Numpy:數組創建、數組基本屬性
阿新 • • 發佈:2019-01-23
shape array數組 tro range 個數 二維數組 numpy 二維 類型
Numpy數組創建
import numpy as np ‘‘‘ numpy中的ndarray數組 ‘‘‘ ary = np.array([1, 2, 3, 4, 5]) print(ary) ary = ary * 10 print(ary) ‘‘‘ ndarray對象的創建 ‘‘‘ # 創建二維數組 # np.array([[],[],...]) a = np.array([[1, 2, 3, 4], [5, 6, 7, 8]]) print(a) # np.arange(起始值, 結束值, 步長(默認1)) b = np.arange(1, 10, 1) print(b) # np.zeros(數組元素個數, dtype=‘數組元素類型‘)c = np.zeros(10) print(c, ‘; c.dtype:‘, c.dtype) # np.ones(數組元素個數, dtype=‘數組元素類型‘) d = np.ones(10, dtype=‘int64‘) print(d, ‘; d.dtype:‘, d.dtype)
Numpy的ndarray對象屬性:
數組的維度:array.shape
元素的類型:array.dtype
數組元素的個數:array.size
數組的索引(下標):array[0]
‘‘‘ 數組的基本屬性 ‘‘‘ a = np.array([[1, 2, 3], [4, 5, 6]]) print(a)
# 測試數組的基本屬性 print(‘a.shape:‘, a.shape) # a.shape = (6, ) # 此格式可將原數組結構變成1行6列的數據結構 # print(a, ‘a.shape:‘, a.shape) print(‘a.size:‘, a.size) print(‘len(a):‘, len(a)) # 數組元素的索引 ary = np.arange(1, 28) ary.shape = (3, 3, 3) # 創建三維數組 print(ary, ‘; ary.shape:‘, ary.shape) print(‘ary[0]:‘, ary[0]) print(‘ary[0][0]:‘, ary[0][0]) print(‘ary[0][0][0]:‘, ary[0][0][0]) print(‘ary[0,0,0]:‘, ary[0, 0, 0]) # 遍歷三維數組 for i in range(ary.shape[0]): for j in range(ary.shape[1]): for k in range(ary.shape[2]): print(ary[i, j, k], end=‘ ‘)
Numpy:數組創建、數組基本屬性