> For the complete documentation index, see [llms.txt](https://docs.cloudfabrix.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.cloudfabrix.io/rda/rda-userguide/rda-aiops-studio/examples-jupyter/data-mapping-cfxdm-dm-to_type.md).

# Data Mapping cfxdm - dm:to\_type

**dm:to\_type:** It allows to change or set the data type to string or integer (numeric) or float for specified columns. 

@param '**columns**' (mandatory, comma separated list of column names), @param '**type**' (mandatory, supported options are: str / int / float)

**dm:to\_type:** Syntax

* **columns** (mandatory)**:** Comma-separated list of column names
* **type** (mandatory)**:** Supported options are: **str** (string or text) / **int** (integer or numeric) / **float**

### Example 1:

Step 1: Create an empty **dm\_to\_type\_example\_1** using AIOps studio as shown in the below screenshot

![Empty pipeline](/files/-Mg7cLjdud1l92kL-yHT)

*`##### This pipeline creates a set of records/dateset details with different datatypes`*\
*`##### String and integer.`*\
\
*`######  This pipeline uses dm to_type to convert basic string data type to int datatype`*\
\
~~*`--> @dm:empty`*~~ \
~~*`--> @dm:addrow id = 'a1' & x = '10.0' & y = '3.11' & z = 9`*~~                                \
~~*`--> @dm:addrow id = 'a2' & x = '1.0' & y = '13.0'  & z = 4`*~~ \
~~*`--> @dm:addrow id = 'a3' & x = '7.0' & y = '3.0'   & z = 3`*~~ \
~~*`--> @dm:addrow id = 'a4' & x = '4.0' & y = '-1.4'  & z = 9`*~~\
&#x20;~~*`--> @dm:to_type columns ='x,y' & type = 'int'`*~~<br>

![Pipeline code added to above created empty pipeline](/files/-Mg7eyUXjK_Qc-8qGHoL)

Step &#x33;**:** Click verify button to verify the pipeline. RDA will verify the pipeline without any errors (as shown below)

![Pipeline code verified ](/files/-Mg7fSEHnOf_t581WXNC)

Step &#x34;**:** Click execute button to execute the pipeline. RDA will execute the pipeline without any errors (as shown below)

![Pipeline execution without any errors](/files/-Mg7fs75-TQyKWKhWHED)

Step 5: Verify that the output data is enriched with the requested column names and print the output as shown in the below screenshot.

![](/files/-Mg7gO7s5WU3zv7b7OKa)

As shown in the above pipeline, this function is used to convert string to int (or float) datatype needed for any integer manipulation, etc.