packages/vaex-core/vaex/dataframe.py
def sum(self, expression, binby=[], limits=None, shape=default_shape, selection=False, delay=False, progress=None, edges=False):
        """Calculate the sum for the given expression, possible on a grid defined by binby

        Example:

        >>> df.sum("L")
        304054882.49378014
        >>> df.sum("L", binby="E", shape=4)
        array([  8.83517994e+06,   5.92217598e+07,   9.55218726e+07,
                         1.40008776e+08])

        :param expression: {expression}
        :param binby: {binby}
        :param limits: {limits}
        :param shape: {shape}
        :param selection: {selection}
        :param delay: {delay}
        :param progress: {progress}
        :return: {return_stat_scalar}
        """
        return self._compute_agg('sum', expression, binby, limits, shape, selection, delay, edges, progress)
        @delayed
        def finish(*sums):
            return vaex.utils.unlistify(waslist, sums)
        expression = _ensure_strings_from_expressions(expression)
        binby = _ensure_strings_from_expressions(binby)
        waslist, [expressions, ] = vaex.utils.listify(expression)
        progressbar = vaex.utils.progressbars(progress)
        limits = self.limits(binby, limits, delay=True)
        # stats = [calculate(expression, limits) for expression in expressions]
        sums = [self._sum_calculation(expression, binby=binby, limits=limits, shape=shape, selection=selection, progressbar=progressbar) for expression in expressions]
        s = finish(*sums)
        return self._delay(delay, s)
def sum(self, expression, binby=[], limits=None, shape=default_shape, selection=False, delay=False, progress=None, edges=False):
        """Calculate the sum for the given expression, possible on a grid defined by binby

        Example:

        >>> df.sum("L")
        304054882.49378014
        >>> df.sum("L", binby="E", shape=4)
        array([  8.83517994e+06,   5.92217598e+07,   9.55218726e+07,
                         1.40008776e+08])

        :param expression: {expression}
        :param binby: {binby}
        :param limits: {limits}
        :param shape: {shape}
        :param selection: {selection}
        :param delay: {delay}
        :param progress: {progress}
        :return: {return_stat_scalar}
        """
        return self._compute_agg('sum', expression, binby, limits, shape, selection, delay, edges, progress)
        @delayed
        def finish(*sums):
            return vaex.utils.unlistify(waslist, sums)
        expression = _ensure_strings_from_expressions(expression)
        binby = _ensure_strings_from_expressions(binby)
        waslist, [expressions, ] = vaex.utils.listify(expression)
        progressbar = vaex.utils.progressbars(progress)
        limits = self.limits(binby, limits, delay=True)
        # stats = [calculate(expression, limits) for expression in expressions]
        sums = [self._sum_calculation(expression, binby=binby, limits=limits, shape=shape, selection=selection, progressbar=progressbar) for expression in expressions]
        s = finish(*sums)
        return self._delay(delay, s)
Calculate the sum for the given expression, possible on a grid defined by binby

        Example:

        >>> df.sum("L")
        304054882.49378014
        >>> df.sum("L", binby="E", shape=4)
        array([  8.83517994e+06,   5.92217598e+07,   9.55218726e+07,
                         1.40008776e+08])

        :param expression: {expression}
        :param binby: {binby}
        :param limits: {limits}
        :param shape: {shape}
        :param selection: {selection}
        :param delay: {delay}
        :param progress: {progress}
        :return: {return_stat_scalar}