# inlunarweektodate Script and chart function
This function finds if timestamp lies inside the part of the lunar week up to and including the last millisecond of base\_date. Lunar weeks in Qlik Sense are defined by counting January 1 as the first day of the week and, apart from the final week of the year, will contain exactly seven days.
Syntax:
InLunarWeekToDate (timestamp, base\_date, period\_no [, first\_week\_day])
Return data type: Boolean
Information note
In Qlik Sense, the Boolean true value is represented by -1, and the false value is represented by 0.
Example diagram of `inlunarweektodate()` function
Example diagram of `inlunarweektodate()` function
Example diagram of `inlunarweektodate()`inlunarweektodate() function 
The `inlunarweektodate()` function acts as the end point of the lunar week. In contrast, the `inlunarweek()` function, determines which lunar week the `base_date` falls into. For example, if the `base_date` were January 5, any timestamp between January 1 and January 5 would return a Boolean result of `TRUE`, while dates on January 6 and 7, and later, would return a Boolean result of `FALSE`.
Arguments
| Argument | Description |
| --- | --- |
| timestamp | The date that you want to compare with base\_date. |
| base\_date | Date that is used to evaluate the lunar week. |
| period\_no | The lunar
week can be offset by period\_no.
period\_no is an integer, where the
value 0 indicates the lunar week which contains base\_date.
Negative values in period\_no indicate
preceding lunar weeks and positive values indicate succeeding lunar weeks. |
| first\_week\_day | An offset that may be greater than or less than zero. This changes the beginning of the year by the specified number of days and/or fractions of
a day. |
## When to use inlunarweektodate
The `inlunarweektodate()` function returns a Boolean result. Typically, this type of function will be used as a condition in an IF expression. The `inlunarweektodate()` function would be used when the user would like the calculation to return an aggregation or calculation, dependent on whether the evaluated date occurred during a particular segment of the week in question.
For example, the `inlunarweektodate()` function can be used to identify all equipment manufactured in a particular week up to and including a particular date.
Function examples
| Example | Result |
| --- | --- |
| `inlunarweektodate('01/12/2013', '01/13/2013',
0)` | Returns `TRUE`, since the value of the `timestamp`, 01/12/2013, falls in the part of the week 01/08/2013 to 01/13/2013. |
| `inlunarweektodate('01/12/2013', '01/11/2013',
0)` | Returns `FALSE`, since the value of the `timestamp` is later than the value of `base_date`, even though the two dates are in the same lunar week before 01/12/2012. |
| `inlunarweektodate('01/12/2006', '01/05/2006',
1)` | Returns `TRUE`. Specifying a value of 1 for `period_no` shifts the `base_date` forward one week, so the value of `timestamp` falls in the part of the lunar week. |
The `inlunarweektodate()` function is often used in combination with the following functions:
Related functions
| Function | Interaction |
| --- | --- |
| [lunarweekname Script and chart function](https://help.qlik.com/en-US/cloud-services/Subsystems/Hub/Content/Sense_Hub/Scripting/DateAndTimeFunctions/lunarweekname.htm) | This function is used to determine the lunar week number of the year in which an input date occurs. |
## 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 applications and scripts](https://help.qlik.com/en-US/cloud-services/Subsystems/Hub/Content/Sense_Hub/Apps/regional-settings-in-apps.htm).
Default regional settings in applications 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.
If you are an application creator, you can set the default region for applications you create. For more information, see [Setting your preferred regional settings for creating apps and scripts in Qlik Cloud Analytics](https://help.qlik.com/en-US/cloud-services/Subsystems/Hub/Content/Sense_Hub/UserInterface/Languages.htm#Setting).
## Example 1 - No additional arguments
#### Load script and results
Overview
Open the Data load editor and add the load script below to a new section.
The load script contains:
* A dataset containing a set of transactions for the month of January, which is loaded into a table called `Transactions`. The default `DateFormat` system variable MM/DD/YYYY is used.
* Create a field `in_lunar_week_to_date`, that determines which transactions took place in lunar week to date of January 10.
