Table calculations allow you to create onthefly metrics and calculations based on results from Slope runs. They are similar to formulas found in spreadsheet tools like Excel. Table calculations can perform mathematical, logical (true/false), lexical (textbased), and datebased calculations on Slope output query results.
Table calculations are created by selecting the Custom Fields menu, then clicking on New and selecting Table Calculation on the left side of an Explore or Dashboard tile edit screen:
This will bring up the table calculation edit screen where you can create new calculations to use in your dashboards and reports.
Mathematical Functions
Function  Syntax  Purpose 

abs  abs(value) 
Returns the absolute value of value 
acos  acos(value) 
Returns the inverse cosine of value 
asin  asin(value) 
Returns the inverse sine of value 
atan  atan(value) 
Returns the inverse tangent of value 
beta_dist  beta_dist(value, alpha, beta, cumulative) 
Returns the position of value on the beta distribution with parameters alpha and beta . If cumulative = yes , returns the cumulative probability 
beta_inv  beta_inv(probability, alpha, beta) 
Returns the position of probability on the inverse cumulative beta distribution with parameters alpha and beta 
binom_dist  binom_dist(num_successes, num_tests, probability, cumulative) 
Returns the probability of getting num_successes successes in num_tests tests with the given probability of success. If cumulative = yes , returns the cumulative probability 
binom_inv  binom_inv(num_tests, test_probability, target_probability) 
Returns the smallest number k such that binom(k, num_tests, test_probability, yes) >= target_probability 
ceiling  ceiling(value) 
Returns the smallest integer greater than or equal to value 
chisq_dist  chisq_dist(value, dof, cumulative) 
Returns the position of value on the gamma distribution with dof degrees of freedom. If cumulative = yes , returns the cumulative probability 
chisq_inv  chisq_inv(probability, dof) 
Returns the position of probability on the inverse cumulative gamma distribution with dof degrees of freedom 
chisq_test  chisq_test(actual, expected) 
Returns the probability for the chisquared test for independence between actual and expected data. actual can be a column or a column of lists, and expected must be the same type. 
combin  combin(set_size, selection_size) 
Returns the number of ways of choosing selection_size elements from a set of size set_size 
confidence_norm  confidence_norm(alpha, stdev, n) 
Returns half the width of the normal confidence interval at significance level alpha , standard deviation stdev , and sample size n 
confidence_t  confidence_t(alpha, stdev, n) 
Returns half the width of the Student’s tdistribution confidence interval at significance level alpha , standard deviation stdev , and sample size n 
correl  correl(column_1, column_2) 
Returns the correlation coefficient of column_1 and column_2 
cos  cos(value) 
Returns the cosine of value 
count  count(expression) 
Returns the count of nonnull values in the column defined by expression , unless expression defines a column of Lists, in which case returns the count in each List 
count_distinct  count_distinct(expression) 
Returns the count of distinct nonnull values in the column defined by expression , unless expression defines a column of Lists, in which case returns the count in each List 
covar_pop  covar_pop(column_1, column_2) 
Returns the population covariance of column_1 and column_2 
covar_samp  covar_samp(column_1, column_2) 
Returns the sample covariance of column_1 and column_2 
degrees  degrees(value) 
Converts value from radians to degrees 
exp(value) 
Returns e to the power of value 

expon_dist  expon_dist(value, lambda, cumulative) 
Returns the position of value on the exponential distribution with parameter lambda . If cumulative = yes , returns the cumulative probability 
f_dist  f_dist(value, dof_1, dof_2, cumulative) 
Returns the position of value on the F distribution with parameters dof_1 and dof_2 . If cumulative = yes , returns the cumulative probability 
f_inv  f_inv(probability, dof_1, dof_2) 
Returns the position of probability on the inverse cumulative F distribution with parameters dof_1 and dof_2 
fact  fact(value) 
Returns the factorial of value 
floor  floor(value) 
Returns the largest integer less than or equal to value 
gamma_dist  gamma_dist(value, alpha, beta, cumulative) 
Returns the position of value on the gamma distribution with parameters alpha and beta . If cumulative = yes , returns the cumulative probability 
gamma_inv  gamma_inv(probability, alpha, beta) 
Returns the position of probability on the inverse cumulative gamma distribution with parameters alpha and beta 
geomean  geomean(expression) 
Returns the geometric mean of the column created by expression unless expression defines a column of Lists, in which case returns the geometric mean of each List 
