Computation#

Expr.abs()

Compute absolute values.

Expr.approx_n_unique()

Approximate count of unique values.

Expr.arccos()

Compute the element-wise value for the inverse cosine.

Expr.arccosh()

Compute the element-wise value for the inverse hyperbolic cosine.

Expr.arcsin()

Compute the element-wise value for the inverse sine.

Expr.arcsinh()

Compute the element-wise value for the inverse hyperbolic sine.

Expr.arctan()

Compute the element-wise value for the inverse tangent.

Expr.arctanh()

Compute the element-wise value for the inverse hyperbolic tangent.

Expr.arg_unique()

Get index of first unique value.

Expr.cbrt()

Compute the cube root of the elements.

Expr.cos()

Compute the element-wise value for the cosine.

Expr.cosh()

Compute the element-wise value for the hyperbolic cosine.

Expr.cot()

Compute the element-wise value for the cotangent.

Expr.cum_count(*[, reverse])

Return the cumulative count of the non-null values in the column.

Expr.cum_max(*[, reverse])

Get an array with the cumulative max computed at every element.

Expr.cum_min(*[, reverse])

Get an array with the cumulative min computed at every element.

Expr.cum_prod(*[, reverse])

Get an array with the cumulative product computed at every element.

Expr.cum_sum(*[, reverse])

Get an array with the cumulative sum computed at every element.

Expr.cumcount(*[, reverse])

Get an array with the cumulative count computed at every element.

Expr.cummax(*[, reverse])

Get an array with the cumulative max computed at every element.

Expr.cummin(*[, reverse])

Get an array with the cumulative min computed at every element.

Expr.cumprod(*[, reverse])

Get an array with the cumulative product computed at every element.

Expr.cumsum(*[, reverse])

Get an array with the cumulative sum computed at every element.

Expr.cumulative_eval(expr[, min_periods, ...])

Run an expression over a sliding window that increases 1 slot every iteration.

Expr.degrees()

Convert from radians to degrees.

Expr.diff([n, null_behavior])

Calculate the first discrete difference between shifted items.

Expr.dot(other)

Compute the dot/inner product between two Expressions.

Expr.entropy([base, normalize])

Computes the entropy.

Expr.ewm_mean(*[, com, span, half_life, ...])

Exponentially-weighted moving average.

Expr.ewm_mean_by(by, *, half_life[, ...])

Calculate time-based exponentially weighted moving average.

Expr.ewm_std(*[, com, span, half_life, ...])

Exponentially-weighted moving standard deviation.

Expr.ewm_var(*[, com, span, half_life, ...])

Exponentially-weighted moving variance.

Expr.exp()

Compute the exponential, element-wise.

Expr.hash([seed, seed_1, seed_2, seed_3])

Hash the elements in the selection.

Expr.hist([bins, bin_count, ...])

Bin values into buckets and count their occurrences.

Expr.kurtosis(*[, fisher, bias])

Compute the kurtosis (Fisher or Pearson) of a dataset.

Expr.log([base])

Compute the logarithm to a given base.

Expr.log10()

Compute the base 10 logarithm of the input array, element-wise.

Expr.log1p()

Compute the natural logarithm of each element plus one.

Expr.mode()

Compute the most occurring value(s).

Expr.n_unique()

Count unique values.

Expr.null_count()

Count null values.

Expr.pct_change([n])

Computes percentage change between values.

Expr.peak_max()

Get a boolean mask of the local maximum peaks.

Expr.peak_min()

Get a boolean mask of the local minimum peaks.

Expr.radians()

Convert from degrees to radians.

Expr.rank([method, descending, seed])

Assign ranks to data, dealing with ties appropriately.

Expr.rolling_apply(function, window_size[, ...])

Apply a custom rolling window function.

Expr.rolling_map(function, window_size[, ...])

Compute a custom rolling window function.

Expr.rolling_max(window_size[, weights, ...])

Apply a rolling max (moving max) over the values in this array.

Expr.rolling_max_by(by, window_size, *[, ...])

Apply a rolling max based on another column.

Expr.rolling_mean(window_size[, weights, ...])

Apply a rolling mean (moving mean) over the values in this array.

Expr.rolling_mean_by(by, window_size, *[, ...])

Apply a rolling mean based on another column.

Expr.rolling_median(window_size[, weights, ...])

Compute a rolling median.

Expr.rolling_median_by(by, window_size, *[, ...])

Compute a rolling median based on another column.

Expr.rolling_min(window_size[, weights, ...])

Apply a rolling min (moving min) over the values in this array.

Expr.rolling_min_by(by, window_size, *[, ...])

Apply a rolling min based on another column.

Expr.rolling_quantile(quantile[, ...])

Compute a rolling quantile.

Expr.rolling_quantile_by(by, window_size, *, ...)

Compute a rolling quantile based on another column.

Expr.rolling_skew(window_size, *[, bias])

Compute a rolling skew.

Expr.rolling_std(window_size[, weights, ...])

Compute a rolling standard deviation.

Expr.rolling_std_by(by, window_size, *[, ...])

Compute a rolling standard deviation based on another column.

Expr.rolling_sum(window_size[, weights, ...])

Apply a rolling sum (moving sum) over the values in this array.

Expr.rolling_sum_by(by, window_size, *[, ...])

Apply a rolling sum based on another column.

Expr.rolling_var(window_size[, weights, ...])

Compute a rolling variance.

Expr.rolling_var_by(by, window_size, *[, ...])

Compute a rolling variance based on another column.

Expr.search_sorted(element[, side])

Find indices where elements should be inserted to maintain order.

Expr.sign()

Compute the element-wise indication of the sign.

Expr.sin()

Compute the element-wise value for the sine.

Expr.sinh()

Compute the element-wise value for the hyperbolic sine.

Expr.skew(*[, bias])

Compute the sample skewness of a data set.

Expr.sqrt()

Compute the square root of the elements.

Expr.tan()

Compute the element-wise value for the tangent.

Expr.tanh()

Compute the element-wise value for the hyperbolic tangent.

Expr.unique(*[, maintain_order])

Get unique values of this expression.

Expr.unique_counts()

Return a count of the unique values in the order of appearance.

Expr.value_counts(*[, sort, parallel, name])

Count the occurrences of unique values.