General Information
The brick provides a possibility to calculate the formula for both string and numerical variables for each row. For column calculation look at Apply Function.
Description
Brick Location
Bricks → Calculation → Math Formula
Brick Inputs/Outputs
- Inputs
Brick takes the dataset.
- Outputs
Brick calculates a formula for the input dataset and returns it with a calculated column.
Formula Adjustment
- Target - the name of the column for which we calculate the formula. It is possible to choose existing or write down the name of the new one.
- Arguments - names of columns which can be used in calculation.
- Block with formula which will be doubled on the side panel as well.
- Operations block shows all the possible operations in categories.
- Arithmetic: addition, subtraction, multiplication and division.
- Trigonometric: functions of sine, cosine, tangent, cotangent.
- Logical: comparing less, more, equal, less equal, more equal, equal, not equal, logical ‘and’, logical ’or’, logical ’not’.
- Logarithm operations.
- Power: finding x power of y, x power of 2, x power of 3, x power of 10, e power of x, 2 power of x, 10 power of x, square root of x, cube root of x, y root of x.
- Other: finding minimum of 2 values, maximum of 2 values, rounding, rounding down, rounding up, sign of x, absolute value.
- String: checking if one string contains another, if one string is contained by another, concatenation of two strings, subtraction of symbols from the string, replacing one string with another.
Example of usage
For demonstration, let us consider the Titanic dataset, which subset is presented below:
Numerical usage
Let suggest we want to set a new fare with a certain rule. We write down the name of the new column in Target field, then choose what operations we need (in this case we choose minimum of two values, one of which is power of two).
As a result we get the table with new_fare column.
String Usage
For example, we need to know the first letter of cabin.
First, we choose the target column or write down the name of a new.
Then, find in String Operations section substring(str, position, n) and choose it. To choose the column we click at one of the argument and then fill other parameters.
As a result we have a dataset with a new column which shows the first letter of the cabin.
Logical Usage
Let try complex logical statement to check if a passenger was female and number of parents/children was equal to 2.
We create a new column, then choose logical operator AND operator and fill it with two conditions. For the first condition we choose contains(str,substr) from String Operations section and fill the parameters with name of the column and word we want to check e.g. ‘female’. For the second condition we need to select column with operator ‘equal’ (==).
As a result we have a dataset with a new column which shows if each row satisfies our conditions.
