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The blog posting 'The Power Of Yellow' describes how Show Alternatives can be used to highlight data excluded by a selection on a field that would otherwise be included. This QlikView application illustrates this functionality.
This tequnique can be useful in making immediately apparent something that would otherwise be hard to spot, or require extra clicks to remove selections.
For a full description of how and why the feature can be used please see the original blog post at: http://www.quickintelligence.co.uk/thepowerofyellow/
Steve Dark
What it is used for?
The Qualify statement is used for switching on the qualification of field names, i.e. field names will get the table name as a prefix.’
In situation where we have two (or more) Tables with the same field names:
Product  Payment 

The Qualify statement will assign name of the Table to fields:
Otherwise you will need to make changes the this path  [Qualify.xlsx]
QUALIFY *;
Product:
LOAD [Serial No],
Category,
Value
FROM
Qualify.xlsx
(ooxml, embedded labels, table is Product);
QUALIFY *;
Payment:
LOAD [Serial No],
Category,
Value
FROM
Qualify.xlsx
(ooxml, embedded labels, table is Payment);
The Outcome:
Table Viewer:
Read only if you need to know more....
If we have not used ‘QUALIFY’ statement in situation as above Qlikview would map both of the Tables with outcome like below:
The end result merge of those two Tables is correct only for the “Serial No” fields
The “Value” and “Category” fields although merged is none of use to us.
To fix this we can only Qualify fields that we do not want to associated:
QUALIFY Category,
Value;
Product:
LOAD [Serial No],
Category,
Value
FROM
Qualify.xlsx
(ooxml, embedded labels, table is Product);
QUALIFY Category,
Value;
Payment:
LOAD [Serial No],
Category,
Value
FROM
Qualify.xlsx
(ooxml, embedded labels, table is Payment);
or by using UNQUALIFY statement:
(which works as opposite to QUALIFY)
QUALIFY *;
UNQUALIFY [Serial No];
Product:
LOAD [Serial No],
Category,
Value
FROM
Qualify.xlsx
(ooxml, embedded labels, table is Product);
QUALIFY *;
UNQUALIFY [Serial No];
Payment:
LOAD [Serial No],
Category,
Value
FROM
Qualify.xlsx
(ooxml, embedded labels, table is Payment);
In second example the ‘QUALIFY *’ part will add Table name to all fields and the UNQUALIFY statement will remove those names only from specified fields(this method is very useful if we got large numbers of fields)
Outcome is as below:
Fields:
Table Viewer:
Feeling Qlikngry?
When showing data in a month on month style the current month can often have a large drop off. This can be prevented by providing a run rate for the current month. This is where the known values for the current period are extrapolated forward for the rest of the period, providing an estimate of where the period will end. For example, if you have a value of 1000 on day 10 of a 30 day month, you could calculate a run rate of 3000 for the month.
This solution was created in response to a question on Qlik Community, which you can find here:
Re: Last time value in time line chart
I have documented how this document works and the reasons why you might use it in a blog post here:
https://www.quickintelligence.co.uk/qlikrunrate/
There is also a link to the QlikView version of this application on the blog post, and further discussions on why run rates are good to have.
I hope that you find it useful. You will find other applications that I have uploaded under my profile on QlikCommunity.
Steve
Often when building QlikView applications, or picking up applications which have been built by someone else I want to have a quick and easy way of viewing the data that is in that application. To enable me to do this I have put together a page of objects that lists all tables and fields in the data model and then gives outline information about any selected field. These objects can be copied and pasted into any QlikView application to view the data model of that document.
I have documented how this document works and the reasons why you might use it in a blog post here:
https://www.quickintelligence.co.uk/qlikviewdataprofiler/
Please see the blog post for further details on using this document.
There is now a Qlik Sense version of this app, which you can find on Qlik Community here:
Qlik Sense App: Generic Data Profiler
I hope that you find it useful. You will find other applications that I have uploaded under my profile on QlikCommunity, or on our Downloads Page.
Steve
https://www.quickintelligence.co.uk/blog/
PLEASE NOTE: The 'With Mask' version of the file includes an experimental tab that may or may not work well on large data sets. Please see comment below for details. If you are not sure which to download go for DataProfiler.qvw. Thanks!
This example QlikView document shows how to create a bar chart that shows variance to target, both as an absolute value and as a percentage.
The charts produced look like this:
By showing both these charts you can see both how regions are comparing to each other and against the targets that have been set for them.
The example was created to accompany the Quick Intelligence blog post, that can be read here:
https://www.quickintelligence.co.uk/qliktargetbarchart/
The example is also available on Qlik Community as a Qlik Sense application.
A list of all our downloadable example files can be found here:
https://www.quickintelligence.co.uk/examples/
Hope you find this application useful.
Regards,
Steve
Definition:
Returns the number of dimension columns that have nonaggregation content. i.e. do not contain partial sums or collapsed aggregates.
A typical use is in attribute expressions, when you want to apply different cell formatting depending on aggregation level of data.
This function is only available in charts. For all chart types except pivot table it will return the number of dimensions in all rows except the total, which will be 0.
What does it mean?
We have Table with 4 dimensions(columns): Product,Category,Type,Sales
Now we want to create Pivot Table by using those Dimensions.
We are going to use only 3 of them(Product,Category,Type) and use 4th(Sales) in our expression.
The result is shown below:
This Pivot Table has 3 dimensions so its maximum dimensionality is 3.
For better understating please see table below.
The function is used to show on which dimensionality level each of the Pivot Table row is:
'Sugar' has dimensionality of 1 which is Total for that 'Product'.
'Salt' has dimensionality of 2 which is Total for each 'Category' of that 'Product'.
'Oil' has dimensionality of 3 which is single value for each 'Type' of the 'Product's' 'Category'.
So then more Dimension we use the greater dimensionality of our Pivot Table is.
Practical use:
1) To show the level of dimensionality:
Expression:
if(Dimensionality()=1 ,RGB(151,255,255),if(Dimensionality()=2 ,RGB(0,238,0),if(Dimensionality()=3,RGB(255,130,171))))
2) Highlight background of rows which on each level fall into certain condition:
Expression:
if(Dimensionality()=1 and sum(Sales)<150,RGB(151,255,255),if(Dimensionality()=2 and sum(Sales)<=20,RGB(0,238,0),if(Dimensionality()=3 and Sum(Sales)<=20,RGB(255,130,171))))
LEVEL1 > Values <140  LEVEL 2 > Values <=20  LEVEL 3 > Values <=20 

