What is a DATABASE formula in a spreadsheet?
Database formulas and functions are used to work with structured data and perform operations like querying, filtering, sorting, and summarizing data. They are particularly useful for managing and manipulating large datasets efficiently.
database formula usage examples.
The DGET function is used to return a single value from a database table-like array or range using a SQL-like query. It takes three arguments: the database, the field to retrieve, and the criteria to filter the data. The function searches the database for records that match the criteria and returns the value of the specified field for the first matching record. If no records match the criteria, the function returns an error value.
The DMAX function is used to retrieve the maximum value from a database table-like array or range based on specified criteria. It requires three arguments: 'database' represents the range or array containing the data, 'field' specifies the column or field to evaluate, and 'criteria' defines the conditions to filter the data. The function returns the maximum value that meets the specified criteria.
The DMIN function is used to return the minimum value selected from a database table-like array or range using a SQL-like query. It takes three arguments: the database, which is the range of cells that makes up the database table; the field, which specifies the column or range of columns to consider for the calculation; and the criteria, which is a range of cells that specifies the conditions that must be met for a record to be included in the calculation. The DMIN function then evaluates the criteria and returns the minimum value from the specified field that meets the criteria.
The DPRODUCT function returns the product of values selected from a database table-like array or range using a SQL-like query. It takes three arguments: the database, the field to calculate the product from, and the criteria to filter the values. The function multiplies the values that meet the specified criteria and returns the result.
The DSTDEV function is used to calculate the standard deviation of a population sample selected from a database table-like array or range using a SQL-like query. It takes three arguments: 'database' represents the database table-like array or range, 'field' specifies the field or column in the database to calculate the standard deviation for, and 'criteria' defines the SQL-like query criteria to filter the population sample. The function returns the standard deviation as a numeric value.
The DSTDEVP function is used to calculate the standard deviation of an entire population selected from a database table-like array or range using a SQL-like query. It takes three arguments: 'database' represents the range or array containing the database table-like data, 'field' specifies the column or field in the database to consider for the calculation, and 'criteria' is an optional range or array specifying the conditions that must be met for a record to be included in the calculation. The function returns the standard deviation of the population.
The DSUM function returns the sum of values selected from a database table-like array or range using a SQL-like query. It takes three arguments: database (the range that represents the database table), field (the column or range containing the values to be summed), and criteria (the SQL-like query that specifies the conditions for selecting the values to be summed). The criteria can include logical operators, comparison operators, and functions to filter the data. DSUM is useful for performing calculations on specific subsets of data within a larger dataset.
The DVAR function is used to calculate the variance of a population sample selected from a database table-like array or range using a SQL-like query. It takes three arguments: 'database' represents the range or array containing the database table, 'field' specifies the column or range of columns to consider for the calculation, and 'criteria' defines the SQL-like query to filter the data before calculating the variance.