dayend - script and chart function

Overview

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

The load script contains:

• A dataset containing a list of dates is loaded into a table named "Calendar".

• The default DateFormat system variable (MM/DD/YYYY).

• A preceding load to create an additional field 'EOD_timestamp', using the dayend() function.

Load script

SET TimestampFormat='M/D/YYYY h:mm:ss[.fff] TT'; 

Calendar: 
    Load 
      date, 
      dayend(date) as EOD_timestamp 
      ; 
Load 
date 
Inline  
[ 
date 
03/11/2022 1:47:15 AM 
03/12/2022 4:34:58 AM 
03/13/2022 5:15:55 AM 
03/14/2022 9:25:14 AM 
03/15/2022 10:06:54 AM 
03/16/2022 10:44:42 AM 
03/17/2022 11:33:30 AM 
03/18/2022 12:58:14 PM 
03/19/2022 4:23:12 PM 
03/20/2022 6:42:15 PM 
03/21/2022 7:41:16 PM 
]; 

Results

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

• date

• EOD_timestamp

As you can see in the table above, the end of day timestamp is generated for each date in our dataset. The timestamp is in the format of the system variable TimestampFormat M/D/YYYY h:mm:ss[.fff] TT.

Overview

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

You will load a dataset containing service bookings into a table named 'Services'.

The dataset includes the following fields:

• service_id

• service_date

• amount

You will create two new fields in the table:

• deposit_due_date: The date when the deposit should be received. This is the end of the day three days before the service_date.

• final_payment_due_date: The date when the final payment should be received. This is the end of the day seven days after the service_date.

The two fields above are created in a preceding load using the dayend() function and they supply the first two parameters, time and period_no.

Load script

SET TimestampFormat='M/D/YYYY h:mm:ss[.fff] TT'; 
						
Services: 
   Load 
     *, 
     dayend(service_date,-3) as deposit_due_date, 
     dayend(service_date,7) as final_payment_due_date 
     ; 
Load 
service_id, 
service_date, 
amount 
Inline  
[ 
service_id, service_date,amount
1,03/11/2022 9:25:14 AM,231.24 
2,03/12/2022 10:06:54 AM,567.28 
3,03/13/2022 10:44:42 AM,364.28 
4,03/14/2022 11:33:30 AM,575.76 
5,03/15/2022 12:58:14 PM,638.68 
6,03/16/2022 4:23:12 PM,785.38 
7,03/17/2022 6:42:15 PM,967.46 
8,03/18/2022 7:41:16 PM,287.67 
9,03/19/2022 8:14:15 PM,764.45 
10,03/20/2022 9:23:51 PM,875.43 
11,03/21/2022 10:04:41 PM,957.35 
]; 

Results

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

• service_date

• deposit_due_date

• final_payment_due_date

The values of the new fields are in the TimestampFormat M/D/YYYY h:mm:ss[.fff] TT. Because the function dayend() was used, the timestamp values are all the last millisecond of the day.

The deposit due date values are three days before the service date because the second argument passed in the dayend() function is negative.

The final payment due date values are seven days after the service date because the second argument passed in the dayend() function is positive.

Overview

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

The dataset and scenario used in this example is the same as in the previous example.

As in the previous example, you will create two new fields:

• deposit_due_date: The date when the deposit should be received. This is the end of the day three days before the service_date.

• final_payment_due_date: The date when the final payment should be received. This is the end of the day seven days after the service_date.

However, your company would like to operate under a policy where the working day begins at 5 PM and ends at 5 PM the following day. Your company can then monitor transactions that occur in those working hours.

To achieve these requirements, the two fields above are created in a preceding load using the dayend() function and use all three arguments, time, period_no, and day_start.

Load Script

SET TimestampFormat='M/D/YYYY h:mm:ss[.fff] TT'; 

Services: 
   Load 
     *, 
     dayend(service_date,-3,17/24) as deposit_due_date, 
     dayend(service_date,7,17/24) as final_payment_due_date 
     ; 
Load 
service_id, 
service_date, 
amount 
Inline  
[ 
service_id, service_date,amount 
1,03/11/2022 9:25:14 AM,231.24 
2,03/12/2022 10:06:54 AM,567.28 
3,03/13/2022 10:44:42 AM,364.28 
4,03/14/2022 11:33:30 AM,575.76 
5,03/15/2022 12:58:14 PM,638.68 
6,03/16/2022 4:23:12 PM,785.38 
7,03/17/2022 6:42:15 PM,967.46 
8,03/18/2022 7:41:16 PM,287.67 
9,03/19/2022 8:14:15 PM,764.45 
10,03/20/2022 9:23:51 PM,875.43 
11,03/21/2022 10:04:41 PM,957.35 
]; 

Results

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

• service_date

• deposit_due_date

• final_payment_due_date

While the dates remain the same as in Example 2, the dates now have a timestamp of the last millisecond before 5:00 PM because the value of the third argument, day_start, passed into the dayend() function is 17/24.

Overview

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

The dataset and scenario used in this example is the same as in the previous two examples. The company would like to operate under a policy where the working day begins at 5:00 PM and ends at 5:00 PM the following day.

As in the previous example, you will create two new fields:

• deposit_due_date: The date when the deposit should be received. This is the end of the day three days before the service_date.

• final_payment_due_date: The date when the final payment should be received. This is the end of the day seven days after the service_date.

Load Script

SET TimestampFormat='M/D/YYYY h:mm:ss[.fff] TT'; 

Services: 
Load 
service_id, 
service_date, 
amount 
Inline  
[ 
service_id, service_date,amount 
1,03/11/2022 9:25:14 AM,231.24 
2,03/12/2022 10:06:54 AM,567.28 
3,03/13/2022 10:44:42 AM,364.28 
4,03/14/2022 11:33:30 AM,575.76 
5,03/15/2022 12:58:14 PM,638.68 
6,03/16/2022 4:23:12 PM,785.38 
7,03/17/2022 6:42:15 PM,967.46 
8,03/18/2022 7:41:16 PM,287.67 
9,03/19/2022 8:14:15 PM,764.45 
10,03/20/2022 9:23:51 PM,875.43 
11,03/21/2022 10:04:41 PM,957.35 
]; 

Results

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

service_date.

To create the deposit_due_date field, create this measure.

=dayend(service_date,-3,17/24).

Then, to create the final_payment_due_date field, create this measure:

=dayend(service_date,7,17/24).

The values of the new fields are in the TimestampFormat M/D/YYYY h:mm:ss[.fff] TT. Because the function dayend() was used, the timestamp values are all the last millisecond of the day.

The payment due date values are three days before the service date because the second argument passed in the dayend() function is negative.

The final payment due date values are seven days after the service date because the second argument passed in the dayend() function is positive.

The dates have a timestamp of the last millisecond before 5:00 PM because the value of the third argument, day_start,that passed into the dayend() function is 17/24.