packages/vaex-core/vaex/dataframe.py
def dtype(self, expression, internal=False):
        """Return the numpy dtype for the given expression, if not a column, the first row will be evaluated to get the dtype."""
        expression = _ensure_string_from_expression(expression)
        if expression in self.variables:
            return np.float64(1).dtype
        elif expression in self.columns.keys():
            column = self.columns[expression]
            data = column[0:1]
            dtype = data.dtype
        else:
            data = self.evaluate(expression, 0, 1, filtered=False)
            dtype = data.dtype
        if not internal:
            if dtype != str_type:
                if dtype.kind in 'US':
                    return str_type
                if dtype.kind == 'O':
                    # we lie about arrays containing strings
                    if isinstance(data[0], six.string_types):
                        return str_type
        return dtype
def dtype(self, expression, internal=False):
        expression = _ensure_string_from_expression(expression)
        if expression in self.variables:
            return np.float64(1).dtype
        elif expression in self.columns.keys():
            column = self.columns[expression]
            data = column[0:1]
            dtype = data.dtype
        else:
            data = self.evaluate(expression, 0, 1, filtered=False)
            dtype = data.dtype
        if not internal:
            if dtype != str_type:
                if dtype.kind in 'US':
                    return str_type
                if dtype.kind == 'O':
                    # we lie about arrays containing strings
                    if isinstance(data[0], six.string_types):
                        return str_type
        return dtype
def dtype ( self , expression , internal = False ) : expression = _ensure_string_from_expression ( expression ) if expression in self . variables : return np . float64 ( 1 ) . dtype elif expression in self . columns . keys ( ) : column = self . columns [ expression ] data = column [ 0 : 1 ] dtype = data . dtype else : data = self . evaluate ( expression , 0 , 1 , filtered = False ) dtype = data . dtype if not internal : if dtype != str_type : if dtype . kind in 'US' : return str_type if dtype . kind == 'O' : # we lie about arrays containing strings if isinstance ( data [ 0 ] , six . string_types ) : return str_type return dtype
Return the numpy dtype for the given expression, if not a column, the first row will be evaluated to get the dtype.
Return the numpy dtype for the given expression if not a column the first row will be evaluated to get the dtype .