numpy.sum(a,axis=None,dtype=None,out=None,keepdims=<no value>,initial=<no value>) 文档中对sum函数只用了一句话描述:Sum of array elements over a give axis(对指定坐标轴axis上的元素进行求和)。它的返回结果: An array with the same shape as input, with the specified axis removed(返回结果的sh...
numpy.sum(a,axis=None,dtype=None,out=None,keepdims=False)[source] Sum of array elements over a given axis. Parameters: a: array_like Elements to sum. axis: None or int or tuple of ints, optional Axis or axes along which a sum is performed. The default (axis=None) is perform a su...
numpy.floor_divide(x1, x2,args, kwargs)Return the largest integer smaller or equal to the division of the inputs. numpy.power numpy.power(x1, x2,args, kwargs)First array elements raised to powers from second array, element-wise.
Thesum()function returns the sum of array elements Example 1: sum() With 2-D Array Theaxisargument defines how we can find the sum of elements in a 2-D array. Ifaxis=None, the array is flattened and the sum of the flattened array is returned. Ifaxis=0, the sum is calculated colum...
importnumpyasnp# 创建一个 numpy 数组array=np.array([1,2,3,4,5])# 计算所有元素的和sum_of_elements=np.sum(array)# 转换为整数result=int(sum_of_elements)print(result)# 输出: 15 Python Copy Output: 示例代码 3: 计算数组所有元素的平均值并转换为整数 ...
numpy.sum(a, axis=None, dtype=None, out=None, keepdims= Parameters: a :array_like Elements to sum. axis :None or int or tuple of ints, optional Axis or axes along which a sum is performed. The default, axis=None, will sum all of the elements of the input array. If axis is neg...
Example 1: Sum of All Values in NumPy ArrayThe following code demonstrates how to calculate the sum of all elements in a NumPy array.For this task, we can apply the sum function of the NumPy library as shown below:print(np.sum(my_array)) # Get sum of all array values # 21...
arr = np.array([2, 1, 3, 2, 1, 4, 5, 4]) # Get the unique elements of the array unique_values = np.unique(arr) [1 2 3 4 5] numpy.fft:傅里叶变换的函数。 numpy.ma:供对掩码数组的支持。 numpy.ma.array:从现有的数组或序列创建一个掩码数组。 numpy.ma.masked_array:从现有数组...
print ("Array with first 2 rows and" " alternate columns(0 and 2):\n", sliced_arr) #打印元素 #specific Indices Index_arr = arr[[1, 1, 0, 3], [3, 2, 1, 0]] print ("\nElements at indices (1, 3), " "(1, 2), (0, 1), (3, 0):\n", Index_arr) ...
rand_array += rand_array # 矩阵对应元素相加 print(rand_array) print(rand_array.dtype) # array的data type print(rand_array.ndim) # 返回数组的维数,也就是行数 # 把列表转换为矩阵 a = [1, 2, 3, 4] print(a) array = np.array(a, dtype=np.int32) ...