This function returns
a value showing the year and week number with an underlying numeric
value corresponding to a timestamp of the first millisecond of the first
day of the week containing date.
The weekname() function determines which week the date falls into and returns the week number and year of that week. The first day of the week is determined by the FirstWeekDay system variable. However, you can also change the first day of the week by using the first_week_day argument in the weekname() function.
In Qlik Sense, the regional settings are fetched when the app is created, and the corresponding settings are stored in the script as environment variables.
A North American app developer often gets Set BrokenWeeks=1; in the script, corresponding to broken weeks. A European app developer often gets Set BrokenWeeks=0; in the script, corresponding to unbroken weeks.
If your application uses broken weeks, the week number count begins on the January 1 and ends on the day prior to the FirstWeekDay system variable regardless of how many days have occurred.
However, if your application is using unbroken weeks, week 1 can begin in the previous year or in the first few days in January. This depends on how you use the ReferenceDay and FirstWeekDay system variables.
Example of Weekname function
Date
ISO week name
US week name
Sat 2020 Dec 26
2020/52
2020/52
Sun 2020 Dec 27
2020/52
2020/53
Mon 2020 Dec 28
2020/53
2020/53
Tue 2020 Dec 29
2020/53
2020/53
Wed 2020 Dec 30
2020/53
2020/53
Thu 2020 Dec 31
2020/53
2020/53
Fri 2021 Jan 1
2020/53
2021/01
Sat 2021 Jan 2
2020/53
2021/01
Sun 2021 Jan 3
2020/53
2021/02
Mon 2021 Jan 4
2021/01
2021/02
Tue 2021 Jan 5
2021/01
2021/02
When to use it
The weekname() function is useful for when you would like to compare aggregations by weeks.
For example, if you want to see the total sales of products by week. To maintain consistency with the BrokenWeeks environment variable in the application, use weekname() instead of lunarweekname(). If the application is using unbroken weeks, week 1 may contain dates from December of the previous year or exclude dates in January of the current year. If the application is using broken weeks, week 1 may contain less than seven days.
Return data type: dual
Arguments
Argument
Description
timestamp
The date or timestamp to evaluate.
period_no
shift is an integer, where the value
0 indicates the week which contains date.
Negative values in shift indicate preceding weeks and positive values
indicate succeeding weeks.
first_week_day
Specifies the day on which the week starts. If omitted, the value of variable FirstWeekDay is used.
The possible values first_week_day are 0 for Monday, 1 for Tuesday, 2 for Wednesday, 3 for Thursday, 4 for Friday, 5 for Saturday, and 6 for Sunday.
For more information about the system variable, see FirstWeekDay.
broken_weeks
If you don't specify broken_weeks, the value of variable BrokenWeeks will be used to define if weeks are broken or not.
For more information about the system variable, see
BrokenWeeks
reference_day
If you don't specify reference_day, the value of variable ReferenceDay will be used to define which day in January to set as reference day to define week 1. By default, Qlik Sense functions use 4 as the reference day. This means that week 1 must contain January 4, or put differently, that week 1 must always have at least 4 days in January.
For more information about the system variable, see
ReferenceDay
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. For more information, see Modifying regional settings for apps and scripts.
Default regional settings in apps are based on the user profile. These regional format settings are not related to the language displayed in the Qlik Cloud user interface. Qlik Cloud will be displayed in the same language as the browser you are using.
The weekday() function which is set as the field ‘week_number’, that returns the year and week number when the transactions took place.
The weekname() function which is set as the field called ‘week_day’, to show the weekday value of each transaction date.
