inquartertodate - script and chart function

This function returns True if timestamp lies inside the part of the quarter containing base_date up until and including the last millisecond of base_date.

Syntax:

InQuarterToDate (timestamp, base_date, period_no [, first_month_of_year])

Return data type: Boolean

In Qlik Sense, the Boolean true value is represented by -1, and the false value is represented by 0.

Example diagram of the range of dates within which the inquartertodate function will return a value of TRUE. In this case, it returns TRUE for certain values in the first half of the second quarter of the year, and FALSE for all other values. — Diagram of inquartertodate function

The inquartertodate() function divides the year into four equal quarters between January 1 and December 31 (or the user-defined start of year and its corresponding end date). Using the base_date, the function will then segment a particular quarter, with the base_date identifying both which quarter and the maximum allowed date for that quarter segment. Finally, the function returns a Boolean result when comparing the prescribed date values to that segment.

Arguments
Argument	Description
timestamp	The date that you want to compare with base_date.
base_date	Date that is used to evaluate the quarter.
period_no	The quarter can be offset by period_no. period_no is an integer, where the value 0 indicates the quarter which contains base_date. Negative values in period_no indicate preceding quarters and positive values indicate succeeding quarters.
first_month_of_year	If you want to work with (fiscal) years not starting in January, indicate a value between 2 and 12 in first_month_of_year.

When to use it

The inquartertodate() function returns a Boolean result. Typically, this type of function will be used as a condition in an if expression. The inquartertodate() function would be used to return an aggregation or calculation dependent on whether a date evaluated occurred in the quarter up to and including the date in question.

For example, the inquartertodate() function can be used to identify all equipment manufactured in a quarter up to a specific date.

Function examples
Example	Result
inquartertodate('01/25/2013', '03/25/2013', 0)	Returns TRUE, since the value of timestamp, 01/25/2013, lies within the three-month period from 01/01/2013 to  03/25/2013, in which the value of base_date, 03/25/2013, lies.
inquartertodate('04/26/2013', '03/25/2013', 0)	Returns FALSE, since 04/26/2013 is outside the same period as the previous example.
inquartertodate('02/25/2013', '06/09/2013', -1)	Returns TRUE, since the value of period_no, -1, shifts the search period back one period of three months (one quarter of the year). This makes the search period 01/01/2013 to 03/09/2013.
inquartertodate('03/25/2006', '04/15/2006', 0, 2)	Returns TRUE, since the value of first_month_of_year is set to 2, which makes the search period 02/01/2006 to 04/15/2006 instead of 04/01/2006 to 04/15/2006.

Regional settings

Unless otherwise specified, the examples in this topic use the following date format: MM/DD/YYYY. The date format is specified in the SET DateFormat statement in your data load script. The default date formatting may be different in your system, due to your regional settings and other factors. You can change the formats in the examples below to suit your requirements. Or you can change the formats in your load script to match these examples.

Default regional settings in apps are based on the regional system settings of the computer or server where Qlik Sense is installed. If the Qlik Sense server you are accessing is set to Sweden, the Data load editor will use Swedish regional settings for dates, time, and currency. These regional format settings are not related to the language displayed in the Qlik Sense user interface. Qlik Sense will be displayed in the same language as the browser you are using.

Example 1 – No additional arguments

Overview

Open the Data load editor and add the load script below to a new tab.

The load script contains:

A dataset containing a set of transactions for 2022, which is loaded into a table called Transactions.
The date field provided in the DateFormat system variable (MM/DD/YYYY) format.
The creation of a field, in_quarter_to_date, that determines which transactions took place in the quarter up until May 15, 2022.