Otherwise you will need to make changes the this path  [Dimensionality.xlsx]
Directory;
LOAD Product,
Category,
Type,
Sales
FROM
[Dimensionality.xlsx]
(ooxml, embedded labels, table is Sheet1);
Felling Qlingry?
What it is used for?
To return values from another table field based on matching field value from current table.
Typically used when only one field records from another table are needed.
(You are dropping this (second) table later on.(see below) )
How does it look like?
How is it design?
and four arguments:
<>
Preparation:
We have got two tables in Excel file.
For convenience let’s call them ‘Table1’ and ‘Table2’:
Table1  Table2 

Remember
Otherwise you will need to make changes the this path  [LookUp.xlsx]
Table2:
LOAD Category,
Sales,
Country
FROM
[Lookup.xlsx]
(ooxml, embedded labels, table is Table2);
Table1:
LOAD Category,
Lookup('Country','Category',Category,'Table2') as Country
FROM
[Lookup.xlsx]
(ooxml, embedded labels, table is Table1);
drop table Table2;
Remember to... Look Up!
(This is where the name of this function has another meaning)
Table 2 must be above Table1!
or after Reload you will get script error.
How does it work?
Formula:
Script:
Table2:
LOAD Category,
Sales,
Country
FROM
[Lookup.xls]
(ooxml, embedded labels, table is Table2);
Table1:
LOAD Category,
Lookup('Country','Category',Category,'Table2') as Country
FROM
[Lookup.xlsx]
(ooxml, embedded labels, table is Table1);
drop table Table2;
Remember:
The final tables you should see are like this:
Pros:
You can look at first field in the table to return third one and to look at third field to return the first one.
Cons:
To overcome this drawback we can wrap the formula in IF function:
If(isnull(Lookup('Country','Category',Category,'Table2')),'No match',Lookup('Country','Category',Category,'Table2')) As Country
Exercise :
Return field ‘Sales’ from Table2 by using ‘Category’ field from Table1.
(Answer at the end of this article)
Appendix:
For many of you coming from Excel world and working with VLOOKUP this syntax is little difficult to understand at first.
Why we can not have:
Take value from this table go to the another table matched the field and return what we need?
So the syntax would have been:
Lookup(Category,Table2,Category,Country)
Would this not be simpler?
This is open question so please state your case....
Answer to Exercise:
Lookup('Sales','Category',Category,'Table2') as Sales
Still feeling hungry?
Hi Qlikers,
This document demonstrates the Benford's law.
To know more about Benford's law, please visit the below link
Benford's law  Wikipedia, the free encyclopedia
Benford’s law can often be used as an indicator of fraudulent data, and can assist with auditing accounting data
Benford's law represents the distribution of 1st Digit of your data set. For eg. sales figure $ 11292 can be represented as 1.
In above chart, we can identify that distribution of the digit 1 of actual data is higher than the Benford's law distribution for the digit 1. That means we need to investigate the transactions of the sales figures starting from digit 1.
Please find the attached sample data with QVW file
Also see,
Bullet points:
What actually a value of a string?
This is the value described by ANSI character standard where 0 ( NULL) is equal to 0 and ÿ to 255.
(For full ANSI character set please attached dosument)
Taking only the standard English alphabet (Az) ‘A’ will be the MIN and ‘z’ will be the MAX.
Remember:
In ANSI standard A < a and Z < z
(A=65,Z=90,a=97,z=122)
Language specific characters will be not recognized in the place where they are in your alphabet but they will be 'pushed' to the end
(see ANSI table)
MinString and MaxString works on dimensions (columns) only so you cannot use is to evaluate single character or strings .
(MaxString(‘a’,’z’…) is not supported
Examples:
1) MIN & MAX (textbox)
Data  Expression  Results 

MinString(Category) MaxString(Category) 
2) MIN and MAX of String per group (Straight table)
Data  Expression  Result 

MinString(Category) MaxString(Category) 
3) With condition:
Return Max and Min string based on another column
We are looking for MIN and MAX string value from column Category where Country='Poland'
Data  Expression  Solution  Result 

MinString( if(Country='Poland', Category, null()) )

4) With LEFT/RIGHT
When used with LEFT the result will be the same as without as the value will be still based on first characters.
Data  Expression  Solution  Result 

=MinString( Right(Country,1)) =MaxString( Right(Country,1)) 
5) With MID
Data  Expression  Solution  Result 

=MinString( Mid(Country,2,2)) =MaxString( Mid(Country,2,2)) 
6) With Substring
When our data are little scrambled TextBetween will return string between '.' and end of the row.
Data  Expression  Result 

=MinString(TextBetween(Country,'.','',1)) =MaxString(TextBetween(Country,'.','',1)) 
7) In set analysis
When Criteria of Sales is 2 return Country with highest and lowest string Value
Data  Expression  Result 

=MinString({<Sales={2}>} Country)

😎 With Aggr()
For each Country return lowest and highest Category string value.
Data  Expression  Result 

