inweek - script and chart function

This function returns True if timestamp lies inside the week containing base_date.

Syntax:

InWeek (timestamp, base_date, period_no[, first_week_day])

Return data type: Boolean

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

Diagram that shows how the inweek() function can be used to evaluate dates within week segments and return a Boolean result if a dat does or does not fall into a selected range. — Diagram of inweek() function's range

The inweek() function uses the base_date argument to identify which seven-day period the date falls into. The start day of the week is based on the FirstWeekDay system variable. However, you can also change the first day of the week by using the first_week_day argument of the inweek() function.

After the selected week has been defined, the function will return Boolean results when comparing the prescribed date values to that week segment.

When to use it

The inweek() function returns a Boolean result. Typically, this type of function will be used as a condition in an if expression. The inweek() function returns an aggregation or calculation which depends on whether a date evaluated occurred in the week with the selected date of the base_date argument.

For example, the inweek() function can be used to identify all equipment manufactured in a specific week.

Arguments
Argument	Description
timestamp	The date that you want to compare with base_date.
base_date	Date that is used to evaluate the week.
period_no	The week can be offset by period_no. period_no is an integer, where the value 0 indicates the week which contains base_date. Negative values in period_no indicate preceding weeks and positive values indicate succeeding weeks.
first_week_day	By default, the first day of the week is Sunday (as determined by the FirstWeekDay system variable), starting at midnight between Saturday and Sunday. The first_week_day parameter supersedes the FirstWeekDay variable. To indicate the week starting on another day, specify a flag between 0 and 6.

first_week_day values
Day	Value
Monday	0
Tuesday	1
Wednesday	2
Thursday	3
Friday	4
Saturday	5
Sunday	6

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.

Function examples
Example	Result
inweek ('01/12/2006', '01/14/2006', 0)	Returns TRUE
inweek ('01/12/2006', '01/20/2006', 0 )	Returns FALSE
inweek ('01/12/2006', '01/14/2006', -1 )	Returns FALSE
inweek ('01/07/2006', '01/14/2006', -1)	Returns TRUE
inweek ('01/12/2006', '01/09/2006', 0, 3)	Returns FALSE because first_week_day is specified as 3 (Thursday), which makes 01/12/2006 the first day of the week following the week containing 01/09/2006.

These topics may help you work with this function:

Related topics
Topic	Default Flag / Value	Description
FirstWeekDay	6 / Sunday	Defines the start day of each week.

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 the month of January 2022 which is loaded into a table called ‘Transactions’.
The FirstWeekDay system variable which is set to 6 (Sunday).
A preceding load which contains the following:
- The inweek() function, set as the field ‘in_week’ that determines which transactions took place in the week of January 14, 2022.
- The weekday() function, set as the field ‘week_day’ that shows which day of the week corresponds to each date.

Load script

SET FirstWeekDay=6; 
SET DateFormat='MM/DD/YYYY'; 
 
Transactions: 
    Load 
       *, 
       weekday(date) as week_day, 
       inweek(date,'01/14/2022', 0) as in_week 
       ; 
Load 
* 
Inline  
[ 
id,date,amount 
8188,'01/02/2022',37.23 
8189,'01/05/2022',17.17 
8190,'01/06/2022',88.27 
8191,'01/08/2022',57.42 
8192,'01/09/2022',53.80 
8193,'01/10/2022',82.06 
8194,'01/11/2022',40.39 
8195,'01/12/2022',87.21 
8196,'01/13/2022',95.93 
8197,'01/14/2022',45.89 
8198,'01/15/2022',36.23 
8199,'01/16/2022',25.66 
8200,'01/17/2022',82.77 
8201,'01/18/2022',69.98 
8202,'01/26/2022',76.11 
8203,'01/27/2022',25.12 
8204,'01/28/2022',46.23 
8205,'01/29/2022',84.21 
8206,'01/30/2022',96.24 
8207,'01/31/2022',67.67 
];

