packages/vaex-core/vaex/dataframe.py
def col(self):
        """Gives direct access to the columns only (useful for tab completion).

        Convenient when working with ipython in combination with small DataFrames, since this gives tab-completion.

        Columns can be accesed by there names, which are attributes. The attribues are currently expressions, so you can
        do computations with them.

        Example

        >>> ds = vaex.example()
        >>> df.plot(df.col.x, df.col.y)

        """
        class ColumnList(object):
            pass
        data = ColumnList()
        for name in self.get_column_names():
            expression = getattr(self, name, None)
            if not isinstance(expression, Expression):
                expression = Expression(self, name)
            setattr(data, name, expression)
        return data
def col(self):
        """Gives direct access to the columns only (useful for tab completion).

        Convenient when working with ipython in combination with small DataFrames, since this gives tab-completion.

        Columns can be accesed by there names, which are attributes. The attribues are currently expressions, so you can
        do computations with them.

        Example

        >>> ds = vaex.example()
        >>> df.plot(df.col.x, df.col.y)

        """
        class ColumnList(object):
            pass
        data = ColumnList()
        for name in self.get_column_names():
            expression = getattr(self, name, None)
            if not isinstance(expression, Expression):
                expression = Expression(self, name)
            setattr(data, name, expression)
        return data
def col ( self ) : class ColumnList ( object ) : pass data = ColumnList ( ) for name in self . get_column_names ( ) : expression = getattr ( self , name , None ) if not isinstance ( expression , Expression ) : expression = Expression ( self , name ) setattr ( data , name , expression ) return data
Gives direct access to the columns only (useful for tab completion).

        Convenient when working with ipython in combination with small DataFrames, since this gives tab-completion.

        Columns can be accesed by there names, which are attributes. The attribues are currently expressions, so you can
        do computations with them.

        Example

        >>> ds = vaex.example()
        >>> df.plot(df.col.x, df.col.y)
Gives direct access to the columns only ( useful for tab completion ) .