=Aggr(Minstring(Category),Country) =Aggr(Maxstring(Category),Country) 
If know about other ways of using these functions please let me know.
Have you ever wondered how the examples from the Qlikview help may look like?
Please see below and enjoy responsibly...
Before () and After()
Description
Returns the value of expression evaluated with a pivot table's dimension values as they appear in the column before the current column within a row segment in the pivot table. This function returns NULL in all chart types except pivot tables.
On the first column of a row segment a NULL value will be returned, as there is no column before this one.
If the table is onedimensional or if the expression is preceded by the total qualifier, the current row segment is always equal to the entire row.
If the pivot table has multiple horizontal dimensions, the current row segment will include only columns with the same values as the current column in all dimension rows except for the row showing the last horizontal dimension of the inter field sort order. The inter field sort order for horizontal dimensions in pivot tables is defined simply by the order of the dimensions from top to bottom.
Specifying an offset greater than 1 lets you move the evaluation of expression to columns further to the left of the current column. A negative offset number will actually make the before function equivalent to a after function with the corresponding positive offset number. Specifying an offset of 0 will evaluate the expression on the current column. Recursive calls will return NULL.
By specifying a third parameter n greater than 1, the function will return not one but a range of n values, one for each of n table columns counting to the left from the original cell. In this form, the function can be used as an argument to any of the special Chart Range Functions.
Data Model:
(Copy and Pasted below code into Edit Script window and reload)
LOAD * inline
[
Product ,Category ,Sales
Salt ,White, 30
Salt, Brown ,40
Salt ,Red ,30
Sugar ,White ,10
Sugar ,Brown ,20
Sugar ,Red ,20
Wine ,White ,40
Wine ,Brown ,30
Wine ,Red ,10
]
Example 1:
Let's build a Pivot Tables with Product as dimension and expressions as below:
The left hand side shows an ordinary use of Sales the right hand side result from our new expression.
sum( Sales ) > before(sum( Sales ) )
Salt value has been assigned to Sugar,
Sugar to Wine,
Salt is now NULL .(there is no column before this one)
sum( Sales ) > after(sum( Sales ) )
Here we see the opposite result:
Sugar value has been assigned to Salt,
Wine to Sugar
and Wine is NULL (no column after this one)
Example 2
Specifying the second criteria as 2 we shifted all values by 2 columns right or left.
before( sum( Sales ), 2 )
after( sum( Sales ), 2 )
Example 3
before(total sum( Sales ) )
after(total sum( Sales ) )
When using with one dimension this expression returns values as if we have used ordinary before/after (Sum(Sales))
For more than one dimension the return value will be based on last column of the first(top) dimension and then appropriate columns for the second dimension.
Salt and Sugar have been omitted leaving Wine as the last column
Example 4
rangesum (Before(sum(Sales),1,2))
RangeSum() takes 3 parameters
expression > Before/After(sum(Sales),
offset of columns>1
number of columns to sum>2
sum(Sales) rangesum (Before(sum(Sales),1,2))
In our example we are shifting our calculation one column to the right:
Salt  As there is no column before Salt this column has been ignored
Sugar we are shifting our calculation one column to the left (Salt) and are summing previous two columns.
As there is no column before Salt the final result is value of Salt alone.
Wine by shifting calculations one column to the left(Sugar) and summing two previous columns we getting 100+50=150
sum(Sales) rangesum (after(sum(Sales),1,2)
In this example we are shifting our calculation one column to the right:
Wine  As there is no column after Salt this column has been ignored
Sugar we are shifting our calculation one column to the right(Wine) and aresumming previous two columns.
As there is no column after Wine the final result is value of Wine alone.
