Pivot tables c01

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Multi-dimensional Data
Analysis using Excel
- - - - -
Pivot Tables

Copyright © 2007 Prentice-Hall. All rights reserved
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When reading these notes please
remember that they are for use in the
classroom with a qualified and
experience instructor who will explain and
illustrate as the class discusses the
issues covered during this session.
They are NOT designed for stand-alone
instruction (that may come later).

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1. Pivot Tables - Intro
2. A well-structured Data Source
3. Prepare the Data
4. The Resultant Pivot Table
5. Dimensions
6. Final Report
7. Keyboard shortcut
8. Grouping
9. Data Area
10. Rows & Columns

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1. Pivot Table Intro
 Data section
 Rows & Columns section
 Page section
A 1st Pivot Table example

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Color Date Quantity
Red 1/2/2010 56
Green 2/2/2010 73
Total 129
This means that we can draw a table with Rows and Columns on
2-dimensional paper.
If we need to illustrate more than 2 dimensions we could (with
some difficulty) draw 3 dimensions but not 4 or above.

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Instructor will now Draw a hierarchy on the white board to illustrate >2 dimensions

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When analyzing data, we need to:
1. Design the report
(Start with the end in mind - Stephen Covey)
2. Consider the source of the data and its structure
and modify where necessary.
3. Invoke the feature in Excel that lets us analyze the
data (Pivot Table wizard)
4. Transfer the fields into the report framework
5. Format the report or produce another form of final
report

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A Pivot Table
is a sophisticated tool for creating a summary table
from a list of data.
Such a source list can be termed a database.

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1a. Data section
The Data section is the most important item because
you cannot analyze anything unless you know what
you wish to analyze.
In the table as drawn, the data to be analyzed is the
Quantity column and forms the core of the analysis.
Note: The Date and the Color columns are not the data
but are attributes to set the dimensions (or attributes) in
terms of which (how) we are analyzing the data.
The data could take the form of:
1. Monetary data
2. Quantity data
3. Text (in which case the analysis will return a count)

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1b. Bottom line:
What are we analyzing?

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1c. Rows and Columns section
After the Data, we need to choose the Rows and
Columns from the available attributes. (1)
If we consider the table, the data to be analyzed is the
Quantity and we probably want to analyze it in terms of
the Color and the Date attributes.
Sales Jan Feb Mar
Blue 11 33 22
Red 45 34 43
Green 21 23 45
Without using anything clever (because there is only 1
observation per likely result) we could arrive at the
following analysis.
Then we can sum the rows and columns (or we can
use a PT report). (2)

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1d. First PT – Use the wizard:
Excel 2003: DataPivotTableFinish
Excel 2007: InsertPivotTableOK
Excel 2010: InsertPivotTableOK
Sum of
Number Date
Color Jan Feb Mar Total
Blue 11 33 22 66
Green 21 23 45 89
Red 45 34 43 122
Total 77 90 110 277
Arrange the Data, Cols & Rows thus:

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2. A Well-structured data source:
Rule: the data must be in tabular form
so that we have a database to work on
- blank columns, rows or cells may cause problems
(In Database terms: blanks are like having a NULL
and a Null is not equal to 0 it is undefined!)
Note: If the data contains section headings they have to
be eliminated and placed in cells so that they are
duplicated in each row - so that you have a de-normalized
data source

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Note: Use the following routine to fill blank
cells in a column:
5. Highlight the entire column
1. Highlight the column
2. {Ctrl-G} - GoTo blanks
3. ={up arrow}
4. {Ctrl - Enter} to enter the formula (the = up arrow) in all
cells selected
6. Copy - PasteSpecialValues to drop the formulas

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A Single Dimension:
The Source data should be stated in a single
dimension:
In Database terms:
have denormalized data instead of normalized data
 rather columns of the data for which you wish to
have sub-headings - columns which are already
analyzed.
 a matrix format is NOT ideal for a Source

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A Single Dimension:
Have a date-column and a value-column rather than
Dates in columns and Values in rows, like this:
Color Date Number
Blue Jan 11
Red Jan 45
Green Jan 21
Blue Feb 33
Red Feb 34
Green Feb 23
Blue Mar 22
Red Mar 43
Green Mar 45

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A Single Dimension:
Not like this:
Sales Jan Feb Mar
Blue 11 33 22
Red 45 34 43
Green 21 23 45
Which is already a result!

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3. Prepare the Source Data:
Before you start, you should design your report on
paper - if it does not work on paper it will not work in
practice and, for a complex report, it may make the job
easier
When designing a report, remember that you are
portraying the data in 2 dimensions - which is the basic
table formed from Rows and Columns.
However, multiple dimensions can be portrayed by
using hierarchies from the Data Source.

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We want a table with Each Days Sales totaled by
Months and also each Year.
We also want the table to show Sales per City, and State.