Results

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

date
week_day
in_week

Results table
date	week_day	in_week
01/02/2022	Sun	0
01/05/2022	Wed	0
01/06/2022	Thu	0
01/08/2022	Sat	0
01/09/2022	Sun	-1
01/10/2022	Mon	-1
01/11/2022	Tue	-1
01/12/2022	Wed	-1
01/13/2022	Thu	-1
01/14/2022	Fri	-1
01/15/2022	Sat	-1
01/16/2022	Sun	0
01/17/2022	Mon	0
01/18/2022	Tue	0
01/26/2022	Wed	0
01/27/2022	Thu	0
01/28/2022	Fri	0
01/29/2022	Sat	0
01/30/2022	Sun	0
01/31/2022	Mon	0

The ‘in_week’ field is created in the preceding load statement by using the inweek() function. The first argument identifies which field is being evaluated. The second argument is a hard-coded date for January 14 which is the base_date. The base_date argument works in with the FirstWeekDay system variable to identify the comparator week. A period_no of 0 — meaning that the function is not comparing weeks preceding or following the segmented week — is the final argument.

The FirstWeekDay system variable determines that weeks begin on a Sunday and end on a Saturday. Therefore, January would be broken into weeks according to the diagram below, with the dates between January 9 and 15 providing the valid period for the inweek() calculation:

Diagram of a calendar showing a month, with the dates of 9 to 15 highlighted in green. 9 is a Sunday and 15 is a Saturday. — Diagram of calendar with the inweek() function's range highlighted

Any transaction that occurs between January 9 and the 15 of January returns a Boolean result of TRUE.

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 containing a set of transactions for 2022 is loaded into a table called ‘Transactions’.
The FirstWeekDay system variable which is set to 6 (Sunday).
A preceding load which contains the following:
- The inweek () function, set as the field ‘prev_week’ that determines which transactions took place a full week before the week of January 14, 2022.
- The weekday() function, set as the field ‘week_day’ that shows which day of the week corresponds to each date.

Load script

SET FirstWeekDay=6; 
SET DateFormat='MM/DD/YYYY'; 
 
Transactions: 
    Load 
       *, 
	weekday(date) as week_day, 
	inweek(date,'01/14/2022', -1) as prev_week  
       ; 
Load 
* 
Inline  
[ 
id,date,amount 
8188,'01/02/2022',37.23 
8189,'01/05/2022',17.17 
8190,'01/06/2022',88.27 
8191,'01/08/2022',57.42 
8192,'01/09/2022',53.80 
8193,'01/10/2022',82.06 
8194,'01/11/2022',40.39 
8195,'01/12/2022',87.21 
8196,'01/13/2022',95.93 
8197,'01/14/2022',45.89 
8198,'01/15/2022',36.23 
8199,'01/16/2022',25.66 
8200,'01/17/2022',82.77 
8201,'01/18/2022',69.98 
8202,'01/26/2022',76.11 
8203,'01/27/2022',25.12 
8204,'01/28/2022',46.23 
8205,'01/29/2022',84.21 
8206,'01/30/2022',96.24 
8207,'01/31/2022',67.67 
];

Results

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

date
week_day
prev_week

Results table
date	week_day	prev_week
01/02/2022	Sun	-1
01/05/2022	Wed	-1
01/06/2022	Thu	-1
01/08/2022	Sat	-1
01/09/2022	Sun	0
01/10/2022	Mon	0
01/11/2022	Tue	0
01/12/2022	Wed	0
01/13/2022	Thu	0
01/14/2022	Fri	0
01/15/2022	Sat	0
01/16/2022	Sun	0
01/17/2022	Mon	0
01/18/2022	Tue	0
01/26/2022	Wed	0
01/27/2022	Thu	0
01/28/2022	Fri	0
01/29/2022	Sat	0
01/30/2022	Sun	0
01/31/2022	Mon	0

Using -1 as the period_no argument in the inweek() function shifts the boundaries of the comparator week back by a full seven days. With a period_no of 0 the week would be between January 9 and 15. But in this example, the period_no of -1 shifts the start and end boundary of this segment backwards by one week. The date boundaries become January 2 to January 8.