Load script

SET DateFormat='MM/DD/YYYY';
						
Transactions:
    Load
        *,
        inquartertodate(date,'05/15/2022', 0) as in_quarter_to_date
        ;
Load
*
Inline
[
id,date,amount
8188,'1/19/2022',37.23
8189,'1/7/2022',17.17
8190,'2/28/2022',88.27
8191,'2/5/2022',57.42
8192,'3/16/2022',53.80
8193,'4/1/2022',82.06
8194,'5/7/2022',40.39
8195,'5/16/2022',87.21
8196,'6/15/2022',95.93
8197,'6/26/2022',45.89
8198,'7/9/2022',36.23
8199,'7/22/2022',25.66
8200,'7/23/2022',82.77
8201,'7/27/2022',69.98
8202,'8/2/2022',76.11
8203,'8/8/2022',25.12
8204,'8/19/2022',46.23
8205,'9/26/2022',84.21
8206,'10/14/2022',96.24
8207,'10/29/2022',67.67
];

Results

Load the data and open a sheet. Create a new table and add these fields as dimensions:

date
in_quarter_to_date

Results table
date	in_quarter_to_date
1/7/2022	0
1/19/2022	0
2/5/2022	0
2/28/2022	0
3/16/2022	0
4/1/2022	-1
5/7/2022	-1
5/16/2022	0
6/15/2022	0
6/26/2022	0
7/9/2022	0
7/22/2022	0
7/23/2022	0
7/27/2022	0
8/2/2022	0
8/8/2022	0
8/19/2022	0
9/26/2022	0
10/14/2022	0
10/29/2022	0

The in_quarter_to_date field is created in the preceding load statement by using the inquartertodate() function. The first argument provided identifies which field is being evaluated. The second argument is a hard-coded date for the for May 15, which is the base_date that identifies which quarter to segment and defines the end boundary of that segment. A period_no of 0 is the final argument, meaning that the function is not comparing quarters preceding or following the segmented quarter.

Diagram showing the range of dates for which the inquartertodate function will return a value of TRUE. This example contains no additional arguments. — Diagram of inquartertodate function, no additional arguments

Any transaction that occurs in between April 1 and May 15 returns a Boolean result of TRUE. Transactions dates of May 16 and later will return FALSE, as do any transactions before April 1.

Example 2 – period_no

Overview

Open the Data load editor and add the load script below to a new tab.

The load script contains:

The same dataset and scenario as the first example.
The creation of a field, previous_qtr_to_date, that determines which transactions took place a full quarter before the quarter segment ending on May 15, 2022.

Load script

SET DateFormat='MM/DD/YYYY';

Transactions:
    Load
        *,
        inquartertodate(date,'05/15/2022', -1) as previous_qtr_to_date
        ;
Load
*
Inline
[
id,date,amount
8188,'1/19/2022',37.23
8189,'1/7/2022',17.17
8190,'2/28/2022',88.27
8191,'2/5/2022',57.42
8192,'3/16/2022',53.80
8193,'4/1/2022',82.06
8194,'5/7/2022',40.39
8195,'5/16/2022',87.21
8196,'6/15/2022',95.93
8197,'6/26/2022',45.89
8198,'7/9/2022',36.23
8199,'7/22/2022',25.66
8200,'7/23/2022',82.77
8201,'7/27/2022',69.98
8202,'8/2/2022',76.11
8203,'8/8/2022',25.12
8204,'8/19/2022',46.23
8205,'9/26/2022',84.21
8206,'10/14/2022',96.24
8207,'10/29/2022',67.67
];

Results

Load the data and open a sheet. Create a new table and add these fields as dimensions:

date
previous_qtr_to_date

Results table
date	previous_qtr_to_date
1/7/2022	-1
1/19/2022	-1
2/5/2022	-1
2/28/2022	0
3/16/2022	0
4/1/2022	0
5/7/2022	0
5/16/2022	0
6/15/2022	0
6/26/2022	0
7/9/2022	0
7/22/2022	0
7/23/2022	0
7/27/2022	0
8/2/2022	0
8/8/2022	0
8/19/2022	0
9/26/2022	0
10/14/2022	0
10/29/2022	0

A period_no value of -1 indicates that the inquartertodate () function compares the input quarter segment to the preceding quarter. May 15 falls into the second quarter of the year, so the segment initially equates to between April 1 and May 15. The period_no then offsets this segment by three months earlier, causing the date boundaries to become January 1 to February 15.