Load script
```
SET DateFormat='MM/DD/YYYY';
Transactions:
Load
*,
inlunarweektodate(date,'01/10/2022', 0) as in_lunar_week_to_date
;
Load
*
Inline
[
id,date,amount
8188,'1/10/2022',37.23
8189,'1/17/2022',17.17
8190,'1/26/2022',88.27
8191,'1/12/2022',57.42
8192,'1/19/2022',53.80
8193,'1/21/2022',82.06
8194,'1/1/2022',40.39
8195,'1/27/2022',87.21
8196,'1/11/2022',95.93
8197,'1/29/2022',45.89
8198,'1/31/2022',36.23
8199,'1/18/2022',25.66
8200,'1/23/2022',82.77
8201,'1/15/2022',69.98
8202,'1/4/2022',76.11
];
```
Results
Load the data and open a sheet. Create a new table and add these fields as dimensions:
* `date`
* `in_lunar_week_to_date`
Results table
| date | in\_lunar\_week\_to\_date |
| --- | --- |
| 1/1/2022 | 0 |
| 1/4/2022 | 0 |
| 1/10/2022 | -1 |
| 1/11/2022 | 0 |
| 1/12/2022 | 0 |
| 1/15/2022 | 0 |
| 1/17/2022 | 0 |
| 1/18/2022 | 0 |
| 1/19/2022 | 0 |
| 1/21/2022 | 0 |
| 1/23/2022 | 0 |
| 1/26/2022 | 0 |
| 1/27/2022 | 0 |
| 1/29/2022 | 0 |
| 1/31/2022 | 0 |
`inlunarweektodate()` function, no additional arguments
`inlunarweektodate()` function, no additional arguments
`inlunarweektodate()`inlunarweektodate() function, no additional arguments 
The `in_lunar_week_to_date` field is created in the preceding load statement by using the `inlunarweektodate()` function and passing the `date` field, a hard-coded date for January 10 as our `base_date`, and an offset of 0 as the function’s arguments.
Because lunar weeks begin on January 1, January 10 would fall in the lunar week that begins on January 8; and because we are using the `inlunarweektodate()` function, that lunar week would then end on the 10th. Therefore, any transactions that occur between those two dates in January would return a Boolean value of `TRUE`. This is validated in the results table.
## Example 2 - period\_no
[](https://help.qlik.com/en-US/cloud-services/Subsystems/Hub/Content/Sense_Hub/Scripting/DateAndTimeFunctions/inlunarweektodate.htm)
#### Load script and results
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 task is to create a field, `2_lunar_weeks_later`, that determines whether or not the transactions took place two weeks after the lunar week to date of January 1.
Load script
```
SET DateFormat='MM/DD/YYYY';
Transactions:
Load
*,
inlunarweektodate(date,'01/10/2022', 2) as [2_lunar_weeks_later]
;
Load
*
Inline
[
id,date,amount
8188,'1/10/2022',37.23
8189,'1/17/2022',17.17
8190,'1/26/2022',88.27
8191,'1/12/2022',57.42
8192,'1/19/2022',53.80
8193,'1/21/2022',82.06
8194,'1/1/2022',40.39
8195,'1/27/2022',87.21
8196,'1/11/2022',95.93
8197,'1/29/2022',45.89
8198,'1/31/2022',36.23
8199,'1/18/2022',25.66
8200,'1/23/2022',82.77
8201,'1/15/2022',69.98
8202,'1/4/2022',76.11
];
```
Results
Load the data and open a sheet. Create a new table and add these fields as dimensions:
* `date`
* `2_lunar_weeks_later`
Results table
| date | 2\_lunar\_weeks\_later |
| --- | --- |
| 1/1/2022 | 0 |
| 1/4/2022 | 0 |
| 1/10/2022 | 0 |
| 1/11/2022 | 0 |
| 1/12/2022 | 0 |
| 1/15/2022 | 0 |
| 1/17/2022 | 0 |
| 1/18/2022 | 0 |
| 1/19/2022 | 0 |
| 1/21/2022 | 0 |
| 1/23/2022 | -1 |
| 1/26/2022 | 0 |
| 1/27/2022 | 0 |
| 1/29/2022 | 0 |
| 1/31/2022 | 0 |
`inlunarweektodate()` function, period\_no example
`inlunarweektodate()` function, period\_no example
`inlunarweektodate()`inlunarweektodate() function, period\_no example 
In this instance, the `inlunarweektodate()` function determines that the lunar week up to January 10 equates to three days (January 8, 9, 10). Since a `period_no` of 2 was used as the offset argument, this lunar week is shifted by 14 days. Therefore, this defines that three-day lunar week to include January 22, 23, and 24. Any transaction that takes place between January 22 and January 24 will return a Boolean result of `TRUE`.