Load script
SET BrokenWeeks=1;
SET DateFormat='MM/DD/YYYY';
SET FirstWeekDay=6;
Transactions:
Load
*,
WeekDay(date) as week_day,
Weekname(date) as week_number
;
Load
*
Inline
[
id,date,amount
8183,12/27/2021,58.27
8184,12/28/2021,67.42
8185,12/29/2021,23.80
8186,12/30/2021,82.06
8187,12/31/2021,40.56
8188,01/01/2022,37.23
8189,01/02/2022,17.17
8190,01/03/2022,88.27
8191,01/04/2022,57.42
8192,01/05/2022,53.80
8193,01/06/2022,82.06
8194,01/07/2022,40.56
8195,01/08/2022,53.67
8196,01/09/2022,26.63
8197,01/10/2022,72.48
8198,01/11/2022,18.37
8199,01/12/2022,45.26
8200,01/13/2022,58.23
8201,01/14/2022,18.52
];
Results
Load the data and open a sheet. Create a new table and add these fields as dimensions:
id
date
week_day
week_number
Results table
id
date
week_day
week_number
8183
12/27/2021
Mon
2021/53
8184
12/28/2021
Tue
2021/53
8185
12/29/2021
Wed
2021/53
8186
12/30/2021
Thu
2021/53
8187
12/31/2021
Fri
2021/53
8188
01/01/2022
Sat
2022/01
8189
01/02/2022
Sun
2022/02
8190
01/03/2022
Mon
2022/02
8191
01/04/2022
Tue
2022/02
8192
01/05/2022
Wed
2022/02
8193
01/06/2022
Thu
2022/02
8194
01/07/2022
Fri
2022/02
8195
01/08/2022
Sat
2022/02
8196
01/09/2022
Sun
2022/03
8197
01/10/2022
Mon
2022/03
8198
01/11/2022
Tue
2022/03
8199
01/12/2022
Wed
2022/03
8200
01/13/2022
Thu
2022/03
8201
01/14/2022
Fri
2022/03
The ‘week_number’ field is created in the preceding load statement by using the weekname() function and passing the date field as the function’s argument.
The weekname() function initially identifies which week the date value falls into and returns the week number count and the year the transaction takes place.
The FirstWeekDay system variable sets Sunday as the first day of the week. The BrokenWeeks system variable sets the application to use broken weeks, meaning that week 1 will begin on January 1.
Week 1 begins on January 1, which is a Saturday, and therefore transactions occurring on this date return the value 2022/01 (the year and week number).
Because the application is using broken weeks and the first weekday is Sunday, transactions occurring from January 2 to January 8 return the value 2022/02 (week number 2 in 2022.) An example of this would be transaction 8192 which took place on January 5 and returns the value 2022/02 for the ‘week_number’ field.
Example 2 – period_no
Overview
The same dataset and scenario as the first example are used.
However, in this example, the task is to create a field, ‘previous_week_number’, that returns the year, and week number, prior to when the transactions took place.
Open the Data load editor and add the following load script to a new tab.
Load the data and open a sheet. Create a new table and add these fields as dimensions:
id
date
week_day
week_number
Results table
id
date
week_day
week_number
8183
12/27/2021
Mon
2021/52
8184
12/28/2021
Tue
2021/52
8185
12/29/2021
Wed
2021/52
8186
12/30/2021
Thu
2021/52
8187
12/31/2021
Fri
2021/52
8188
01/01/2022
Sat
2021/52
8189
01/02/2022
Sun
2021/53
8190
01/03/2022
Mon
2021/53
8191
01/04/2022
Tue
2021/53
8192
01/05/2022
Wed
2021/53
8193
01/06/2022
Thu
2021/53
8194
01/07/2022
Fri
2021/53
8195
01/08/2022
Sat
2022/01
8196
01/09/2022
Sun
2022/02
8197
01/10/2022
Mon
2022/02
8198
01/11/2022
Tue
2022/02
8199
01/12/2022
Wed
2022/02
8200
01/13/2022
Thu
2022/02
8201
01/14/2022
Fri
2022/02
Because a period_no of -1 is used as the offset argument in the weekname() function, the function first identifies the week that the transactions take place in. It then looks one week prior and identifies the first millisecond of that week.
Transaction 8192 took place on January 5, 2022. The weekname() function looks one week prior, December 30, 2021, and returns the week number and year for that date – 2021/53.
Example 3 – first_week_day
Overview
The same dataset and scenario as the first example are used.