Diagram showing the range of dates for which the inquartertodate function will return a value of TRUE. In this example, the period_no argument is set to -1. — Diagram of inquartertodate function, period_no example

Therefore, any transaction that occurs between January 1 and February 15 will return a Boolean result ofTRUE.

Example 3 – first_month_of_year

Overview

Open the Data load editor and add the load script below to a new tab.

The load script contains:

The same dataset and scenario as the first example.
The creation of a field, in_quarter_to_date, that determines which transactions took place in the same quarter up to May 15, 2022.

In this example, we set March as the first month of the fiscal year.

Load script

SET DateFormat='MM/DD/YYYY';

Transactions:
    Load
        *,
        inquartertodate(date,'05/15/2022', 0,3) as in_quarter_to_date
        ;
Load
*
Inline
[
id,date,amount
8188,'1/19/2022',37.23
8189,'1/7/2022',17.17
8190,'2/28/2022',88.27
8191,'2/5/2022',57.42
8192,'3/16/2022',53.80
8193,'4/1/2022',82.06
8194,'5/7/2022',40.39
8195,'5/16/2022',87.21
8196,'6/15/2022',95.93
8197,'6/26/2022',45.89
8198,'7/9/2022',36.23
8199,'7/22/2022',25.66
8200,'7/23/2022',82.77
8201,'7/27/2022',69.98
8202,'8/2/2022',76.11
8203,'8/8/2022',25.12
8204,'8/19/2022',46.23
8205,'9/26/2022',84.21
8206,'10/14/2022',96.24
8207,'10/29/2022',67.67
];

Results

Load the data and open a sheet. Create a new table and add these fields as dimensions:

date
in_quarter_to_date

Results table
date	in_quarter_to_date
1/7/2022	0
1/19/2022	0
2/5/2022	0
2/28/2022	0
3/16/2022	-1
4/1/2022	-1
5/7/2022	-1
5/16/2022	0
6/15/2022	0
6/26/2022	0
7/9/2022	0
7/22/2022	0
7/23/2022	0
7/27/2022	0
8/2/2022	0
8/8/2022	0
8/19/2022	0
9/26/2022	0
10/14/2022	0
10/29/2022	0

By using 3 as the first_month_of_year argument in the inquartertodate() function, the function begins the year on March 1, and then divides the year into quarters. Therefore, the quarter segments are:

March to May
June to August
September to November
December to February

The base_date of May 15 then segments the March to May quarter by setting its end boundary as May 15.

Diagram showing the range of dates for which the inquartertodate function will return a value of TRUE. In this example, the first_month_of_year is defined as 3, setting March to the first month of the year. — Diagram of inquartertodate function, first_month_of_year example

Therefore, any transaction that occurs in between the March 1 and May 15 will return a Boolean result of TRUE, while transactions with dates outside these boundaries will return a value of FALSE.

Example 4 – Chart object example

Overview

Open the Data load editor and add the load script below to a new tab.

The load script contains the same dataset and scenario as the first example. However, in this example, the unchanged dataset is loaded into the application. The calculation that determines which transactions took place in the same quarter as May 15 is created as a measure in the chart object.

Load script

SET DateFormat='MM/DD/YYYY';

Transactions:
Load
*
Inline
[
id,date,amount
8188,'1/19/2022',37.23
8189,'1/7/2022',17.17
8190,'2/28/2022',88.27
8191,'2/5/2022',57.42
8192,'3/16/2022',53.80
8193,'4/1/2022',82.06
8194,'5/7/2022',40.39
8195,'5/16/2022',87.21
8196,'6/15/2022',95.93
8197,'6/26/2022',45.89
8198,'7/9/2022',36.23
8199,'7/22/2022',25.66
8200,'7/23/2022',82.77
8201,'7/27/2022',69.98
8202,'8/2/2022',76.11
8203,'8/8/2022',25.12
8204,'8/19/2022',46.23
8205,'9/26/2022',84.21
8206,'10/14/2022',96.24
8207,'10/29/2022',67.67
];

Results

Load the data and open a sheet. Create a new table and add this field as a dimension:date.

