Please enable JavaScript.
Coggle requires JavaScript to display documents.
Chapter 10: Data Transformations (Transforms; Multiple Columns (Addition…
Chapter 10: Data Transformations
IF-THEN
examination
make changes to values
Create content in a new column
Transforms; Multiple Columns
Addition
+
adding different columns, predictive signals can be increased
Subtraction
-
subtracting one column from another, similarities and differences become more apparent
Absolute
Abs()
actual distance between two numbers
Multiplication
*
multiply two columns, product can represent a variable
Division
/
divides two columns, can be useful information
Less Than
<
predictive, informational
Less than or equal
<=
predictive, informational
Greater than
predictive, informational
Greater than or equal
=
predictive, informational
Not equal
!=
two data points aren't the same, can be used for prediction
Equal
=
if two data points are the same, can be used for prediction
Exponentiation
**
capture exponential relationship between columns
Transforms; Single Columns
Natural logarithm
Log()
linearize exponential data
Square Root
Sqrt()
compare ability to linearize data vs log
Square
Square()
makes large values even larger