Diagram of a calendar showing a month, with the dates of 2 to 8 highlighted in green. 2 is a Sunday and 8 is a Saturday. — Diagram of calendar with the inweek() function's range highlighted

Therefore, any transaction that occurs between January 2 and January 8 will return a Boolean result of TRUE.

Example 3 - first_week_day

Overview

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

The load script contains:

The same dataset containing a set of transactions for 2022 is loaded into a table called ‘Transactions’.
The FirstWeekDay system variable which is set to 6 (Sunday).
A preceding load which contains the following:
- The inweek() function, set as the field ‘in_week’ that determines which transactions took place in the week of January 14, 2022.
- The weekday() function, set as the field ‘week_day’ that shows which day of the week corresponds to each date.

Load script

SET FirstWeekDay=6; 
SET DateFormat='MM/DD/YYYY'; 
 
Transactions: 
    Load 
       *, 
	weekday(date) as week_day, 
	inweek(date,'01/14/2022', 0, 0) as in_week 
       ; 
Load 
* 
Inline  
[ 
id,date,amount 
8188,'01/02/2022',37.23 
8189,'01/05/2022',17.17 
8190,'01/06/2022',88.27 
8191,'01/08/2022',57.42 
8192,'01/09/2022',53.80 
8193,'01/10/2022',82.06 
8194,'01/11/2022',40.39 
8195,'01/12/2022',87.21 
8196,'01/13/2022',95.93 
8197,'01/14/2022',45.89 
8198,'01/15/2022',36.23 
8199,'01/16/2022',25.66 
8200,'01/17/2022',82.77 
8201,'01/18/2022',69.98 
8202,'01/26/2022',76.11 
8203,'01/27/2022',25.12 
8204,'01/28/2022',46.23 
8205,'01/29/2022',84.21 
8206,'01/30/2022',96.24 
8207,'01/31/2022',67.67 
];

Results

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

date
week_day
in_week

Results table
date	week_day	in_week
01/02/2022	Sun	0
01/05/2022	Wed	0
01/06/2022	Thu	0
01/08/2022	Sat	0
01/09/2022	Sun	0
01/10/2022	Mon	-1
01/11/2022	Tue	-1
01/12/2022	Wed	-1
01/13/2022	Thu	-1
01/14/2022	Fri	-1
01/15/2022	Sat	-1
01/16/2022	Sun	-1
01/17/2022	Mon	0
01/18/2022	Tue	0
01/26/2022	Wed	0
01/27/2022	Thu	0
01/28/2022	Fri	0
01/29/2022	Sat	0
01/30/2022	Sun	0
01/31/2022	Mon	0

Using 0 as the first_week_day argument in the inweek() function supersedes the FirstWeekDay system variable and sets Monday as the first day of the week.

Diagram of a calendar showing a month, with the dates of 10 to 16 highlighted in green. 10 is a Monday and 16 is a Sunday. — Diagram of calendar with the inweek() function's range highlighted

Therefore, any transaction that occurs between January 10 and 16 will return a Boolean result of TRUE.

Example 4 - Chart object example

Overview

The same dataset and scenario as the first example are used.

However, in this example, the dataset is unchanged and loaded into the application. Create a measure in the results table to determine which transactions took place in the week of January 14, 2022.

