Home
Function Reference
1010data Insights Platform offers a rich set of functions that may be used in value expressions when creating computed columns and in selection expressions when performing row selections.
Math functions
Math functions are vector functions that perform mathematical operations on one or more columns and return a column of results based on the operation.
Statistical
normal_cdf_inv(P;U;S)
Returns the inverse of the normal_cdf at P.

Function Reference
1010data Insights Platform offers a rich set of functions that may be used in value expressions when creating computed columns and in selection expressions when performing row selections.
- All 1010data Functions
  1010data provides a whole range of functions that can provide information and act on your data.
- Time/Date functions
  The time/date functions are vector functions that operate on columns containing time-related data and return specific information about the date/time for each row.
- Group functions (g_functions)
  Group functions, or g_functions, are used to perform operations, such as summarizations, on rows that have the same values in a set of given columns.
- Math functions
  Math functions are vector functions that perform mathematical operations on one or more columns and return a column of results based on the operation.
  - General
  - Exponential
  - Trigonometric
  - Factorial
  - Statistical
    - beta_cdf(A;B;X)
      Returns the beta cumulative distribution function with shape parameter A, rate parameter B, and value X.
    - bincoeff(N;K)
      Returns the binomial coefficient of two given values.
    - binomial_cdf(N;K;P)
      Returns the binomial cumulative distribution function value with N-trials, K-successes, and success probability P.
    - chisqr_cdf(DF;X)
      Returns the chi squared cumulative distribution function with degrees of freedom DF and value X.
    - combs(N;K)
      Returns the number of combinations of two given values.
    - draw(X;Y)
      Returns a random number using a given seed.
    - draw_(X;Y)
      Returns a random number using a given seed that remains persistent (sticky) even after selections or links with expansion are used.
    - drawint(X;Y)
      Returns a random integer between 0 and Y-1, seeded with X.
    - draw_int(X;Y)
      Returns a random integer using a given seed that remains persistent (sticky) even after selections or links with expansion are used.
    - drawrand(X)
      Returns a random float between 0 and 1, seeded with X.
    - draw_rand(X)
      Returns a random number using a given seed that remains persistent (sticky) even after selections or links with expansion are used.
    - drawunif(X;A;B)
      Returns a random float between A and B, using seed X.
    - draw_unif(X;A;B)
      Returns a random float between A and B, using a given seed that remains persistent (sticky) even after selections or links with expansion are used.
    - erf(X)
      Returns the Gaussian error function of a given value.
    - erlang_cdf(K;L;X)
      Returns the Erlang cumulative distribution function value with rate L and shape K at value X.
    - exponential_cdf(L;X)
      Returns the exponential cumulative distribution function value with mean L at value X.
    - f_cdf(DF1;DF2;F)
      Returns the F cumulative distribution function with degrees of freedom DF1 and DF2 at F.
    - gamma_cdf(A;B;X)
      Returns the gamma cumulative distribution function with shape parameter A, rate parameter B, and value X.
    - interp(V;N;X;Y;E)
      Returns a particular interpolation of a given value based on a discrete set of data points, and if specified, extrapolates out-of-range values.
    - normal01_rand_devs(X)
      Returns a random number for each row in the column drawn from a normal distribution with a mean of 0 and a standard deviation of 1.
    - normal_cdf(X;U;S)
      Returns the cumulative distribution function value at X for a normal distribution.
    - normal_cdf_inv(P;U;S)
      Returns the inverse of the normal_cdf at P.
    - perms(N;K)
      Returns the number of permutations of two given values.
    - poisson_cdf(L;K)
      Returns the Poisson cumulative distribution function for a given mean.
    - studentt_cdf(DF;T)
      Returns the Student's T cumulative distribution function with degrees of freedomDF and value T.
  - Bitwise
- Matrix functions
- Categorization functions
  Categorization functions are vector functions that organize data and determine logical groupings. These functions can be used for conditionalizing results and/or bucketing value ranges.
- String functions
  String functions are vector functions that manipulate vectors of strings to provide information about a string or substring, concatenate and split strings, or transform strings based on specified criteria.
- List functions
  List functions are scalar functions that return lists, subsets of lists, and combinations of lists, among other functionality. Lists, along with packages, are compound scalar data types that facilitate programmatic interaction with scalar data values and variables.
- Data-handling functions
  Data-handling functions are vector functions that return a hash value based on an input column or columns.
- Row functions
  Row functions are vector functions that return computational outputs for row inputs, as opposed to column outputs. Row inputs are defined as a space- or comma-separated list of column names.
- SQL compatibility functions
  SQL compatibility functions are functions that treat null values as SQL nulls.
- Financial functions
- System functions
  System functions are special functions in 1010data that return information about users, tables, and other system objects.
- Object functions
  The object functions can be used to check the existence, type, and accessibility of objects such as folders, tables, and queries on the 1010data Insights Platform.
- Miscellaneous functions
  This category of functions contains special functions that don't neatly fit into other categories of functions.

`normal_cdf_inv(P;U;S)`

Returns the inverse of the normal_cdf at P.

Syntax

normal_cdf_inv(P;U;S)

Input

Argument	Type	Description
`P`	decimal	A scalar value or the name of a column This is the probability of a random number being below a specific value such as `X`.
`U`	integer	A scalar value or the name of a column This value is the mean.
`S`	integer	A scalar value or the name of a column This value is the standard deviation.

Return Value

Returns the inverse of the normal_cdf at P.

If any argument is N/A, the result is N/A.