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.