However, in this example, the company policy is for the work week to begin on Tuesday.
Open the Data load editor and add the following load script to a new tab.
Load script
SET BrokenWeeks=1;
SET DateFormat='MM/DD/YYYY';
Transactions:
Load
*,
weekday(date) as week_day,
weekname(date,0,1) as week_number
;
Load
*
Inline
[
id,date,amount
8183,12/27/2021,58.27
8184,12/28/2021,67.42
8185,12/29/2021,23.80
8186,12/30/2021,82.06
8187,12/31/2021,40.56
8188,01/01/2022,37.23
8189,01/02/2022,17.17
8190,01/03/2022,88.27
8191,01/04/2022,57.42
8192,01/05/2022,53.80
8193,01/06/2022,82.06
8194,01/07/2022,40.56
8195,01/08/2022,53.67
8196,01/09/2022,26.63
8197,01/10/2022,72.48
8198,01/11/2022,18.37
8199,01/12/2022,45.26
8200,01/13/2022,58.23
8201,01/14/2022,18.52
];
Results
Load the data and open a sheet. Create a new table and add these fields as dimensions:
id
date
week_day
week_number
Results table
id
date
week_day
week_number
8183
12/27/2021
Mon
2021/52
8184
12/28/2021
Tue
2021/53
8185
12/29/2021
Wed
2021/53
8186
12/30/2021
Thu
2021/53
8187
12/31/2021
Fri
2021/53
8188
01/01/2022
Sat
2022/01
8189
01/02/2022
Sun
2022/01
8190
01/03/2022
Mon
2022/01
8191
01/04/2022
Tue
2022/02
8192
01/05/2022
Wed
2022/02
8193
01/06/2022
Thu
2022/02
8194
01/07/2022
Fri
2022/02
8195
01/08/2022
Sat
2022/02
8196
01/09/2022
Sun
2022/02
8197
01/10/2022
Mon
2022/02
8198
01/11/2022
Tue
2022/03
8199
01/12/2022
Wed
2022/03
8200
01/13/2022
Thu
2022/03
8201
01/14/2022
Fri
2022/03
Because the first_week_date argument of 1 is used in the weekname() function, it uses Tuesday as the first day of the week. The function therefore determines that week 53 of 2021 begins on Tuesday December 28; and, due to the application using broken weeks, week 1 begins on January 1, 2022, and ends on the last millisecond of Monday January 3, 2022.
Transaction 8192 took place on January 5, 2022. Therefore, using a first_week_day parameter of Tuesday, the weekname() function returns the value 2022/02 for the ‘week_number’ field.
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. The calculation that returns the year number of the week for when the transactions took place is created as a measure in a chart object of the application.
Load the data and open a sheet. Create a new table and add these fields as dimensions:
id
date
=week_day (date)
To calculate the start of the week that a transaction takes place in, create the following measure:
=weekname(date)
Results table
id
date
=weekday(date)
=weekname(date)
8183
12/27/2021
Mon
2021/53
8184
12/28/2021
Tue
2021/53
8185
12/29/2021
Wed
2021/53
8186
12/30/2021
Thu
2021/53
8187
12/31/2021
Fri
2021/53
8188
01/01/2022
Sat
2022/01
8189
01/02/2022
Sun
2022/02
8190
01/03/2022
Mon
2022/02
8191
01/04/2022
Tue
2022/02
8192
01/05/2022
Wed
2022/02
8193
01/06/2022
Thu
2022/02
8194
01/07/2022
Fri
2022/02
8195
01/08/2022
Sat
2022/02
8196
01/09/2022
Sun
2022/03
8197
01/10/2022
Mon
2022/03
8198
01/11/2022
Tue
2022/03
8199
01/12/2022
Wed
2022/03
8200
01/13/2022
Thu
2022/03
8201
01/14/2022
Fri
2022/03
The ‘week_number’ field is created as a measure in the chart object by using the weekname() function and passing the date field as the function’s argument.
The weekname() function initially identifies which week the date value falls into and returns the week number count and the year that the transaction takes place.