Salt by shifting calculations one column to the right(Sugar) and summing two previous columns we getting 50+80=130
Still feeling hungry?
Do you Qualify? How to use QUALIFY statement
Missing Manual  GetFieldSelections() + Bonus Example
MaxString & MinString  How to + examples
The second dimension... or how to use secondarydimensionality()
Dear all,
Sharing simple example of What if analysis in Qlik Sense using Slider extension
GitHub  mhamano/qliksenseslider: Qlik Sense extension for a slider object
Hope will be good start for beginners
Vikas
This example shows how to call a macro that saves image files for a selected sheet and chart to a specified location on reload.
The saved images could then be published via a web site or Wall Board, for example.
This QlikView was written in response to a post in the QlikView UK user group.
For other tutorial apps you can download and use, please see:
https://www.quickintelligence.co.uk/qlikviewexamples/
Hope you find this app useful.
Steve Dark
This example has been produced to accompany the blog post QlikView Buttons, When, Why and How.
The shared QlikView demonstrates how actions can be attached a number of different types of objects and used to navigate and enrich a QlikView application. Download it and click around to see what you can find.
The blog article gives more information on Actions in QlikView, along with step by step instructions on how to implement some of what is displayed in this shared QlikView and a video walk through.
Please also see my other Community uploads here stevedarkand also listed on our website here https://www.quickintelligence.co.uk/examples/
Steve Dark
Hi Qlikers,
This document demonstrates the Bollinger Bands.
Many traders use Bollinger Bands to determine overbought and oversold levels, selling when price touches the upper Bollinger Band and buying when it hits the lower Bollinger Band.
Components of Bollinger Bands
1) Avg Stock Price
It's simple Avg of stock price.
2) Moving Avg of Stock Price
It's Moving Avg of Stock price over last n Period
3) Upper Band
Moving Avg of Stock Price + Std Deviation over last n Period * Std Deviation Multiplier
4) Lower Band
Moving Avg of Stock Price  Std Deviation over last n Period * Std Deviation Multiplier
Note :
1) User can select the Moving period and Std Deviation multiplier by own.
2) When you see the Bollinger Band by week, you can choose the Moving period from 1 to 50.
3) When you see the Bollinger Band by month, you can choose the Moving period from 1 to 10.
4) You can input the Std Deviation multiplier from 0.01 to 4.
Please see the attached Application
If you liked this then also see
Have you ever wondered how the examples from the Qlikview help may look like?
Please see below and enjoy responsibly...
Valueloop() & VaueList()
Both of those functions belong to Synthetic Dimension Functions.
Synthetic Dimension is a type of Calculated Dimension
 the difference between "standard" Calculated Dimension and Synthetic one is that
the standard dimensions are based on values from existing fields
whereas for Synthetic Dimensions those values are created "on the fly".
The drawback here is that you can not mix standard dimensions with synthetic in the way you would expect.
(please see "Practical use").
ValueLoop()
Used:
Back End No
Front End  Yes
Description(Qlikview Help)
Returns a set of iterated values which, when used in a calculated dimension, will form a synthetic dimension.
The values generated will start with the from value and end with the to value including intermediate values in increments of step. In charts with a synthetic dimension created with the valueloop function it is possible to reference the dimension value corresponding to a specific expression cell by restating the valuloop function with the same parameters in the chart expression. The function may of course be used anywhere in the layout, but apart from when used for synthetic dimensions it will only be meaningful inside an aggregation function
Create series of numbers in a range given by criteria.
from  first value
to  last value
step  intermediate values criteria.
When step is missing 1 is assumed
Qlikview help examples are very straightforwards and easy to understand:
Example 1  Example 2  Example 3 

