Looker Functions and Operators

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Table Calculations and Custom Filters both use Looker Expressions. A major part of these expressions are the functions and operators that you can use in them. This page includes information about all of these functions and operators.

The functions and operators can be divided into a few basic categories:

Mathematical Functions and Operators

Mathematical functions and operators work in one of two ways:

  • Some mathematical functions perform calculations based on a single row. For example, rounding, taking a square root, multiplying, and similar functions can be used for values in a single row, returning a distinct value for each and every row. All mathematical operators, such as +, are performed one row at a time.
  • Other mathematical functions, like averages and running totals, operate over many rows. These functions take many rows and reduce them to a single number, then display that same number on every row.

Functions for Custom Filters and Table Calculations

Function Syntax Purpose Relevant Discourse Articles
abs abs(value) Returns the absolute value of value Example
ceiling ceiling(value) Returns the smallest integer greater than or equal to value
exp exp(value) Returns e to the power of value Example
floor floor(value) Returns the largest integer less than or equal to value
ln ln(value) Returns the natural logarithm of value Example
log log(value) Returns the base 10 logarithm of value
mod mod(value, divisor) Returns the remainder of dividing value by divisor
power power(base, exponent) Returns base raised to the power of exponent Example
rand rand() Returns a random number between 0 and 1 Example
round round(value, num_decimals) Returns value rounded to num_decimals decimal places Example 1
Example 2
sqrt sqrt(value) Returns the square root of value Example

Functions for Table Calculations Only

Many of these functions operate over many rows and will only consider the rows returned by your query.

Function Syntax Purpose Relevant Discourse Articles
acos acos(value) ADDED4.22Returns the inverse cosine of value
asin asin(value) ADDED4.22Returns the inverse sine of value
atan atan(value) ADDED4.22Returns the inverse tangent of value
beta_dist beta_dist(value, alpha,
beta, cumulative)
ADDED4.22Returns 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)
ADDED4.22Returns 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)
ADDED4.22Returns 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)
ADDED4.22Returns the smallest number k such that binom(k, num_tests,
test_probability, yes)
>= target_probability
chisq_dist chisq_dist(value, dof,
cumulative)
ADDED4.22Returns 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) ADDED4.22Returns the position of probability on the inverse cumulative gamma distribution with dof degrees of freedom
chisq_test chisq_test(actual,
expected)
ADDED4.22Returns the probability for the chi-squared 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)
ADDED4.22Returns the number of ways of choosing selection_size elements from a set of size set_size
confidence_norm confidence_norm(alpha,
stdev, n)
ADDED4.22Returns 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)
ADDED4.22Returns half the width of the Student’s t confidence interval at significance level alpha, standard deviation stdev, and sample size n
correl correl(column_1, column_2) ADDED4.22Returns the correlation coefficient of column_1 and column_2
cos cos(value) ADDED4.22Returns the cosine of value
count count(expression) Returns the count of non-null 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) ADDED4.22Returns the count of distinct non-null 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)
ADDED4.22Returns the population covariance of column_1 and column_2
covar_samp covar_samp(column_1,
column_2)
ADDED4.22Returns the sample covariance of column_1 and column_2
degrees degrees(value) ADDED4.22Converts value from radians to degrees
expon_dist expon_dist(value, lambda,
cumulative)
ADDED4.22Returns 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)
ADDED4.22Returns 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)
ADDED4.22Returns the position of probability on the inverse cumulative F distribution with parameters dof_1 and dof_2
fact fact(value) ADDED4.22Returns the factorial of value
gamma_dist gamma_dist(value, alpha,
beta, cumulative)
ADDED4.22Returns 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)
ADDED4.22Returns the position of probability on the inverse cumulative gamma distribution with parameters alpha and beta
geomean geomean(expression) ADDED4.22Returns 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)
ADDED4.22Returns 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)
ADDED4.22Returns the intercept of the linear regression line through the points determined by y_column and x_column
kurtosis kurtosis(expression) ADDED4.22Returns 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) ADDED4.22Returns the kth largest value of the column created by expression unless expression defines a column of Lists, in which case returnsthe kth largest value of each List
match match(value, expression) ADDED4.22Returns 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 Example 1
Example 2
Example 3
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 Example 1
Example 2
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
mode mode(expression) ADDED4.22Returns 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, ...)
ADDED4.22Returns 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)
ADDED4.22Returns 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)
ADDED4.22Returns 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)
ADDED4.22Returns the position of probability on the inverse normal cumulative distribution
norm_s_dist norm_s_dist(value,
cumulative)
ADDED4.22Returns the position of value on the standard normal distribution. If cumulative = yes, returns the cumulative probability
norm_s_inv norm_s_inv(probability) ADDED4.22Returns the position of probability on the inverse standard normal cumulative distribution
percent_rank percent_rank(column, value) ADDED4.22Returns 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() ADDED4.22Returns the value of pi
poisson_dist poisson_dist(value, lambda,
cumulative)
ADDED4.22Returns the position of value on the poisson distribution with parameter lambda. If cumulative = yes, returns the cumulative probability
product product(expression) ADDED4.22Returns 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) ADDED4.22Converts value from degrees to radians
rank rank(value, expression) ADDED4.22Returns the rank of value in the column created by expression unless expression defines a column of Lists, in which case returns the rank of value in each List
rank_avg rank_avg(value, expression) ADDED4.22Returns 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
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 Example 1
Example 2
sin sin(value) ADDED4.22Returns the sine of value
skew skew(expression) ADDED4.22Returns 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) ADDED4.22Returns the slope of the linear regression line through points determined by y_column and x_column
small small(expression, k) ADDED4.22Returns the kth smallest value of the column created by expression unless expression defines a column of Lists, in which case returnsthe kth smallest value of each List
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 Example 1
Example 2
Example 3
Example 4
t_dist t_dist(value, dof,
cumulative)
ADDED4.22Returns the position of value on the student’s t-distribution with dof degrees of freedeom. If cumulative = yes, returns the cumulative probability
t_inv t_inv(probability, dof) ADDED4.22Returns 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)
ADDED4.22Returns the result of a Student’s t-test on the data from column_1 and column_2, using 1 or 2 tails. type: 1 = paired, 2 = homoscedastic, 3 = heteroscedastic
tan tan(value) ADDED4.22Returns 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)
ADDED4.22Returns 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) ADDED4.22Returns the one-tailed p-value of the z-test using the existing data and stdev on the hypothesized mean value.

