Array Functions

Apache OpenOffice 4.1 Calc Guide

Appendix B — Description of Functions

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• Functions Available in Calc
  • Terminology: Numbers and Arguments
• Mathematical Functions
• Financial Analysis Functions
  • A Note About Dates
  • A Note About Interest Rates
• Statistical Analysis Functions
• Date and Time Functions
• Logical Functions
• Informational Functions
• Database Functions
• Array Functions
• Spreadsheet Functions
• Text Functions
• Converting Decimal, Binary, Octal, Hexadecimal
• Complex Number Functions

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Array Functions

Table 44: Array functions

Syntax	Description
FREQUENCY(data; classes)	Counts how many elements of the cell range data are in each of the bins defined by the cell range classes.
GROWTH(data_Y; data_X; new_data_X; function_type)	Calculates the points of an exponential trend in an array. Data_Y is the Y Data array. Data_X (optional) is the X Data array. New_Data_X (optional) is the X data array, in which the values are recalculated. Function_type is optional. If function_type = 0, functions in the form y = m^x are calculated. Otherwise, y = b*m^x functions are calculated.
LINEST(data_Y; data_X; linear_type; stats)	Returns the parameters of a linear trend. Data_Y is the Y Data array. Data_X (optional) is the X Data array. Linear_Type (optional): If the line goes through the zero point, then set Linear_Type = 0. Stats (optional): If Stats=0, only the regression coefficients are calculated. Otherwise, other statistics will be seen.
LOGEST(data_Y; data_X; function_type; stats)	Fits the data to an exponential regression curve (y=b*m^x). Data_Y is the Y Data array. Data_X (optional) is the X Data array. Function_type (optional): If function_type = 0, functions in the form y = m^x are calculated. Otherwise, y = b*m^x functions are calculated. Stats (optional). If Stats=0, only the regression coefficient is calculated.
MDETERM(array)	Returns the determinant of an array. This function returns a value in the current cell; it is not necessary to define a range for the results. Array is a square array.
MINVERSE(array)	Returns the inverse array. Array is a square array that is to be inverted.
MMULT(array1; array2)	Calculates the array product of two arrays. The number of columns for array 1 must match the number of rows for array 2. Array1 is the first array used in the array product. Array2 is the second array.
MUNIT(dimensions)	Returns the unitary square array of a certain size. The unitary array is a square array where the main diagonal elements equal 1 and all other array elements are equal to 0. Dimensions refers to the size of the array unit.
SUMPRODUCT(array 1; array 2; …array 30)	Multiplies corresponding elements in the given arrays, and returns the sum of those products. Array 1; array 2;…array 30 are arrays whose corresponding elements are to be multiplied. At least one array must be part of the argument list. If only one array is given, all array elements are summed.
SUMX2MY2(array_X; array_Y)	Returns the sum of the difference of squares of corresponding values in two arrays. Array_X is the first array. Array_Y is the second array whose elements are to be squared.
SUMX2PY2(array_X; array_Y)	Returns the sum of the sum of squares of corresponding values in two arrays. Array_X is the first array whose arguments are to be squared and added. Array_Y is the second array, whose elements are to be added and squared.
SUMXMY2(array_X; array_Y)	Adds the squares of the difference between corresponding values in two arrays. Array_X is the first array, and Array_Y is the second array.
TRANSPOSE(array)	Transposes the rows and columns of an array. Array is the array in the spreadsheet that is to be transposed.
TREND(data_Y; data_X; new_data_X; linear_Type)	Returns values along a linear trend. Data_Y is the y-data array. Data_X (optional) is the x-data array. New_data_X (optional) is the array of the x-data, which is used for recalculating values. Linear_type is optional. If linear_type = 0, then lines will be calculated through the zero point. Otherwise, offset lines will also be calculated. The default is linear_type <> 0.