valueloop ( 1, 3 ) From 1 to 3, (step is omitted so 1 is assumed):  valueloop ( 1, 5, 2 ) From 1 to 5, step 2: 1,1+2=3,3+2=5  valueloop ( 11 ) returns the value 11 
Practical use
Example 1
If you need to provide calculations to check if the MOD of values from 0 to 100 with step 5 is divided by 10 without remainder
Create Dimension: ValueLoop(0,100,5)
and Expression: if(mod(ValueLoop(0,100,5),10)=0,'OK', 'No OK')
See also:
How to create a Square Pie Chart
or
qlikfreak.wordpress.com/2014/06/17/infographicsinqlikviewvol2/
ValueList()
Used:
Back End No
Front End  Yes
Description(Qlikview Help)
Returns a set of listed values which, when used in a calculated dimension,
will form a synthetic dimension. In charts with a synthetic dimension created with the valuelist function it is possible to reference the dimension value corresponding to a specific expression cell by restating the valuelist function with the same parameters in the chart expression. The function may of course be used anywhere in the layout, but apart from when used for synthetic dimensions it will only be meaningful inside an aggregation function
Create series of values from given list
v1  list of values
Again, both of those examples are very easy to understand:
Header 1  Header 2 

valuelist ( 1, 10, 100 ) 
Header 1  Header 2 

valuelist ( 'a', 'xyz', 55 ) 
Practical use
Data Model
LOAD Date,
Year(Date) as Year,
Values
inline [
Date, Values
01/01/2009, 1
11/04/2009, 2
20/07/2009, 2
28/10/2009, 2
05/02/2010, 2
16/05/2010, 2
24/08/2010, 1
02/12/2010, 1
]
The usual way of creating straight table is be to add Year as Dimension and sum(Values) as expression.
This will return value for each Year.
But if we want o use Synthetic Dimension in the same way this will return only one Total value for both years.
One of the way to use this function is to create list (similar to Statistics Box) with your own KPI's:
and then use nested IF statement to create your Metrics
=if(ValueList('Sum','Count','Average')='Sum',Sum(Values),
if(ValueList('Sum','Count','Average')='Count',Count(Values),Avg(Values)))
to get below result:
As nesting IF's can be tricky and cumbersome beyond 2 or 3 criteria we can use Pick/Match functions to improve our calculations:
=pick(match(ValueList('Sum','Count','Average'),'Sum','Count','Average')
,Sum(Values),Count(Values),Avg(Values))
Conclusion:
Although both of those function are not very often used
(they did not make to final 30 of rwunderlich survey
you can find a practical way of using them.
Feeling Qlikngry?
Hi,
The Following blog was inspired by a recent post that allowed me to exercise my brain into trying something new
(link to thread: Qlikview Chart)
Below is one of the two charts to be achieved in Qlikview. This led / music equalizer style looked pretty cool so I had to try
I finished with a chart like this. Close enough I'd say.
You can also adjust the number of bands you wish to see on the chart, but make sure you adjust the percentage scales for background colors
How did we achieve this chart?
The Idea is to break each value into multiple segments and then use background expression to make only alternate segments visible.
Simple isn't it.
So we've basically turned a simple single dimension one expression chart into a Stacked Chart with two Dimensions and one Expression.
Apply the same approach with Grid Charts which allow other visualization possibilities.
These are just for your viewing pleasure, hope you enjoy playing with them as much as I did.
Happy Qlik'in
Cheers
Vineeth
Vineeth Pujari