Operators for Custom Filters and Table Calculations

You can use the following standard mathematical operators:

Operators Syntax Purpose
+ value_1 + value_2 Adds value_1 and value_2
- value_1 - value_2 Subtracts value_1 and value_2
* value_1 * value_2 Multiplies value_1 and value_2
/ value_1 / value_2 Divides value_1 and value_2

String Functions

String functions operate on sentences, words, or letters, which are collectively called “strings”. String functions are used to capitalize words and letters, extract parts of a phrase, check to see if a word or letter is in a phrase, or replace elements of a word or phrase. They can also be used to format the data returned in the table.

Functions for Custom Filters and Table Calculations

Function Syntax Purpose
concat concat(value_1, value_2, ...) Returns value_1, value_2, ..., value_n joined as one string
contains contains(string, search_string) Returns Yes if string contains search_string, and No otherwise
length length(string) Returns the number of characters in string
lower lower(string) Returns string with all characters converted to lower case
position position(string, search_string) Returns the start index of search_string in string if it exists, and 0 otherwise
replace replace(string, old_string, new_string) Returns string with all occurrences of old_string replaced with new_string
substring substring(string, start_position, length) Returns the substring of string beginning at start_position consisting of length characters
upper upper(string) Returns string with all characters converted to upper case

Functions for Table Calculations Only

Function Syntax Purpose
to_number to_number(string) ADDED4.22 Returns the number represented by string, or null if the string cannot be converted

Date Functions

Date functions enable you to work with dates and times.

Functions for Custom Filters and Table Calculations

Function Syntax Purpose Relevant Discourse Articles
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 “year-month-day” date or null if the date would be invalid
date_time date_time(year, month, day,
hours, minutes, seconds)
Returns
year-month-day 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 Example
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 Example
diff_months diff_months(start_date, end_date) Returns the number of months between start_date and end_date Example
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 Example
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 Example 1
Example 2
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

Additional information and examples can be found in this Discourse article.

Functions for Table Calculations Only

Function Syntax Purpose
to_date to_date(string) ADDED4.22 Returns the date and time corresponding to string (YYYY, YYYY-MM, YYYY-MM-DD, YYYY-MM-DD hh, YYYY-MM-DD hh:mm, or YYYY-MM-DD hh:mm:ss)

Logical Functions, Operators, and Constants

Logical functions and operators deal with whether or not something is true or false. This type of function takes the value of something, evaluates it against some criteria, returns true if the criteria is met, and false if the criteria is not met. There are also various logical operators for comparing values and combining logical expressions.

