Last Updated: May 10, 2022
The data in the CSV Dataset can be cleansed or transformed as needed to use in the automation process. The following transformations can be done to make the data more usable:
You can manipulate the existing columns in the CSV Dataset to clean-up the data.
icon and select the Dataset Schema option.
.png)
icon to edit the schema.
The data type of the columns can be changed based on the user requirement.
Nullable, Hide,
, and
options are available against each column.
.png)
Click the
icon, the below options appear.
.png)
You can create a derived column to the left or right of the existing column using either option Add Expression Above or Add Expression Below to transform the column data using an expression.
Create a new column Discount using expression Fare - FinalFare.
.png)
Create a new column FinalFare with a discounted fare calculated based on the condition,
If the value in the existing column Fare is greater than 80000 then 20% discount is applied. Else 10% discount is applied.
.png)
icon to apply the conditions.
To provide column name as input, enter the column name as is.
To provide input as a string, give the text in single quotes.
You can transform the data in a column by performing various operations on the column data using the inbuilt expressions.
Click the
icon to perform operations on the selected column.
icon and select Insert Above and Insert Below options..png)
The following are the available categories of expressions:
In addition, you can also write your own expression as desired using the Expression option shown below.
To refresh the dataset after applying the changes, click the
icon.
To reload the dataset, click the
icon and select the Reload Dataset option.
.png)
After the applied changes are verified, click the
icon to publish the Dataset. The published data can now be further accessed in the automation tasks.
.png)