
automatically and puts them in a range you can immediately use for charting.
Drop Page Fields Here
Sum of SALES_REVENUE
140000
120000
100000
PRODUCT
80000 56K Modem
Hard Drive
60000 Printer
Zip Drive
40000
20000
0
East North South West
REGION
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What’s Required to Construct a Pivot Table?
To create a
• a data field, where the data field is
Pivot Table the variable you want to summarize
you need to • a row and/or column field where the
identify these row and/or column fields are the
variables that will “control” the data
two elements summary
in your data:
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To create the Pivot Table, invoke the Pivot Table Wizard with
the menu commands Data, Pivot Table and Pivot Chart Report.
The Pivot Table Wizard leads you through three steps:
• Allows you to specify where
your data is located and
Step whether you want a chart as
well as a table.
• Most commonly you’ll get
1: your data from an Excel list
that’s part of the current
worksheet.
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• Identifies the list range.
Step 2: • If you have the insertion point anywhere in the list
when you start the Wizard, Excel defines the list
range automatically.
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Step 3: • Creates the Pivot Table using its best guess as
to layout.
Use This
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If you choose the Layout button in Step 3 or invoke that view
while working with the Pivot Table, you get a dialog that looks like
this:
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Drag field buttons at right (representing variables from the list) to the
layout diagram at left.
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Once you’ve created your Pivot Table, you can modify it by using the buttons on the Pivot
Table toolbar that automatically displays.
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Pivot Table Row and Column Fields
A row • A row field in a Pivot Table is a variable that takes on different
values. For example, a row field might be “Manufacturer” and its
values might be “Desire”, “Marco Polo Jeans”, “New Fashion”,
“Vector” and “Young Look”.
field • The values a variable takes on are sometimes referred to as
“items”.
In the example below, for each value of the
Sum of Monthly Sales
variable “Manufacturer”, the Pivot Table displays a
Manufacturer Total
summary of the chosen data field in an adjoining
column. The data field in this example is “Annual Desire 120000
Sales” and the summary function is sum. Marco Polo Jeans 78000
New Fashion 15000
Vector 30000
Notice that the Pivot Table uses the label “Sum of Young Look 48000
Annual Sales” to identify not only the data field Grand Total 291000
(Annual Sales) but also the default summary
operation (sum).
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A column • A Pivot Table column field works like a row field. A column field
might be the variable “Year” with values ranging from 1999 to
2001. Data beneath each column in the Pivot Table is
field associated with the year at the head of the column.
Manufacturer Year Annual Sales Sum of Annual Sales Year
Vector 1999 $220,000 Manufacturer 1999 2000 2001 Grand Total
New Fashion 1999 $108,000 Desire $456,000 $460,000 $410,000 $1,326,000
Young Look 1999 $300,000 Marco Polo Jeans $234,000 $280,000 $360,000 $874,000
Desire 1999 $456,000 New Fashion $108,000 $100,000 $120,000 $328,000
Marco Polo Jeans 1999 $234,000 Vector $220,000 $230,000 $200,000 $650,000
Vector 2000 $230,000 Young Look $300,000 $302,000 $320,000 $922,000
New Fashion 2000 $100,000 Grand Total $1,318,000 $1,372,000 $1,410,000 $4,100,000
Young Look 2000 $302,000
Desire 2000 $460,000
Marco Polo Jeans 2000 $280,000
Vector 2001 $200,000
New Fashion 2001 $120,000
Young Look 2001 $320,000
Desire 2001 $410,000
Marco Polo Jeans 2001 $360,000
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When you define a Pivot Table you must identify a data field, or the
variable to summarize otherwise Excel displays an error. By contrast,
however, you need not define either a row or a column field. In this case,
you won’t get an error message but you won’t get a very meaningful
result either. Without a row and/or column “control”, Excel will return a
simple table since it will have no way to summarize the data.
If you specify a row field only, your Pivot Table will have one column
that contains the values of the row field and another column to its
right that contains the corresponding summary values for the data
field. If you specify a column field only, your Pivot Table will have a top
row that holds the values of the column field and a row beneath that
holds the corresponding summary values of the data field.