hypgeom_dist  hypgeom_dist (sample_successes, sample_size, population_successes, population_size, cumulative) 
Returns the probability of getting sample_successes from the given sample_size , number of population_successes , and population_size . If cumulative = yes , returns the cumulative probability 
intercept  intercept(y_column, x_column) 
Returns the intercept of the linear regression line through the points determined by y_column and x_column 
kurtosis  kurtosis(expression) 
Returns the sample excess kurtosis of the column created by expression unless expression defines a column of Lists, in which case returns the sample excess kurtosis of each List 
large  large(expression, k) 
Returns the k th largest value of the column created by expression unless expression defines a column of Lists, in which case returnsthe k th largest value of each List 
ln  ln(value) 
Returns the natural logarithm of value 
log  log(value) 
Returns the base 10 logarithm of value 
match  match(value, expression) 
Returns the row number of the first occurence of value in the column created by expression unless expression defines a column of Lists, in which case returns the position of value in each List 
max  max(expression) 
Returns the max of the column created by expression unless expression defines a column of Lists, in which case returns the max of each List 
mean  mean(expression) 
Returns the mean of the column created by expression unless expression defines a column of Lists, in which case returns the mean of each List 
median  median(expression) 
Returns the median of the column created by expression unless expression defines a column of Lists, in which case returns the median of each List 
min  min(expression) 
Returns the min of the column created by expression unless expression defines a column of Lists, in which case returns the min of each List 
mod  mod(value, divisor) 
Returns the remainder of dividing value by divisor 
mode  mode(expression) 
Returns the mode of the column created by expression unless expression defines a column of Lists, in which case returns the mode of each List 
multinomial  multinomial(value_1, value_2, ...) 
Returns the factorial of the sum of the arguments divided by the product of each of their factorials 
negbinom_dist  negbinom_dist(num_failures, num_successes, probability, cumulative) 
Returns the probability of getting num_failures failures before getting num_successes successes, with the given probability of success. If cumulative = yes , returns the cumulative probability 
norm_dist  norm_dist(value, mean, stdev, cumulative) 
Returns the position of value on the normal distribution with the given mean and stdev . If cumulative = yes , then returns the cumulative probability 
norm_inv  norm_inv(probability, mean, stdev) 
Returns the position of probability on the inverse normal cumulative distribution 
norm_s_dist  norm_s_dist(value, cumulative) 
Returns the position of value on the standard normal distribution. If cumulative = yes , returns the cumulative probability 
norm_s_inv  norm_s_inv(probability) 
Returns the position of probability on the inverse standard normal cumulative distribution 
percent_rank  percent_rank(column, value) 
Returns the rank of value in column as a percentage from 0 to 1 inclusive 
percentile  percentile(value_column, percentile_value) 
Returns the value from the column created by expression corresponding to the given percentile_value , unless expression defines a column of Lists, in which case returns the percentile value for each List. Note: percentile_value must be between 0 and 1, else this returns null 
pi  pi() 
Returns the value of pi 
poisson_dist  poisson_dist(value, lambda, cumulative) 
Returns the position of value on the poisson distribution with parameter lambda . If cumulative = yes , returns the cumulative probability 
power  power(base, exponent) 
Returns base raised to the power of exponent 
product  product(expression) 
Returns the product of the column created by expression unless expression defines a column of Lists, in which case returns the product of each List 
radians  radians(value) 
Converts value from degrees to radians 
rand  rand() 
Returns a random number between 0 and 1 
rank  rank(value, expression) 
Returns the rank of value in the column created by expression . For example, if you want to rank orders by their total sale price, you could use rank(${order_items.total_sale_price},${order_items.total_sale_price}) , which gives a rank for each value of order_items.total_sale_price in your query when comparing it to the entire column of order_items.total_sale_price in your query. In the case where the expression defines multiple lists, this function returns the relative size of the value in each list. 
rank_avg  rank_avg(value, expression) 
Returns the average rank of value in the column created by expression unless expression defines a column of lists, in which case returns the average rank of value in each list. 
