# MoneyThousandSep

The thousands separator defined replaces the digit grouping symbol for currency set by your regional settings.

Tip note

By default, Qlik Sense displays numbers and text differently in table charts. Numbers are right-aligned, and text is left-aligned. This makes it easy to find text-to-number conversion issues. Any tables on this page that show Qlik Sense results will use this formatting.

Syntax:

MoneyThousandSep

Qlik Sense applications will interpret text fields that conform to this formatting as monetary values. The text field must contain the currency symbol that is defined in the `MoneyFormat` system variable. `MoneyThousandSep` is particularly helpful when handling data sources received from multiple different regional settings.

The following example shows a possible use of the `MoneyThousandSep` system variable:

`Set MoneyDecimalSep=',';`

This function is often used together with the following functions:

Related functions

| Function | Interaction |
| --- | --- |
| `MoneyFormat` | In instances of text field interpretation, the `MoneyFormat` symbol will be used as part of the interpretation.<br>For Number Formatting, the `MoneyFormat` formatting will be used by Qlik Sense in chart objects. |
| `MoneyDecimalSep` | In instances of text field interpretation, the `MoneyDecimalSep` function must also be adhered to. |

## 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 - MoneyThousandSep comma (,) notation

[](https://help.qlik.com/en-US/sense/Subsystems/Hub/Content/Sense_Hub/Scripting/NumberInterpretationVariables/MoneyThousandSep.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:

* A dataset which is loaded into a table named `Transactions`.

* Provided data that has its monetary field in text format with a comma used as the thousands separator. Each record is also prefixed by a ‘$’ symbol.

Keep in mind that the `MoneyFormat` system variable defines dollar ‘$’ as the default currency.

Load script

```
SET MoneyThousandSep=',';
SET MoneyDecimalSep='.';
SET MoneyFormat='$###0.00;-$###0.00';

Transactions:
Load
date,
id,
amount
Inline 
[
date,id,amount
01/01/2022,1,'$10,000,000,441'
01/02/2022,2,'$21,237,492,432'
01/03/2022,3,'$249,475,336'
01/04/2022,4,'$24,313,369,837'
01/05/2022,5,'$7,873,578,754'
01/06/2022,6,'$24,313,884,663'
01/07/2022,7,'$545,883,436'
01/08/2022,8,'$35,545,828,255'
01/09/2022,9,'$37,565,817,436'
01/10/2022,10,'$3.454.343.566'
];
```

Results

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

Add the following measures:

* `isNum(amount)`

* `sum(amount)`

Review the results below. The table demonstrates the correct interpretation of all values using comma ‘,’ notation as the thousands separator.

The `amount` field has been interpreted correctly for all values, with the exception of one value which used a dot '.' as the thousands separator.

Results table

| amount | =isNum(amount) | =Sum(amount) |
| --- | --- | --- |
| Totals | 0 | $161645330590.00 |
| $3.454.343.566 | 0 | $0.00 |
| $249,475,336 | -1 | $249475336.00 |
| $545,883,436 | -1 | $545883436.00 |
| $7,873,578,754 | -1 | $7873578754.00 |
| $10,000,000,441 | -1 | $10000000441.00 |
| $21,237,492,432 | -1 | $21237492432.00 |
| $24,313,369,837 | -1 | $24313369837.00 |
| $24,33,884,663 | -1 | $24313884663.00 |
| $35,545,828,255 | -1 | $35545828255.00 |
| $37,565,817,436 | -1 | $37565817436.00 |

## Example 2 - MoneyThousandSep dot (.) notation

[](https://help.qlik.com/en-US/sense/Subsystems/Hub/Content/Sense_Hub/Scripting/NumberInterpretationVariables/MoneyThousandSep.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:

* A dataset which is loaded into a table named `Transactions`.

* Provided data that has its monetary field in text format with a dot '.' used as the thousands separator. Each record is also prefixed by a ‘$’ symbol.

Keep in mind that the `MoneyFormat` system variable defines dollar ‘$’ as the default currency.

Load script

```
SET MoneyThousandSep='.';
SET MoneyDecimalSep=',';
SET MoneyFormat='$###0.00;-$###0.00';

Transactions:
Load
date,
id,
amount
Inline 
[
date,id,amount
01/01/2022,1,'$10.000.000.441'
01/02/2022,2,'$21.237.492.432'
01/03/2022,3,'$249.475.336'
01/04/2022,4,'$24.313.369.837'
01/05/2022,5,'$7.873.578.754'
01/06/2022,6,'$24.313.884.663'
01/07/2022,7,'$545.883.436'
01/08/2022,8,'$35.545.828.255'
01/09/2022,9,'$37.565.817.436'
01/10/2022,10,'$3,454,343,566'
];
```

Results

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

Add the following measures:

* `isNum(amount)`

* `sum(amount)`

Review the results below, demonstrating the correct interpretation of all values using dot ‘.’ notation as the thousand separator.

The `amount` field has been interpreted correctly for all values, with the exception of one value which used a comma ',' as the thousands separator.

Results table

| amount | =isNum(amount) | =Sum(amount) |
| --- | --- | --- |
| Totals | 0 | $161645330590.00 |
| $3,545,343,566 | 0 | $0.00 |
| $249.475.336 | -1 | $249475336.00 |
| $545.883.436 | -1 | 545883436.00 |
| $7.873.578.754 | -1 | $7873578754.00 |
| $10.000.000.441 | -1 | $10000000441.00 |
| $21.237.492.432 | -1 | $21237492432.00 |
| $24.313.884.663 | -1 | $24313884663.00 |
| $24.313.884.663 | -1 | $24313884663.00 |
| $35.545.828.255 | -1 | $35545828255.00 |
| $37.565.817.436 | -1 | $37565817436.00 |