```python
import numpyarr = numpy.array([[1,2,3,4],[5,6,7,8]])
print(arr)
print(arr[1, 2])
print(arr.ndim)# rank 维度数
print(arr.shape)# rows, columns 行列数
print(arr.size)# number of element 元素个数
print(type(arr))
# help(numpy.array)# print(numpy.ones(3, 2))# float 1填充
# print(numpy.zeros(3, 4))
print(numpy.random.random(3))# array of random value [0.0, 1.0)
print(numpy.random.random_sample((3, 2)) # 三行两列 [0.0, 1.0)
print(numpy.full((3, 3), 12))# new_arr 12填充
print(numpy.full((3, 3), 12, dtype=numpy.float32)) # 指定数值类型
a = arr.copy()# # numpy.loadtxt('')# load from file
# numpy.save(a, '')# save to fileprint(numpy.arange(0, 10, 2))# int同range函数
print(numpy.linspace(0, 10, 6))# float[0,10]等分取6个元素0,2,4,6,8,10
# arr.resize(4, 2)# resize return None 就地修改
# numpy.resize(arr, (4, 2))# 返回新的arr
print(arr.reshape(2, 4))# resize return new_arr
print(arr.ravel())# flattened array return new_arr 扁平化
print(arr.transpose())# transpose an array return new_arr
print(arr[0:1:100])# start, end, step 行切片
print(arr[:, 2])# columns 列切片
print(arr[..., 0:2])# columns 列切片
print(arr[0:2, 0:2])# rows, columns, 行列切片# operations + - * / % ** < == >
# add, subtract, multiply, divide, remainder, power
print(numpy.dot(a.reshape(4, 2), [1, 0]))**dot运算**: 二维行去dot列, columns1 = rows2
# dot operation is not commutativeA . B != B . A
print(arr + numpy.array(10))# have same shape otherwise broadcast 广播
print(numpy.array(10) + numpy.ones((3, 2)))# boardcast
aa[:, 0:1] += numpy.ones((4, 1), dtype=int)
print(numpy.exp(n))# e**n , e = 2.718281828459045
print(numpy.exp(arr))# x *= e
print(numpy.square(arr))# x**2
print(numpy.sqrt(arr))# x**(1/2)
print(numpy.around(1.5))# Evenly round to the given number of decimals. 四舍六入五取偶
print(numpy.trunc(1.5))# trunc截断, 类似int的操作, 返回float, 1.0
print(numpy.floor(-1.5))# float(floor)math.floor + 0.0
print(numpy.ceil(-1.5))# float(ceil)math.ceil + 0.0
print(numpy.log(arr))# log(x)
print(numpy.sum(arr, axis=1), numpy.max(arr), numpy.min(arr))
# axis=1 rows sum 行求和,axis=0 columns sum列求和
print(numpy.cumsum(arr, axis=1))# cumulative sum 累加
print(numpy.mean(arr))# mean value,average 平均数
print(numpy.median(arr))# median 中位数, 从大到小排序取最中间位置的数, 或者中间两个数的平均值
```【Python|Numpy简单使用】
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