## Example 3 - first\_week\_day
[](https://help.qlik.com/en-US/cloud-services/Subsystems/Hub/Content/Sense_Hub/Scripting/DateAndTimeFunctions/inlunarweektodate.htm)
#### Load script and results
Overview
Open the Data load editor and add the load script below to a new section.
The load script contains:
* The same dataset and scenario as the first example.
* The default `DateFormat` system variable MM/DD/YYYY is used.
* A `first_week_date` argument of 3. This sets lunar weeks to begin on January 3.
Load script
```
SET DateFormat='MM/DD/YYYY';
Transactions:
Load
*,
inlunarweek(date,'01/10/2022', 0,3) as in_lunar_week_to_date
;
Load
*
Inline
[
id,date,amount
8188,'1/10/2022',37.23
8189,'1/17/2022',17.17
8190,'1/26/2022',88.27
8191,'1/12/2022',57.42
8192,'1/19/2022',53.80
8193,'1/21/2022',82.06
8194,'1/1/2022',40.39
8195,'1/27/2022',87.21
8196,'1/11/2022',95.93
8197,'1/29/2022',45.89
8198,'1/31/2022',36.23
8199,'1/18/2022',25.66
8200,'1/23/2022',82.77
8201,'1/15/2022',69.98
8202,'1/4/2022',76.11
];
```
Results
Load the data and open a sheet. Create a new table and add these fields as dimensions:
* `date`
* `in_lunar_week_to_date`
Results table
| date | in\_lunar\_week\_to\_date |
| --- | --- |
| 1/1/2022 | 0 |
| 1/4/2022 | -1 |
| 1/10/2022 | -1 |
| 1/11/2022 | 0 |
| 1/12/2022 | 0 |
| 1/15/2022 | 0 |
| 1/17/2022 | 0 |
| 1/18/2022 | 0 |
| 1/19/2022 | 0 |
| 1/21/2022 | 0 |
| 1/23/2022 | 0 |
| 1/26/2022 | 0 |
| 1/27/2022 | 0 |
| 1/29/2022 | 0 |
| 1/31/2022 | 0 |
`inlunarweektodate()` function, first\_week\_day example
`inlunarweektodate()` function, first\_week\_day example
`inlunarweektodate()`inlunarweektodate() function, first\_week\_day example 
In this instance, because `the first_week_date` argument of 3 is used in the `inlunarweek()` function, the first lunar week will be from January 3 to January 10. Because January 10 is also the `base_date`, any transaction that falls between these two dates will return a Boolean value of `TRUE`.
## Example 4 - Chart object example
#### Load script and chart expression
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 whether the transactions took place in the lunar week up to January 10 is created as a measure in a chart object of the application.
Load script
```
SET DateFormat='MM/DD/YYYY';
Transactions:
Load
*
Inline
[
id,date,amount
8188,'1/10/2022',37.23
8189,'1/17/2022',17.17
8190,'1/26/2022',88.27
8191,'1/12/2022',57.42
8192,'1/19/2022',53.80
8193,'1/21/2022',82.06
8194,'1/1/2022',40.39
8195,'1/27/2022',87.21
8196,'1/11/2022',95.93
8197,'1/29/2022',45.89
8198,'1/31/2022',36.23
8199,'1/18/2022',25.66
8200,'1/23/2022',82.77
8201,'1/15/2022',69.98
8202,'1/4/2022',76.11
];
```
Results
Load the data and open a sheet. Create a new table and add this field as a dimension: date.
