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Statistics

Over One Variable​

Elements that calculate different statistics with the self-descriptive names:

  • average calculates the arithmetic mean.
  • standard_deviation square root of dispersion for a set of values
  • dispersion dispersion for a set of values (Σ((x - x̅)^2) / n), , where n is the sample size and x̅ is the average value of x
  • median median of a numeric data sample
  • entropy calculates Shannon entropy of a set of values
  • skew skewness of a set of values
  • kurtosis kurtosis of a set of values
  • quantileapproximate quantile of a numeric data sequence (have level argument from 0 to 1, 0.5 is median)

For example to calculate average reward:

average(of: Reward_Total)

Over Two Variables​

Some statistics require 2 variables. One variable is specified in of attribute, the other in with attribute, for example:

correlation(of: Reward_Total with: Block_GasUsed)

Elements that calculate different statistics with the self-descriptive names:

  • covariance value of Σ((x - x̅)(y - y̅)) / n
  • correlation pearson correlation coefficient: Σ((x - x̅)(y - y̅)) / sqrt(Σ((x - x̅)^2) * Σ((y - y̅)^2))
  • contingency calculates the contingency coefficient, a value that measures the association between two columns in a table. The computation is similar to the cramersV function but with a different denominator in the square root
  • rank_correlation rank correlation coefficient of the ranks of x and y. The value of the correlation coefficient ranges from -1 to +1. If less than two arguments are passed, the function will return an exception. The value close to +1 denotes a high linear relationship, and with an increase of one random variable, the second random variable also increases. The value close to -1 denotes a high linear relationship, and with an increase of one random variable, the second random variable decreases. The value close or equal to 0 denotes no relationship between the two random variables.
  • cramers Cramér's V (sometimes referred to as Cramér's phi) is a measure of association between two columns in a table. The result of the cramers function ranges from 0 (corresponding to no association between the variables) to 1 and can reach 1 only when each value is completely determined by the other. It may be viewed as the association between two variables as a percentage of their maximum possible variation.
  • cramers_bias_corrected Cramér's V is a measure of association between two columns in a table. The result of the cramersV function ranges from 0 (corresponding to no association between the variables) to 1 and can reach 1 only when each value is completely determined by the other. The function can be heavily biased, so this version of Cramér's V uses the bias correction.
  • theils calculates the Theil's U uncertainty coefficient, a value that measures the association between two columns in a table. Its values range from −1.0 (100% negative association, or perfect inversion) to +1.0 (100% positive association, or perfect agreement). A value of 0.0 indicates the absence of association.
tip

You can use condition to any of these metrics