The FirstWeekDay system variable sets Sunday as the first day of the week. The BrokenWeeks system variable sets the application to use broken weeks, meaning that week 1 begins on January 1.
Because the application is using broken weeks and the first weekday is Sunday, transactions occurring from January 2 to January 8 return the value 2022/02, week number 2 in 2022. Note that transaction 8192 took place on January 5 and returns the value 2022/02 for the ‘week_number’ field.
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 containing a set of transactions for the last week of 2019 and first two weeks of 2020 is loaded into a table called ‘Transactions’.
The BrokenWeeks system variable which is set to 0.
The ReferenceDay system variable which is set to 2.
The DateFormat system variable which is set to the MM/DD/YYYY format.
Load the data and open a sheet. Create a new table.
Create a calculated dimension using the following expression:
=weekname(date)
To calculate total sales create the following aggregation measure:
=sum(amount)
Set the measure’s Number Formatting to Money.
Results table
weekname(date)
=sum(amount)
2019/52
$125.69
2020/01
$346.51
2020/02
$347.57
2020/03
$122.01
To demonstrate the results of using the weekname() function in this scenario, add the following field as a dimension:
date
Results table with date field
weekname(date)
date
=sum(amount)
2019/52
12/27/2019
$58.27
2019/52
12/28/2019
$67.42
2020/01
12/29/2019
$23.80
2020/01
12/30/2019
$82.06
2020/01
12/31/2019
$40.56
2020/01
01/01/2020
$37.23
2020/01
01/02/2020
$17.17
2020/01
01/03/2020
$88.27
2020/01
01/04/2020
$57.42
2020/02
01/05/2020
$53.80
2020/02
01/06/2020
$82.06
2020/02
01/07/2020
$40.56
2020/02
01/08/2020
$53.67
2020/02
01/09/2020
$26.63
2020/02
01/10/2020
$72.48
2020/02
01/11/2020
$18.37
2020/03
01/12/2020
$45.26
2020/03
01/13/2020
$58.23
2020/03
01/14/2020
$18.52
Because the application uses unbroken weeks, and week 1 requires a minimum of two days in January because of the ReferenceDay system variable, week 1 of 2020 includes transactions from December 29, 2019.
Variable
A variable in Qlik Sense is a container storing a static value or a calculation, for example a numeric or alphanumeric value.
A Qlik Sense or QlikView app: Apps are task-specific, purpose-built applications. Apps contain data loaded from data sources that is interpreted through visualizations.
The Qlik Sense Mobile app: A mobile app for iOS and Android devices. In the mobile app, you connect to and interact with your cloud data. You can work with your available apps.
The term dataset is sometimes synonymous with table. It can refer to the original source table, the table after undergoing transformations, or the fact and dimension tables in a data mart.
It can also refer to a logical table, where there are several instance tables and views:
Current data
History, which holds previous versions of the table
A preceding load is a script construct that allows you to load from the following LOAD or SELECT statement without specifying that source. Preceding loads are often faster than resident loads.
A field contains values, loaded from a data source. At a basic level, a field corresponds to a column in a table. Fields are used to create dimensions and measures in visualizations.
A measure is a calculation base on one ore more aggregations. For example, the sum of sales is a single aggregation, while the sum of sales divided by the count of customers is a measure based on two aggregations.
Sheets are components of Qlik Sense apps. They present visualizations to app users so they can explore, analyze, and discover data. Sheets can be public or private.
A dimension is an entity used to categorize data in a chart. For example, the slices in a pie chart or the bars of a bar chart represent individual values in a dimension. Dimensions are often a single field with discrete values, but can also be calculated in an expression.
A dimension is a dataset in a data mart that forms part of the star schema. Dimension datasets hold the descriptive information for all related fields that are included in the fact table’s records. A few common examples of dimension datasets are Customer and Product. Since the data in a dimension dataset is often denormalized, dimension datasets have a large number of columns.
An aggregation is a calculation using multiple records in the source tables. Often it is a single field aggregated with a function such as sum, count, min, max, or average. For example, the sum of sales.