Create the following measure:
=inlunarweektodate(date,'01/10/2022', 0)
Results table
| date | =inlunarweektodate(date,'01/10/2022', 0) |
| --- | --- |
| 1/1/2022 | 0 |
| 1/4/2022 | 0 |
| 1/10/2022 | -1 |
| 1/11/2022 | 0 |
| 1/12/2022 | 0 |
| 1/15/2022 | 0 |
| 1/17/2022 | 0 |
| 1/18/2022 | 0 |
| 1/19/2022 | 0 |
| 1/21/2022 | 0 |
| 1/23/2022 | 0 |
| 1/26/2022 | 0 |
| 1/27/2022 | 0 |
| 1/29/2022 | 0 |
| 1/31/2022 | 0 |
inlunarweektodate() function, chart object example
inlunarweektodate() function, chart object example
inlunarweektodate()inlunarweektodate() function, chart object example 
The in\_lunar\_week\_to\_date measure is created in the chart object by using the inlunarweektodate() function and passing the date field, a hard-coded date for January 10 as our base\_date, and an offset of 0 as the function’s arguments.
Because lunar weeks begin on January 1, January 10 would fall in the lunar week that begins on January 8. Additionally, since we are using the inlunarweektodate() function, that lunar week would then terminate on the 10th. Therefore, any transactions that occur between those two dates in January would return a Boolean value of TRUE. This is validated in the results table.
## Example 5 - Scenario
#### Load script and chart expressions
Overview
Open the Data load editor and add the load script below to a new section.
The load script contains:
* A dataset which is loaded into a table called Products.
* Information consisting of product ID, manufacture date, and cost price.
It has been identified that due to equipment error, products that were manufactured in the lunar week of January 12 were defective. The issue was resolved on January 13. The end user would like a chart object that displays, by week, the status of whether the products manufactured ‘defective’ or ‘faultless’ and the cost of the products manufactured in that week.
Load script
```
SET TimestampFormat='M/D/YYYY h:mm:ss[.fff]';
Products:
Load
*
Inline
[
product_id,manufacture_date,cost_price
8188,'01/02/2022 12:22:06',37.23
8189,'01/05/2022 01:02:30',17.17
8190,'01/06/2022 15:36:20',88.27
8191,'01/08/2022 10:58:35',57.42
8192,'01/09/2022 08:53:32',53.80
8193,'01/10/2022 21:13:01',82.06
8194,'01/11/2022 00:57:13',40.39
8195,'01/12/2022 09:26:02',87.21
8196,'01/13/2022 15:05:09',95.93
8197,'01/14/2022 18:44:57',45.89
8198,'01/15/2022 06:10:46',36.23
8199,'01/16/2022 06:39:27',25.66
8200,'01/17/2022 10:44:16',82.77
8201,'01/18/2022 18:48:17',69.98
8202,'01/26/2022 04:36:03',76.11
8203,'01/27/2022 08:07:49',25.12
8204,'01/28/2022 12:24:29',46.23
8205,'01/30/2022 11:56:56',84.21
8206,'01/30/2022 14:40:19',96.24
8207,'01/31/2022 05:28:21',67.67
];
```
Results
Do the following:
1. Load the data and open a sheet. Create a new table.
2. Create a dimension to show the week names:
=weekname(manufacture\_date)
3. Next, create a dimension which uses the inlunarweektodate() function to identify which of the products are defective and which are faultless:
=if(inlunarweektodate(manufacture\_date,makedate(2022,01,12),0),'Defective','Faultless')
4. Create a measure to sum the cost\_price of the products:
=sum(cost\_price)
5. Set the measure's Number formatting to Money.
Results table
| =lunarweekname(manufacture\_date) | =if(InLunarWeekToDate(manufacture\_date,makedate(2022,01,12),0),'Defective','Faultless') | =Sum(cost\_price) |
| --- | --- | --- |
| 2022/01 | Faultless | $142.67 |
| 2022/02 | Defective | $320.88 |
| 2022/02 | Faultless | $141.82 |
| 2022/03 | Faultless | $214.64 |
| 2022/04 | Faultless | $147.46 |
| 2022/05 | Faultless | $248.12 |
The inlunarweektodate() 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 lunar week up to January 12, it marks the products as ‘Faultless’.