Learn about a variety of mathematical functions available for creating derived columns, including operations like rounding, logarithmic calculations, trigonometric functions, and more. These functions allow for sophisticated data transformations in subscription and financial models, helping you derive meaningful insights from your datasets.
abs(value)
abs(-150)
to ensure you’re working with positive values in calculations.ceiling(value)
ceiling(250.75)
to round up to the next whole number.exp(value)
exp(0.5)
might represent an increase factor.floor(value)
floor(discount_percentage)
to get a whole number.ln(value)
ln(MRR)
to the monthly recurring revenue.log(value)
log(subscription_quantity)
can be applied.mod(value, divisor)
mod(total_months, 12)
.power(base, exponent)
power(MRR, growth_factor)
.rand()
rand()
and picking the lowest values.round(value, num_decimals)
round(MRR, 2)
.sqrt(value)
sin(value)
cos(value)
tan(value)
trunc(value)
trunc(MRR)
.sign(value)
sign(MRR_change)
could be used.Learn about a variety of mathematical functions available for creating derived columns, including operations like rounding, logarithmic calculations, trigonometric functions, and more. These functions allow for sophisticated data transformations in subscription and financial models, helping you derive meaningful insights from your datasets.
abs(value)
abs(-150)
to ensure you’re working with positive values in calculations.ceiling(value)
ceiling(250.75)
to round up to the next whole number.exp(value)
exp(0.5)
might represent an increase factor.floor(value)
floor(discount_percentage)
to get a whole number.ln(value)
ln(MRR)
to the monthly recurring revenue.log(value)
log(subscription_quantity)
can be applied.mod(value, divisor)
mod(total_months, 12)
.power(base, exponent)
power(MRR, growth_factor)
.rand()
rand()
and picking the lowest values.round(value, num_decimals)
round(MRR, 2)
.sqrt(value)
sin(value)
cos(value)
tan(value)
trunc(value)
trunc(MRR)
.sign(value)
sign(MRR_change)
could be used.