Numbers
Last updated
Last updated
This transformation helps to compute the ceiling of a value, which is the smallest integer that is greater than the input value. Input can be an Integer or a Decimal.
Check out the illustration on the ceiling columns transform.
Steps to perform the Ceiling Columns transformation:
Navigate to the Data Preparation workspace.
Open the Transforms tab.
Click the Ceiling Columns transform from the Functions category.
The Ceiling Columns dialog box opens.
Select a column using the drop-down menu.
Click the Submit option.
As a result, the selected column data will be rounded with the ceiling values.
The Max transform gives the maximum value from the selected columns row-wise. The selected column should be numerical, and the given numbers should be more than one.
Check out the illustration on the Max transform.
Navigate to the Data Preparation workspace.
Open the Transforms tab.
Click the Max transform from the Numbers category.
The Max dialog box opens.
Select multiple columns using the checkboxes.
Click the Submit option after selecting the columns.
As a result, a new column displaying the Max values out of the selected columns will be added to the dataset.
This transform helps to get the row-wise average value from all the selected columns. The Mean transform supports only numerical columns.
Check out the illustration on the Mean transformation.
Steps to apply the Mean transform:
Navigate to the Data Preparation workspace.
Open the Transforms tab.
Click the Mean transform from the Numbers category.
The Mean dialog box opens.
Select multiple values using the checkboxes.
Click the Submit option after selecting the columns.
As a result, a new column gets added to the dataset with the mean values of the revenue column data:
This transform helps to get the row-wise minimum value from all the selected columns. The Min transform supports only numerical columns.
Check out the illustration on the Min transformation.
In the following example, the Min transform is applied to the North America, Europe, and Asia columns:
As a result, a new column gets added to the dataset with the minimum values out of the selected column data:
The Negate Data transform is a data transformation technique that involves changing the sign or flipping the values of a numerical variable. It is commonly used to reverse the polarity or direction of the data.
The process of applying the Negate Data transform is straightforward.
Multiplying each data point in the numerical variable by -1 effectively changes its sign.
This operation flips positive values to negative and negative values to positive, effectively reversing the polarity.
Check out the illustration on the Negate transform.
Steps to apply the Negate transform:
Navigate to the Data Preparation workspace.
Select a float or integer column from the dataset.
Open the Transforms tab.
Click the Nagate transform from the Numbers category.
The Negate dialog box opens.
Provide the following information to configure a new column with negate values.
Enable the Create a New Column option using the checkbox.
Provide the name of the newly added column.
Click the Submit option.
As a result, a new column gets added to the dataset with the negative values of the selected column data:
It converts the value of the selected column into words. The column must be of integer type.
The Number Name transformation, also known as numeral conversion or number-to-word conversion, is the process of converting a numerical value into its corresponding written representation.
Check out the illustration on how to use the Number Names transform.
Use with: Users can convert words into either Western or South Asian format.
The Number Names transform is applied to the slno column as displayed below (used with the Western option:
Navigate to the Data Preparation workspace.
Select a column from the dataset using the data grid.
Open the Transforms tab.
Click the Number Names transform from the Numbers category.
The Number Names dialog box opens.
Enable the Create new column option to create a new column with the transformed values.
Select a number names system from the below-given supported systems:
Western
South Asian
Click the Submit option.
As a result, a new column gets added to the dataset with the Number Names of the revenue column data:
The Remove Fractional Part data transform, truncation, or integer casting removes the decimal or fractional part of numerical values and keeps only the integer component. This transform effectively rounds down the values towards zero. The float column is converted into the integer data type.
The user can truncate or cast the numerical values to integers through the Remove Fractional Part transform. This operation discards the decimal portion of the value, resulting in an integer value.
Check out the illustration on the Remove Fractional Part transform.
Steps to apply the Remove Fractional Part transform:
Navigate to the Data Preparation workspace.
Select a column from the dataset.
Navigate to the Transforms tab.
Select the Remove Fractional Part transform from the Numbers category.
The Remove Fractional Part dialog box opens.
Create a new column through the following process:
Enable the Create a New Column
Provide a name for the newly created column.
Click the Submit option.
As a result, a new column gets added to the dataset after removing the fractional part from the selected column:
The Round Multiple Columns using Floor Mode transformation is a data manipulation technique that adjusts numeric values for multiple columns by rounding them down to the nearest whole number or specified decimal places.
Check out the illustration on the Round Multiple Columns Using Floor Mode transform.
Steps to apply the Round Multiple Columns using Floor Mode transform:
Navigate to the Data Preparation workspace.
Select a column from the dataset.
Navigate to the Transforms tab.
Select the Round Multiple Column using the Floor Mode transform from the Numbers category.
The Round Multiple Columns using the Floor Mode dialog box opens.
Select multiple columns using the drop-down menu.
Click the Submit option.
As a result, the round-off values of the selected columns will be modified with the floor mode:
When using the Ceil mode in data transformation, the round value operation is performed using the ceiling function. The ceiling function takes a number as input and returns the smallest integer greater than that number.