Create the following measure:

=inquartertodate(date,'05/15/2022', 0)

Results table
date	=inquartertodate(date,'05/15/2022', 0)
1/7/2022	0
1/19/2022	0
2/5/2022	0
2/28/2022	0
3/16/2022	0
4/1/2022	-1
5/7/2022	-1
5/16/2022	0
6/15/2022	0
6/26/2022	0
7/9/2022	0
7/22/2022	0
7/23/2022	0
7/27/2022	0
8/2/2022	0
8/8/2022	0
8/19/2022	0
9/26/2022	0
10/14/2022	0
10/29/2022	0

The in_quarter_to_date measure is created in a chart object by using the inquartertodate() function. The first argument is the date field being evaluated. The second argument is a hard-coded date for May 15, which is the base_date that identifies which quarter to segment and defines the end boundary of that segment. A period_no of 0 is the final argument, meaning that the function is not comparing quarters preceding or following the segmented quarter.

Diagram showing the range of dates for which the inquartertodate function will return a value of TRUE. The function determines whether transactions took place in the same quarter as May 15. — Diagram of inquartertodate function, chart object example

Any transaction that occurs between April 1 and May 15 returns a Boolean result of TRUE. Transactions on May 16 and later will return FALSE, as do any transactions before April 1.

Example 5 – Scenario

Overview

Open the Data load editor and add the load script below to a new tab.

The load script contains:

A dataset which is loaded into a table called Products.
Information concerning product ID, manufacture date, and cost price.

On May 15, 2022, a piece of equipment error was identified in the manufacturing process and resolved. Products that were manufactured in that quarter up to this date will be defective. The end user would like a chart object that displays, by quarter name, the status of whether the product is ‘defective’ or ‘faultless’ and the cost of the products manufactured in that quarter to date.

Load script

Products:
Load
*
Inline 
[
product_id,manufacture_date,cost_price
8188,'1/19/2022',37.23
8189,'1/7/2022',17.17
8190,'2/28/2022',88.27
8191,'2/5/2022',57.42
8192,'3/16/2022',53.80
8193,'4/1/2022',82.06
8194,'5/7/2022',40.39
8195,'5/16/2022',87.21
8196,'6/15/2022',95.93
8197,'6/26/2022',45.89
8198,'7/9/2022',36.23
8199,'7/22/2022',25.66
8200,'7/23/2022',82.77
8201,'7/27/2022',69.98
8202,'8/2/2022',76.11
8203,'8/8/2022',25.12
8204,'8/19/2022',46.23
8205,'9/26/2022',84.21
8206,'10/14/2022',96.24
8207,'10/29/2022',67.67
];

Results

Do the following:

Load the data and open a sheet. Create a new table. Create a dimension to show the quarter names:

=quartername(manufacture_date)
Next, create a dimension to identify which of the products are defective and which are faultless:

=if(inquartertodate(manufacture_date,makedate(2022,05,15),0),'Defective','Faultless')
Create a measure to sum the cost_price of the products:

=sum(cost_price)
Set the measure's Number formatting to Money.

Results table
quartername(manufacture_date)	if(inquartertodate(manufacture_date,makedate(2022,05,15),0),'Defective','Faultless')	Sum(cost_price)
Jan-Mar 2022	Faultless	$253.89
Apr-Jun 2022	Faultless	$229.03
Apr-Jun 2022	Defective	$122.45
Jul-Sep 2022	Faultless	$446.31
Oct-Dec 2022	Faultless	$163.91

The inquartertodate() function returns a Boolean value when evaluating the manufacturing dates of each of the products. For those that return a Boolean value of TRUE, it marks the products as ‘Defective’. For any product returning a value of FALSE, and therefore not made in the quarter up to and including May 15, it marks the products as ‘Faultless’.

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