Functions for Custom Filters and Table Calculations

Function Syntax Purpose Relevant Discourse Articles
coalesce coalesce(value_1, value_2, ...) Returns the first non-null value in value_1, value_2, ..., value_n if found and null otherwise Example 1
Example 2
Example 3
if if(yesno_expression,
value_if_yes,
value_if_no)
If yesno_expression evaluates to Yes, returns the value_if_yes value. Otherwise, returns the value_if_no value Example 1
Example 2
is_null is_null(value) Returns Yes if value is null, and No otherwise Example 1
Example 2

Operators for Custom Filters and Table Calculations

The following comparison operators can be used with any datatype:

Operator Syntax Purpose
= value_1 = value_2 Returns Yes if value_1 is equal to value_2, and No otherwise
!= value_1 != value_2 Returns Yes if value_1 is not equal to value_2, and No otherwise

The following comparison operators only can be used with numbers and dates:

Operator Syntax Purpose
> value_1 > value_2 Returns Yes if value_1 is greater than value_2, and No otherwise
< value_1 < value_2 Returns Yes if value_1 is less than value_2, and No otherwise
>= value_1 >= value_2 Returns Yes if value_1 is greater than or equal to value_2, and No otherwise
<= value_1 <= value_2 Returns Yes if value_1 is less than or equal to value_2, and No otherwise

You also can combine Looker Expressions with these logical operators:

Operator Syntax Purpose
AND value_1 AND value_2 Returns Yes if both value_1 and value_2 are Yes, and No otherwise
OR value_1 OR value_2 Returns Yes if either value_1 or value_2 is Yes, and No otherwise
NOT NOT value Returns Yes if value is No, and Yes otherwise

Logical Constants

You can use logical constants in Looker Expressions. These constants are always written in lowercase and have the following meanings:

Constant Meaning
yes True
no False
null There is no value

Note that the constants yes and no, are the special symbols that ‚Äčmean true or false in Looker Expressions. In contrast, using quotes such as in "yes" and "no" creates literal strings with those values.

Logical expressions evaluate to true or false without requiring an if function. For example, this:

if(${field} > 100, yes, no)

is equivalent to this:

${field} > 100

You also can use null to indicate no value. For example, you may want to determine if a field is empty, or assign an empty value in a certain situation. This formula returns no value if the field is less than 1, or the value of the field if it is more than 1:

if(${field} < 1, null, ${field})

Combining AND and OR operators

AND operators are evaluated before OR operators, if you don’t otherwise specify the order with parentheses. Thus the following expression without additional parentheses:

if (
  ${order_items.days_to_process}>=4 OR
  ${order_items.shipping_time}>5 AND
  ${order_facts.is_first_purchase},
"review", "okay")

would be evaluated as:

if (
  ${order_items.days_to_process}>=4 OR
  (${order_items.shipping_time}>5 AND ${order_facts.is_first_purchase}),
"review", "okay")

Positional Functions

When creating table calculations, you can use positional transformation functions to extract information about fields in different rows or pivot columns.

Row-related Functions for Table Calculations Only

Function Syntax Purpose Relevant Discourse Articles
index index(expression, n) ADDED4.22 Returns the value of the nth element of the column created by expression, unless expression defines a column of Lists, in which case returns the nth element of each list
list list(value_1, value_2, ...) Creates a List out of the given values Example
lookup lookup(value, lookup_column,
result_column)
ADDED4.22 Returns the value in result_column that is in the same row as value is in lookup_column
offset offset(column, row_offset) Returns the value of row (n + row_offset) in column, where n is the current row number Example 1
Example 2
Example 3
Example 4
offset_list offset_list(column, row_offset,
num_values)
Returns a List of the num_values values starting at row (n + row_offset) in column, where n is the current row number Example 1
Example 2
row row() Returns the current row number Example

Pivot-related Functions for Table Calculations Only

Some of these functions use the relative positions of pivot columns, so changing the sort order of the pivoted dimension affects the results of those functions.

Function Syntax Purpose Relevant Discourse Articles
pivot_column pivot_column() Returns the index of the current pivot column
pivot_index pivot_index(expression, pivot_index) Evaluates expression in the context of the pivot column at position pivot_index (1 for first pivot, 2 second pivot, etc.). Returns null for unpivoted results Example 1
Example 2
pivot_offset pivot_offset(pivot_expression, col_offset) Returns the value of the pivot_expression in position (n + col_offset), where n is the current pivot column position. Returns null for unpivoted results Example 1
Example 2
Example 3
pivot_offset_list pivot_offset_list(pivot_expression,
col_offset, num_values)
Returns a List of the the num_values values in pivot_expression starting at position (n + col_offset), where n is the current pivot index. Returns null for unpivoted results Example
pivot_row pivot_row(expression) Returns the pivoted values of expression as a List. Returns null for unpivoted results. Example 1
Example 2
pivot_where pivot_where(select_expression, expression) Returns the value of expression for the pivot column which uniquely satisfies select_expression or null if such a unique column does not exist.

The specific pivot functions you use determines whether the table calculation is displayed next to each pivoted column, or is displayed as a single column at the end of the table.

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