Let's say you have a dataset with numerical values, and you want to round those values up to the nearest whole number using the Ceil mode. Here's how the transformation works:
Take each numerical value in the dataset. Apply the ceiling function to that value. Replace the original value with the result of the ceiling function.
Check out the illustration on the Round Value Using Mode transform.
The Round value using ceil mode transform is applied to the Fare column,
Navigate to the Data Preparation workspace.
Select a column with the float values.
Open the Transforms tab.
Click the Round Value using the Ceil Mode transform from the Numbers transform category.
The Round Value using Ceil Mode dialog box opens.
Provide the following information to apply the transformation:
Enable the Create New column option to create a new column with the transform result.
Set Precision value
If you select 0 as Precision, the transform will show only full numbers. For example, if the selected precision value is 0 and the value in the original data set is 7.542, it will return 8 as the transformed value.
The Transform result will display the value up to the selected precision value. For example, if the selected precision value is 1 and the value in the original data set is 7.2434, it will return 7.3 as the transformed value.
Click the Submit option.
A new column gets added with the set round off value using ceil mode:
It rounds the number down to a specified digit or gives the specified number of decimals without any change in value. The transformed value can replace the existing column value or can be added as a new column.
Check out the illustration on the Round Value Using Mode transform.
Steps to apply the Round Value using Down Mode transform:
Navigate to the Data Preparation workspace.
Select a column with the float values.
Navigate to the Transforms tab.
Open the Round Value using Down Mode transform from the Numbers transform category.
The Round Value using Down Mode dialog box opens.
Provide the following information to apply the transformation:
Enable the Create New column if you wish to create a new column with the transform result.
Provide a name for the newly created column.
Set Precion value.
By selecting 0 as Precision, the transform will show only full numbers. For example, if the selected precision value is 0 and the value in the original data set is 7.542, it will return 7 as the transformed value.
If the selected precision value is 1 and the value in the original data set is 7.2434, it will return 7.2 as the transformed value.
Click the Submit option.
A new column gets added to the dataset with the round-off values using the down mode on the Mark column data:
The Round Value using Floor Mode transformation is a data manipulation technique that adjusts numeric values by rounding them down to the nearest whole number or specified decimal places.
Steps to use it
Input: The transformation requires a numerical input column or field that you want to round.
Floor Mode: The Floor function is used to round down the input value to the nearest whole number or specified decimal places. For example, if the input value is 4.8 and the floor mode is set to 0 decimal places, the transformed value would be 4. If the floor mode is set to 1 decimal place, the transformed value would be 4.8.
Output: The transformation generates a new column or modifies the existing column, replacing the original values with the rounded values based on the floor mode specified.
The Round Value using Floor Mode transformation is particularly useful when you want to convert decimal values into whole numbers or adjust the precision of numeric data according to specific requirements.
Check out the illustration on the Round Value using Floor Mode transform.
Steps to apply Round Value using Floor Mode transform:
Navigate to the Data Preparation workspace.
Select a number column from the dataset.
Navigate to the Transforms tab.
Select the Round Value using Floor Mode transform from the Numbers category.
The Round Value using Floor Mode dialog box appears.
Provide the following information to apply the transformation:
Enable the Create New column option to create a new column with the transformed result.
Provide a name for the newly created column.
Set the Precision value up to what decimal you wish to show the value.
Click the Submit option.
As a result, a new column gets added to the dataset with the round-off values of the Mark column data by using the floor mode:
The Round Value using the Half-up Mode transformation is a data manipulation technique that adjusts numeric values by rounding them to the nearest whole number or specified decimal places. Here's how it works:
Input: The transformation requires a numerical input column or field that you want to round.
Half-up Mode: The Half-up rounding method follows the conventional rounding rule: when the fraction part is exactly halfway between two whole numbers, it is rounded up to the nearest even whole number. For example, if the input value is 4.5 and the half-up mode is set to 0 decimal places, the transformed value would be 5. If the half-up mode is set to 1 decimal place, the transformed value would be 4.5.
Output: The transformation generates a new column or modifies the existing column, replacing the original values with the rounded values based on the half-up mode specified.
The Round Value using the Half-up Mode transformation is commonly used in situations where a fair rounding approach is desired, aiming to minimize any systematic bias introduced by rounding. It ensures that values are rounded in a balanced manner, avoiding a bias towards rounding up or down in specific scenarios.
Check out the illustration on the Round Value using the Half-up mode transform.
The Round Value using Half-up mode transform is applied to the Fare column as displayed below:
Navigate to the Data Preparation workspace.
Select a column from the displayed data grid.
Navigate to the Transforms tab.
Select the Round value using the halfup mode transform from the Numbers category.
The Round Value using Halfup Mode dialog box appears.
Provide the following information to apply the transforms:
Enable the Create a New Column option if you wish to create a new column with the transformed values.
Provide a name for the newly created column.
Set the Precision value up to what decimal you wish to show the value.
Select the Submit option.
As a result, a new column gets added to the dataset with the round-off values of the Fare column data by using the half-up mode:
