Formula

Add new features to your dataset.

Inputs

• Data: input dataset

Outputs

• Data: dataset with additional features

Formula allows computing new columns by combining the existing ones with a user-defined expression. The resulting column can be categorical, numerical or textual.

For numeric variables, it sufices to provide a name and an expression.

1. List of constructed variables
2. Add or remove variables
3. New feature name
4. Expression in Python
5. Select a feature
6. Select a function
7. Produce a report
8. Press Send to communicate changes

The following example shows construction of a categorical variable: its value is “lower” is “sepal length” is below 6, “mid” if it is at least 6 but below 7, and “higher” otherwise. Note that spaces need to be replaced by underscores (sepal_length).

1. List of variable definitions
2. Add or remove variables
3. New feature name
4. Expression in Python
5. If checked, the feature is put among meta attributes
6. Select a feature to use in expression
7. Select a function to use in expression
8. Optional list of values, used to define their order
9. Press Send to compute and output data

Hints

If you are unfamiliar with Python math language, here’s a quick introduction.

Expressions can use the following operators:

• +, -, *, /: addition, subtraction, multiplication, division
• //: integer division
• %: remainder after integer division
• **: exponentiation (for square root square by 0.5)
• <, >, <=, >= less than, greater than, less or equal, greater or equal
• == equal
• != not equal
• if-else: value if condition else other-value (see the above example

See more here.