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Sum of Annual Sales
Manufacturer Total
Desire $1,326,000
Marco Polo Jeans $874,000
Row‐only Pivot Table
New Fashion $328,000
Vector $650,000
Young Look $922,000
Grand Total $4,100,000
Sum of Annual Sales Year
1999 2000 2001 Grand Total
Total $1,318,000 $1,372,000 $1,410,000 $4,100,000
Column‐only
Pivot Table
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The Pivot Table gets its name because it’s easy to modify, or
pivot (turn), the positions of the Pivot Table fields. Imagine a
point at the upper left‐hand corner of the Pivot Table as the
pivot point. You can drag and drop a row field up and to the
right, making it a column field. And you can drag and drop a
column field down and to the left, making it a row field. As
mentioned earlier, although you can return to the Wizard’s
layout view to accomplish this layout change, it’s easier to
do it on the fly without using the Wizard.
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Another Example
Using <wine.xls> file
State Jan-2000 Feb-2000 Mar-2000 Apr-2000 May-2000 Jun-2000 Jul-2000 Sep-2000 Oct-2000 Nov-2000 Dec-2000
CA 849.9 1065 1013.05 1612.6 1776.8 1426.8 1606.55 3155.7 1871.7 2014.7 1935.5
MA 958 1309
NJ 1256.8 1151.4 1016.4 982.6 928 1559.4 1050.6 2341.9 902.8 1163.2 923.4
NY 1552.8 705 603.5 703.2 1324.9 977.4 998.9 1825.4 1172.8 970.5 1244.4
Grand Total 3659.5 2921.4 2632.95 4256.4 4029.7 3963.6 3656.05 7323 3947.3 5457.4 4103.3
Now lets try to make this a bit more complicated.
What if you wanted to see what type of product was sold in each State?
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Select any cell within
the existing Pivot Table,
then select the menu
item Data ‐ Pivot
Tables… you will go
back to the Wizard at
step 3.
Sum of Sales Month
State Type Jan-2000 Feb-2000 Mar-2000 Apr-2000 May-2000 Jun-2000 Jul-2000 Sep-2000 Oct-2000 Nov-2000
CA Red 592.5 648 648 799.2 913 649 910.5 2204.2 1102.2 1305.7
White 257.4 417 365.05 813.4 863.8 777.8 696.05 951.5 769.5 709
CA Total 849.9 1065 1013.05 1612.6 1776.8 1426.8 1606.55 3155.7 1871.7 2014.7
MA Red 591 906
White 367 403
MA Total 958 1309
NJ Red 606 342 342 528 466.5 750 685.2 2076.4 252 786.2
White 650.8 809.4 674.4 454.6 461.5 809.4 365.4 265.5 650.8 377
NJ Total 1256.8 1151.4 1016.4 982.6 928 1559.4 1050.6 2341.9 902.8 1163.2
NY Red 1166.4 447 443.5 568.2 1049.4 720 364.5 906 399 628.5
White 386.4 258 160 135 275.5 257.4 634.4 919.4 773.8 342
NY Total 1552.8 705 603.5 703.2 1324.9 977.4 998.9 1825.4 1172.8 970.5
Grand Total 3659.5 2921.4 2632.95 4256.4 4029.7 3963.6 3656.05 7323 3947.3 5457.4
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Pivot it!
Sum of Sales Month
Type State Jan-2000 Feb-2000 Mar-2000 Apr-2000 May-2000 Jun-2000 Jul-2000 Sep-2000 Oct-2000 Nov-2000
Red CA 592.5 648 648 799.2 913 649 910.5 2204.2 1102.2 1305.7
MA 591 906
NJ 606 342 342 528 466.5 750 685.2 2076.4 252 786.2
NY 1166.4 447 443.5 568.2 1049.4 720 364.5 906 399 628.5
Red Total 2364.9 1437 1433.5 2486.4 2428.9 2119 1960.2 5186.6 1753.2 3626.4
White CA 257.4 417 365.05 813.4 863.8 777.8 696.05 951.5 769.5 709
MA 367 403
NJ 650.8 809.4 674.4 454.6 461.5 809.4 365.4 265.5 650.8 377
NY 386.4 258 160 135 275.5 257.4 634.4 919.4 773.8 342
White Total 1294.6 1484.4 1199.45 1770 1600.8 1844.6 1695.85 2136.4 2194.1 1831
Grand Total 3659.5 2921.4 2632.95 4256.4 4029.7 3963.6 3656.05 7323 3947.3 5457.4
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Creating another Pivot Table based on an
existing Table
Now, let say we want to see both Sales and Margin side by side so that
we can compare them. We could create another pivot table. It is better
to base the new Pivot Table on the existing Pivot Table, because this
way Excel uses the same memory cache for both Pivot Tables thus
making sure you do not run out of memory on large Tables.
Select a blank cell on your worksheet and start the Pivot Table Wizard.
On the first screen, check the option button that says the data resides
in Another Pivot Table;
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Original Pivot Table
Sum of Sales Month
Type State Jan-2000 Feb-2000 Mar-2000 Apr-2000 May-2000 Jun-2000 Jul-2000 Sep-2000 Oct-2000
Red CA 592.5 648 648 799.2 913 649 910.5 2204.2 1102.2
MA 591
NJ 606 342 342 528 466.5 750 685.2 2076.4 252
NY 1166.4 447 443.5 568.2 1049.4 720 364.5 906 399
Red Total 2364.9 1437 1433.5 2486.4 2428.9 2119 1960.2 5186.6 1753.2
White CA 257.4 417 365.05 813.4 863.8 777.8 696.05 951.5 769.5
MA 367
NJ 650.8 809.4 674.4 454.6 461.5 809.4 365.4 265.5 650.8
NY 386.4 258 160 135 275.5 257.4 634.4 919.4 773.8
White Total 1294.6 1484.4 1199.45 1770 1600.8 1844.6 1695.85 2136.4 2194.1
Grand Total 3659.5 2921.4 2632.95 4256.4 4029.7 3963.6 3656.05 7323 3947.3
Pivot Table using data from the above Pivot Table
Sum of Quanti Month
Type State 1/1/00 2/1/00 3/1/00 4/1/00 5/1/00 6/1/00 7/1/00 9/1/00 10/1/00
Red CA 31 28 48 51 56 44 69 116 59
MA 28
NJ 32 17 17 42 33 36 36 112 17
NY 60 17 25 29 54 30 18 54 14
Red Total 123 62 90 150 143 110 123 282 90
White CA 18 21 28 55 58 59 50 65 57
MA 25
NJ 43 48 39 37 31 48 27 18 43
NY 21 18 10 9 19 18 44 62 52
White Total 82 87 77 126 108 125 121 145 152
Grand Total 205 149 167 276 251 235 244 427 242
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Using Page Fields
Drag the Type Field button from the Row area to the Page area;
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Notice that sales for all product types are shown, and that a small arrow is placed beside the (All) label
next to the Type field. Click on this small arrow, a dropdown box appears that allows you to select one
of the Type values (either Red or White). Try this and watch the data change to show just White or Red
products.
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Grouping Data
It is a little difficult to pick trends over the twelve month data period. Select the
Month field by Clicking on the Month label on the Pivot Table. Then use menu item
Data‐Group and Outline‐Group… or Click on the Group toolbar button. A dialog will
ask how you wish to group the Month Field, select the Quarters option and Click
Finish.
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Sum of Sales Month
State Type Qtr1 Qtr2 Qtr3 Qtr4 Grand Total
CA Red $1,889 $2,361 $3,115 $3,955 $11,319
White $1,039 $2,455 $1,648 $1,867 $7,009
CA Total $2,928 $4,816 $4,762 $5,822 $18,328
MA Red $591 $906 $1,497
White $367 $403 $770
MA Total $958 $1,309 $2,267
NJ Red $1,290 $1,745 $2,762 $1,655 $7,451
White $2,135 $1,726 $631 $1,335 $5,826
NJ Total $3,425 $3,470 $3,393 $2,989 $13,277
NY Red $2,057 $2,338 $1,271 $1,670 $7,335
White $804 $668 $1,554 $1,718 $4,744
NY Total $2,861 $3,006 $2,824 $3,388 $12,079
Grand Total $9,214 $12,250 $10,979 $13,508 $45,951
Note various formatting options used along with
this Pivot Table.
