--- title: "varPop" slug: "/en/sql-reference/aggregate-functions/reference/varpop" sidebar_position: 32 --- This page covers the `varPop` and `varPopStable` functions available in ClickHouse. ## varPop Calculates the population covariance between two data columns. The population covariance measures the degree to which two variables vary together. Calculates the amount `Σ((x - x̅)^2) / n`, where `n` is the sample size and `x̅`is the average value of `x`. **Syntax** ```sql covarPop(x, y) ``` **Parameters** - `x`: The first data column. [Numeric](../../../native-protocol/columns.md) - `y`: The second data column. [Numeric](../../../native-protocol/columns.md) **Returned value** Returns an integer of type `Float64`. **Implementation details** This function uses a numerically unstable algorithm. If you need numerical stability in calculations, use the slower but more stable [`varPopStable` function](#varPopStable). **Example** ```sql DROP TABLE IF EXISTS test_data; CREATE TABLE test_data ( x Int32, y Int32 ) ENGINE = Memory; INSERT INTO test_data VALUES (1, 2), (2, 3), (3, 5), (4, 6), (5, 8); SELECT covarPop(x, y) AS covar_pop FROM test_data; ``` ```response 3 ``` ## varPopStable Calculates population covariance between two data columns using a stable, numerically accurate method to calculate the variance. This function is designed to provide reliable results even with large datasets or values that might cause numerical instability in other implementations. **Syntax** ```sql covarPopStable(x, y) ``` **Parameters** - `x`: The first data column. [String literal](../syntax#syntax-string-literal) - `y`: The second data column. [Expression](../syntax#syntax-expressions) **Returned value** Returns an integer of type `Float64`. **Implementation details** Unlike [`varPop()`](#varPop), this function uses a stable, numerically accurate algorithm to calculate the population variance to avoid issues like catastrophic cancellation or loss of precision. This function also handles `NaN` and `Inf` values correctly, excluding them from calculations. **Example** Query: ```sql DROP TABLE IF EXISTS test_data; CREATE TABLE test_data ( x Int32, y Int32 ) ENGINE = Memory; INSERT INTO test_data VALUES (1, 2), (2, 9), (9, 5), (4, 6), (5, 8); SELECT covarPopStable(x, y) AS covar_pop_stable FROM test_data; ``` ```response 0.5999999999999999 ```