def sum_of_squares(x):
x = x.astype("f8")._column
outcol = cpp_reduce.apply_reduce("sum_of_squares", x)
return cudf.Series(outcol)
def sum(self):
return cpp_reduce.apply_reduce('sum', self)
def sum_of_squares(self):
return cpp_reduce.apply_reduce('sum_squared', self)
def min(self):
return cpp_reduce.apply_reduce('min', self)
def max(self):
return cpp_reduce.apply_reduce('max', self)
def product(self, dtype=None):
return cpp_reduce.apply_reduce('product', self, dtype=dtype)
def sum_of_squares(self, dtype=None):
return cpp_reduce.apply_reduce('sum_of_squares', self, dtype=dtype)
def max(self, dtype=None):
return cpp_reduce.apply_reduce('max', self, dtype=dtype)
def sum(self, dtype=None):
return cpp_reduce.apply_reduce('sum', self, dtype=dtype)
def min(self, dtype=None):
return cpp_reduce.apply_reduce('min', self, dtype=dtype)
def product(self):
return cpp_reduce.apply_reduce('product', self)
def std(self, ddof=1, dtype=np.float64):
return cpp_reduce.apply_reduce("std", self, dtype=dtype, ddof=ddof)
def var(self, ddof=1, dtype=np.float64):
return cpp_reduce.apply_reduce("var", self, dtype=dtype, ddof=ddof)
def mean(self, dtype=np.float64):
return cpp_reduce.apply_reduce("mean", self, dtype=dtype)