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Sum of Sales Month
State Group Qtr1 Qtr2 Qtr3 Qtr4 Grand Total
CA Blend $330 $685 $1,021 $1,865 $3,902
Creating Melot
Pinot Noir
$180
$708
$378
$626
$54
$1,240
$252
$1,167
$864
$3,741
another table Riesling
Semillon
$668
$372
$2,135
$320
$1,558
$90
$1,124
$743
$5,485
$1,524
based on CA Total
Shiraz $671
$2,928
$672
$4,816
$800
$4,762
$671
$5,822
$2,813
$18,328
previous MA Blend
Pinot Noir
$330 $786
$120
$1,116
$120
table using Riesling
Semillon
$207
$160
$403 $610
$160
GROUP” field. MA Total
Shiraz $261
$958 $1,309
$261
$2,267
NJ Blend $336 $1,720 $400 $2,456
Melot $468 $162 $342 $972
Pinot Noir $822 $708 $772 $386 $2,688
Riesling $1,571 $1,264 $631 $1,175 $4,641
Semillon $564 $461 $160 $1,185
Shiraz $539 $270 $527 $1,335
NJ Total $3,425 $3,470 $3,393 $2,989 $13,277
NY Blend $1,481 $1,651 $666 $501 $4,299
Melot $108 $108 $198 $414
Pinot Noir $313 $579 $234 $708 $1,834
Riesling $362 $668 $1,074 $1,436 $3,540
Semillon $442 $480 $282 $1,204
Shiraz $263 $263 $263 $788
NY Total $2,861 $3,006 $2,824 $3,388 $12,079
Grand Total $9,214 $12,250 $10,979 $13,508 $45,951
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Field calculations
Select a cell anywhere on the
Pivot Table and call the Pivot
Table Wizard. Sum of Sales is
shown in the Data area,
Double‐Click this. Notice that
you can show the sum of sales
or the count of the number of
sales during a period, or
several other calculations. For
now, leave the selection at
Sum. Click on the Options
button, then select % of row
from the Show data as:
dropdown list.
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Sum of Sales Month
State Group Qtr1 Qtr2 Qtr3 Qtr4 Grand Total
CA Blend 8.46% 17.56% 26.17% 47.81% 100.00%
Melot 20.83% 43.75% 6.25% 29.17% 100.00%
Pinot Noir 18.93% 16.73% 33.15% 31.19% 100.00%
Riesling 12.18% 38.93% 28.41% 20.49% 100.00%
Semillon 24.38% 20.99% 5.88% 48.75% 100.00%
Shiraz 23.84% 23.89% 28.43% 23.84% 100.00%
CA Total 15.98% 26.28% 25.98% 31.76% 100.00%
MA Blend 0.00% 29.57% 0.00% 70.43% 100.00%
Pinot Noir 0.00% 0.00% 0.00% 100.00% 100.00%
Riesling 0.00% 33.93% 0.00% 66.07% 100.00%
Semillon 0.00% 100.00% 0.00% 0.00% 100.00%
Shiraz 0.00% 100.00% 0.00% 0.00% 100.00%
MA Total 0.00% 42.26% 0.00% 57.74% 100.00%
NJ Blend 0.00% 13.68% 70.02% 16.30% 100.00%
Melot 48.15% 16.67% 0.00% 35.19% 100.00%
Pinot Noir 30.58% 26.34% 28.72% 14.36% 100.00%
Riesling 33.84% 27.25% 13.60% 25.31% 100.00%
Semillon 47.59% 38.91% 0.00% 13.50% 100.00%
Shiraz 0.00% 40.34% 20.22% 39.44% 100.00%
NJ Total 25.79% 26.14% 25.55% 22.52% 100.00%
NY Blend 34.46% 38.39% 15.49% 11.65% 100.00%
Melot 0.00% 26.09% 26.09% 47.83% 100.00%
Pinot Noir 17.07% 31.57% 12.76% 38.60% 100.00%
Riesling 10.24% 18.87% 30.33% 40.57% 100.00%
Semillon 36.71% 0.00% 39.87% 23.42% 100.00%
Shiraz 33.33% 0.00% 33.33% 33.33% 100.00%
NY Total 23.69% 24.88% 23.38% 28.05% 100.00%
Grand Total 20.05% 26.66% 23.89% 29.40% 100.00%
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