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Table 2.
Functions which can be computed on N dimensional grids and exploit the fast binning algorithm, which are readily available in vaex.
| Statistic | Description |
|---|---|
| count | Counts the number of rows, or non-missing values of an expression. |
| sum | Sum of non-missing values of an expression. |
| mean | The sample mean of an expression. |
| var | The sample variance of an expression, using a non-stable algorithm. |
| std | The sample standard deviation of an expression using a non-stable algorithm. |
| min | The minimum value of an expression. |
| max | The maximum value of an expression. |
| minmax | The minimum and maximum value of an expression (faster than min and max seperately). |
| covar | The sample covariance between two expressions. |
| correlation | The sample correlation coefficient between two expressions, i.e.  . |
| cov | The full covariance matrix for a list of expressions. |
| percentile_approx | Estimates the percentile of an expression. Since the true value requires sorting of values, we implement an approximation by interpolation over a cumulative histogram. |
| median_approx | Approximation of the median, based on the percentile statistic. |
| mode | Estimates the mode of an expression by calculating the peak of its histogram. |
| mutual_information | Calculates the mutual information for two or more expression, see Sect. 3.5.3 for details. |
| nearest | Finds the nearest row to a particular point for given a metric. |
Notes. All statistics can be computed for the full dataset, a subset using selections or multiple selections at the same time. For all calculations, missing values or NaN’s are ignored.
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