This example shows an alternative way of showing current selections in your applications.
It is useful to see a complete list of all selections on every screen, but this can take a lot of space  leaving less room for analysis.
This shared QlikView uses a text box that sits neatly at the top of the page and shows what selections are currently in play. A large current selections box can then be shown or hidden dynamically by clicking the text box. This allows selections to be modified and removed in the standard way.
Using text boxes in itself can be a good way of conveying a lot of information in a small space. Attaching actions to items other than Buttons is a good way to a cleaner 'flat' UI. Combining the two things can work really well  as I hope this example shows.
Please see the other example apps I have uploaded also: Steve Dark
Regards,
Steve Dark
Prologue...
Firstly I would like to say that probably it would be easier to call this function Horizontal Dimensionality (or HDim or even SecDim)
This could clear some clouds  when you first see this function you may feel that this another level for dimensionality function.
(for those who wants to know more about the dimensionality function please see this document
What it is used for?
Returns the number of dimension pivot table rows that have nonaggregation content. i.e. do not contain partial sums or collapsed aggregates. This function is the equivalent of the dimensionality function for horizontal pivot table dimensions.
The secondarydimensionality() function always returns 0 when used outside of pivot tables.
What does it mean?
Where dimensionality shows number of vertical dimensions, secondarydimensionality shows number of horizontal dimensions.
Lets take our sample data.
We have four dimensions(columns):
Product,Category,Type and Sales.
Each Product have 2 Categories
Each Category can have up to 3 Types
Let's create Pivot Table using 3 of those Dimension Product,Category and Type and use Sales as our Expression.
This Pivot Table has 3 dimensions so its maximum dimensionality is 3.
'Sugar' has dimensionality of 1 which is Total for that 'Product'.
'Salt' has dimensionality of 2 which is Total for each 'Category' of that 'Product'.
'Oil' has dimensionality of 3 which is single value for each 'Type' of the 'Product's' 'Category'
So in few words : secondarydimensionality (and dimensionality) is the number of dimensions used in a Table
For better understating please see table below:
The function is used to show on which dimensionality level each of the Pivot Table row is:
Practical use:
1) To show the level of dimensionality:
Expression:
if(secondaryDimensionality()=1,RGB(151,255,255),if(secondaryDimensionality()=2,RGB(0,238,0),
if(secondaryDimensionality()=3,RGB(255,130,171))))
2) Highlight background of rows which on each level fall into certain condition:
Expression:
if(Dimensionality()=1 and sum(Sales)<150,RGB(151,255,255),if(Dimensionality()=2 and sum(Sales)<=20,RGB(0,238,0),if(Dimensionality()=3 and Sum(Sales)<=20,RGB(255,130,171))))
LEVEL 1 > Values <35  LEVEL 2 > Values <=15  LEVEL 3 > Values <=20 

Otherwise you will need to make changes the this path  secondarydimensionality.xlsx
Directory;
LOAD Product,
Category,
Type,
Sales
FROM
secondarydimensionality.xlsx
(ooxml, embedded labels, table is Sheet1);
Still feeling hungry?
Do you Qualify? How to use QUALIFY statement
Missing Manual  GetFieldSelections() + Bonus Example
MaxString & MinString  How to + examples
The second dimension... or how to use secondarydimensionality()