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We can have a hierarchy for the columns and a
hierarchy for the rows.
Another way to say this is that we can sub-total the
data and layer these sub-totals
State City Date Month Year Sales $
CA SFC 1/1/07 January 2007 100
CA LA 1/2/07 January 2007 222
Michigan Troy 2/1/07 February 2007 333
Michigan Chicago 1/1/07 January 2007 444
CA LA 1/2/07 January 2007 555
CA LA 2/1/07 February 2007 666
CA SFC 2/1/07 February 2007 999
Michigan Troy 1/1/07 January 2007 121
Michigan Troy 2/1/07 February 2007 343
Michigan Chicago 2/1/07 February 2007 676
Michigan Chicago 2/1/07 February 2007 555

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4. The Resultant Pivot Table:
Process the table without the State dimension and
produce this PT Report
Sales $ City
Year Month Date Chicago LA SFC Troy Grand Total
2007 January 1/1/2007 1231 877 575 2683
1/2/2007 1554 777 888 232 3451
January Total 2785 777 1765 807 6134
February 2/1/2007 1231 666 999 676 3572
February Total 1231 666 999 676 3572
2007
Total 4016 1443 2764 1483 9706
Grand
Total 4016 1443 2764 1483 9706

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When you add the State to the Columns you get:
Sales $ State City
CA CA
Total
Michigan Michigan
Total
Grand
Total
Year Month Date LA SFC Chicago Troy
2007 Jan 1/1/2007 877 877 1231 575 1806 2683
1/2/2007 777 888 1665 1554 232 1786 3451
Jan Total 777 1765 2542 2785 807 3592 6134
Feb 2/1/2007 666 999 1665 1231 676 1907 3572
Feb Total 666 999 1665 1231 676 1907 3572
2007
Total 1443 2764 4207 4016 1483 5499 9706
Grand
Total 1443 2764 4207 4016 1483 5499 9706

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One of the characteristics of this table has been that there
are 2 'Natural' hierarchies - formed from:
- Date (Year, Month)
- Region, Address (State, City)
There are 2 hierarchies for columns and rows - and a
Grand Total on each axis.
This has a restriction - we cannot, with any sense,
change the order of the hierarchy.
In makes no sense to change the sub-totals to Day
instead of Month.
It does not have to be that way and we also could use
unrelated sub-totals.
We can create different pivot points or points of view
or different ways of looking at the data
or we can describe it as analyzing in different ways.

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5. Dimensions:
The left column forms the hierarchies that we will use for analysis.
For a time-hierarchy we will make this the Columns - the rest of
the Product Characteristics will form the Row hierarchy.
The database should not have columns for the choices (Red,
Green, Blue, and White) but rather have a column for Color
containing values Red, Green, Blue, and White.
Dimension Value 1 Value 2 Value 3 Value 4
Color
Red Green Blue White
Sleeve
Long Short
Size S M L XL
Collar Yes No
Style Sports Dress Casual Golf
Year 2006 2007
Month Jan Feb Mar Etc
Day Date 1 2 Etc
This means that you can add another color with no effort and
incur no changes in the design (no additional columns).

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7. Keyboard Shortcut:
A shortcut way of processing the Pivot Table is to use the
shortcut keys.
Excel 2003
Alt-D, P, F will take you through the Wizard to the Field List
without having to step your way through the wizard.

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8. Grouping Pivot Table Items
if you have dates and you want to group the rows into Months
you can go to the Pivot Table and
select the Date heading,
then RtClk and choose Group,
From the Window that appears you can choose Month and
Year - when you 1xClk ‘OK’
the Pivot Table will be modified into Year and Month Headings
instead of individual dates.

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8. Grouping Pivot Table Items
if you have dates and you want to group the rows into Months
you can go to the Pivot Table and
select the Date heading,
then RtClk and choose Group,
From the Window that appears you can choose Month and
Year - when you 1xClk ‘OK’
the Pivot Table will be modified into Year and Month Headings
instead of individual dates.
Caveat: If the range of months exceeds a year you should
chose both Year AND month,
otherwise you will get the months but each month will contain
the months from more than one year.

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9. Data Area
Consider the Data Area first but do not drag items to this area
first.
The information in this section is usually defined as:
- type = number, or quantity
- type = money.
This means that the subject of the analysis needs to be
considered first because this forms the information that will
result in the body of the PT.

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10. Rows and Columns (Subtotals and Headings)
Rows will form one of the 2 dimension hierarchies and
Columns the other dimensional hierarchy.
There arises a problem - because you can only have 2
dimensions on paper and if you mix dimensions the PT will
display them as different levels of a dimension.
i.e. A natural dimension may be formed by Year/Month
but Red/Large has no hierarchical meaning - but is shown as
one of the 2 possible dimensions displayed on the 'paper.'

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That’s all folks!
The End

Pivot tables c01

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