round  round(value, num_decimals) 
Returns value rounded to num_decimals decimal places 
running_product  running_product (value_column) 
Returns a running product of the values in value_column 
running_total  running_total(value_column) 
Returns a running total of the values in value_column 
sin  sin(value) 
Returns the sine of value 
skew  skew(expression) 
Returns the sample skewness of the column created by expression unless expression defines a column of Lists, in which case returns the sample skewness of each List 
slope  slope(y_column, x_column) 
Returns the slope of the linear regression line through points determined by y_column and x_column 
small  small(expression, k) 
Returns the k th smallest value of the column created by expression unless expression defines a column of Lists, in which case returnsthe k th smallest value of each List 
sqrt  sqrt(value) 
Returns the square root of value 
stddev_pop  stddev_pop(expression) 
Returns the standard deviation (population) of the column created by expression unless expression defines a column of Lists, in which case returns the standard deviation (population) of each List 
stddev_samp  stddev_pop(expression) 
Returns the standard deviation (sample) of the column created by expression unless expression defines a column of Lists, in which case returns the standard deviation (sample) of each List 
sum  sum(expression) 
Returns the sum of the column created by expression unless expression defines a column of Lists, in which case returns the sum of each List 
t_dist  t_dist(value, dof, cumulative) 
Returns the position of value on the Student’s tdistribution with dof degrees of freedeom. If cumulative = yes , returns the cumulative probability 
t_inv  t_inv(probability, dof) 
Returns the position of probability on the inverse normal cumulative distribution with dof degrees of freedom 
t_test  t_test(column_1, column_2, tails, type) 
Returns the result of a Student’s ttest on the data from column_1 and column_2 , using 1 or 2 tails . type : 1 = paired, 2 = homoscedastic, 3 = heteroscedastic 
tan  tan(value) 
Returns the tangent of value 
var_pop  var_pop(expression) 
Returns the variance (population) of the column created by expression unless expression defines a column of Lists, in which case returns the variance (population) of each List 
var_samp  var_pop(expression) 
Returns the variance (sample) of the column created by expression unless expression defines a column of Lists, in which case returns the variance (sample) of each List 
weibull_dist  weibull_dist(value, shape, scale, cumulative) 
Returns the position of value on the Weibull distribution with parameters shape and scale . If cumulative = yes , returns the cumulative probability 
z_test  z_test(data, value, stdev) 
Returns the onetailed pvalue of the ztest using the existing data and stdev on the hypothesized mean value . 
String Functions
Date Functions
Function  Syntax  Purpose 

add_days  add_days(number, date) 
Adds number days to date 
add_hours  add_hours(number, date) 
Adds number hours to date 
add_minutes  add_minutes(number, date) 
Adds number minutes to date 
add_months  add_months(number, date) 
Adds number months to date 
add_seconds  add_seconds(number, date) 
Adds number seconds to date 
add_years  add_years(number, date) 
Adds number years to date 
date  date(year, month, day) 
Returns “yearmonthday ” date or null if the date would be invalid 
date_time  date_time(year, month, day, hours, minutes, seconds) 
Returns “ yearmonthday hours:minutes:seconds ” date or null if the date would be invalid 
diff_days  diff_days(start_date, end_date) 
Returns the number of days between start_date and end_date 
diff_hours  diff_hours(start_date, end_date) 
Returns the number of hours between start_date and end_date 
diff_minutes  diff_minutes(start_date, end_date) 
Returns the number of minutes between start_date and end_date 
diff_months  diff_months(start_date, end_date) 
Returns the number of months between start_date and end_date 
diff_seconds  diff_seconds(start_date, end_date) 
Returns the number of seconds between start_date and end_date 
diff_years  diff_years(start_date, end_date) 
Returns the number of years between start_date and end_date 
extract_days  extract_days(date) 
Extracts the days from date 
extract_hours  extract_hours(date) 
Extracts the hours from date 
extract_minutes  extract_minutes(date) 
Extracts the minutes from date 
extract_months  extract_months(date) 
Extracts the months from date 
extract_seconds  extract_seconds(date) 
Extracts the seconds from date 
extract_years  extract_years(date) 
Extracts the years from date 
now  now() 
Returns the current date and time 
trunc_days  trunc_days(date) 
Truncates date to days 
trunc_hours  trunc_hours(date) 
Truncates date to hours 
trunc_minutes  trunc_minutes(date) 
Truncates date to minutes 
trunc_months  trunc_months(date) 
Truncates date to months 
trunc_years  trunc_years(date) 
Truncates date to years 