packages/vaex-core/vaex/dataframe.py
def count(self, expression=None, binby=[], limits=None, shape=default_shape, selection=False, delay=False, edges=False, progress=None):
        """Count the number of non-NaN values (or all, if expression is None or "*").

        Example:

        >>> df.count()
        330000
        >>> df.count("*")
        330000.0
        >>> df.count("*", binby=["x"], shape=4)
        array([  10925.,  155427.,  152007.,   10748.])

        :param expression: Expression or column for which to count non-missing values, or None or '*' for counting the rows
        :param binby: {binby}
        :param limits: {limits}
        :param shape: {shape}
        :param selection: {selection}
        :param delay: {delay}
        :param progress: {progress}
        :param edges: {edges}
        :return: {return_stat_scalar}
        """
        return self._compute_agg('count', expression, binby, limits, shape, selection, delay, edges, progress)
def count(self, expression=None, binby=[], limits=None, shape=default_shape, selection=False, delay=False, edges=False, progress=None):
        """Count the number of non-NaN values (or all, if expression is None or "*").

        Example:

        >>> df.count()
        330000
        >>> df.count("*")
        330000.0
        >>> df.count("*", binby=["x"], shape=4)
        array([  10925.,  155427.,  152007.,   10748.])

        :param expression: Expression or column for which to count non-missing values, or None or '*' for counting the rows
        :param binby: {binby}
        :param limits: {limits}
        :param shape: {shape}
        :param selection: {selection}
        :param delay: {delay}
        :param progress: {progress}
        :param edges: {edges}
        :return: {return_stat_scalar}
        """
        return self._compute_agg('count', expression, binby, limits, shape, selection, delay, edges, progress)
def count ( self , expression = None , binby = [ ] , limits = None , shape = default_shape , selection = False , delay = False , edges = False , progress = None ) : return self . _compute_agg ( 'count' , expression , binby , limits , shape , selection , delay , edges , progress )
Count the number of non-NaN values (or all, if expression is None or "*").

        Example:

        >>> df.count()
        330000
        >>> df.count("*")
        330000.0
        >>> df.count("*", binby=["x"], shape=4)
        array([  10925.,  155427.,  152007.,   10748.])

        :param expression: Expression or column for which to count non-missing values, or None or '*' for counting the rows
        :param binby: {binby}
        :param limits: {limits}
        :param shape: {shape}
        :param selection: {selection}
        :param delay: {delay}
        :param progress: {progress}
        :param edges: {edges}
        :return: {return_stat_scalar}
Count the number of non - NaN values ( or all if expression is None or * ) .