Load script

SET FirstWeekDay=6; 
SET DateFormat='MM/DD/YYYY'; 
 
Transactions: 
Load 
* 
Inline  
[ 
id,date,amount 
8188,'01/02/2022',37.23 
8189,'01/05/2022',17.17 
8190,'01/06/2022',88.27 
8191,'01/08/2022',57.42 
8192,'01/09/2022',53.80 
8193,'01/10/2022',82.06 
8194,'01/11/2022',40.39 
8195,'01/12/2022',87.21 
8196,'01/13/2022',95.93 
8197,'01/14/2022',45.89 
8198,'01/15/2022',36.23 
8199,'01/16/2022',25.66 
8200,'01/17/2022',82.77 
8201,'01/18/2022',69.98 
8202,'01/26/2022',76.11 
8203,'01/27/2022',25.12 
8204,'01/28/2022',46.23 
8205,'01/29/2022',84.21 
8206,'01/30/2022',96.24 
8207,'01/31/2022',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 measures:

=inweek (date,'01/14/2022',0), to calculate whether transactions took place in the same week as January 14.
=weekday(date), to show which day of the week corresponds to each date.

Results table
date	week_day	=inweek (date,'01/14/2022',0)
01/02/2022	Sun	0
01/05/2022	Wed	0
01/06/2022	Thu	0
01/08/2022	Sat	0
01/09/2022	Sun	-1
01/10/2022	Mon	-1
01/11/2022	Tue	-1
01/12/2022	Wed	-1
01/13/2022	Thu	-1
01/14/2022	Fri	-1
01/15/2022	Sat	-1
01/16/2022	Sun	0
01/17/2022	Mon	0
01/18/2022	Tue	0
01/26/2022	Wed	0
01/27/2022	Thu	0
01/28/2022	Fri	0
01/29/2022	Sat	0
01/30/2022	Sun	0
01/31/2022	Mon	0

The ‘in_week’ measure is created in chart by using the inweek() function. The first argument identifies which field is being evaluated. The second argument is a hard-coded date for January 14 which is the base_date. The base_date argument works in with the FirstWeekDay system variable to identify the comparator week. A period_no of 0 is the final argument.

Any transaction that occurs between January 9 and the 15 of January returns a Boolean result of TRUE.

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’.
The table contains the following fields:
- product ID
- product type
- manufacture date
- cost price

It has been identified that due to equipment error, products that were manufactured in the week of January 12 were defective. The end user would like a chart that displays, by week, the status of which products manufactured were ‘defective’ or ‘faultless’ and the cost of the products manufactured in that week.

Load script

Products: 
Load 
* 
Inline  
[ 
product_id,manufacture_date,cost_price
8188,'01/02/2022',37.23 
8189,'01/05/2022',17.17 
8190,'01/06/2022',88.27 
8191,'01/08/2022',57.42 
8192,'01/09/2022',53.80 
8193,'01/10/2022',82.06 
8194,'01/11/2022',40.39 
8195,'01/12/2022',87.21 
8196,'01/13/2022',95.93 
8197,'01/14/2022',45.89 
8198,'01/15/2022',36.23 
8199,'01/16/2022',25.66 
8200,'01/17/2022',82.77 
8201,'01/18/2022',69.98 
8202,'01/26/2022',76.11 
8203,'01/27/2022',25.12 
8204,'01/28/2022',46.23 
8205,'01/29/2022',84.21 
8206,'01/30/2022',96.24 
8207,'01/31/2022',67.67 
];

Results

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

=weekname(manufacture_date)

Create the following measures:

=if(only(inweek(manufacture_date,makedate(2022,01,12),0)),'Defective','Faultless'), to identify which of the products are defective and which are faultless using the inweek() function.
=sum(cost_price), to show the sum of the cost of each product.

Do the following:

Set the measure’s Number Formatting to Money.
Under Appearance, turn off Totals.

Results table
weekname(manufacture_date)	=if(only(inweek(manufacture_date,makedate(2022,01,12),0)), 'Defective','Faultless')	Sum(cost_price)
2022/02	Faultless	200.09
2022/03	Defective	441.51
2022/04	Faultless	178.41
2022/05	Faultless	231.67
2022/06	Faultless	163.91

The inweek() function returns a Boolean value when evaluating the manufacturing dates of each of the products. For any product manufactured in the week of January 12, the inweek() function returns a Boolean value of TRUE and marks the products as ‘Defective’. For any product returning a value of FALSE, and therefore not manufactured in that week, it marks the products as ‘Faultless’.

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