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Arrays are used in a Multiple values are stored in variables. Python does not have built-in support for arrays, but Python lists can be used instead.
Example:
arr = [1, 2, 3, 4, 5] arr1 = ["geeks", "for", "geeks"]
# 用于创建数组的 Python 程序 # 使用列表创建数组 arr=[1, 2, 3, 4, 5] for i in arr: print(i)
Output:
1
2
3
4
5
array(data type, value list) The function is used to create an array, specified in its parameters List of data types and values.
Example:
# 演示 array() 工作的 Python 代码 # 为数组操作导入“array” import array # 用数组值初始化数组 # 用有符号整数初始化数组 arr = array.array('i', [1, 2, 3]) # 打印原始数组 print ("The new created array is : ",end="") for i in range (0,3): print (arr[i], end=" ") print ("\r")
Output:
##The new created array is : 1 2 3 1 5Creating arrays using numpy methodsNumPy provides several functions to create arrays with initial placeholder contents. These minimize the need to grow the array, which is an expensive operation. For example: np.zeros, np.empty, etc.
numpy.empty(shape, dtype = float, order = 'C'): Returns a new array of the given shape and type, with random values.
# 说明 numpy.empty 方法的 Python 代码 import numpy as geek b = geek.empty(2, dtype = int) print("Matrix b : \n", b) a = geek.empty([2, 2], dtype = int) print("\nMatrix a : \n", a) c = geek.empty([3, 3]) print("\nMatrix c : \n", c)
Output:
Matrix b :[ 0 1079574528]
Matrix a :
[[0 0 ]
[0 0]]
Matrix a :
[[ 0. 0. 0.]
[ 0. 0. 0.]
[ 0. 0. 0 .]]
numpy.zeros(shape, dtype = None, order = 'C'): Returns a new array of the given shape and type, with zeros.
# 说明 numpy.zeros 方法的 Python 程序 import numpy as geek b = geek.zeros(2, dtype = int) print("Matrix b : \n", b) a = geek.zeros([2, 2], dtype = int) print("\nMatrix a : \n", a) c = geek.zeros([3, 3]) print("\nMatrix c : \n", c)
Output:
Matrix b :Reshape the arrayWe can use the[0 0]
Matrix a :
[[0 0 ]
[0 0]]
Matrix c :
[[ 0. 0. 0.]
[ 0. 0. 0.]
[ 0. 0. 0 .]]
reshape method to reshape the array. Consider an array of shape (a1, a2, a3, ..., aN). We can reshape and convert it into another array of shape (b1, b2, b3, ..., bM).
numpy.reshape(array, shape, order = 'C'): Reshape the array without changing the array data .
# 说明 numpy.reshape() 方法的 Python 程序 import numpy as geek array = geek.arange(8) print("Original array : \n", array) # 具有 2 行和 4 列的形状数组 array = geek.arange(8).reshape(2, 4) print("\narray reshaped with 2 rows and 4 columns : \n", array) # 具有 2 行和 4 列的形状数组 array = geek.arange(8).reshape(4 ,2) print("\narray reshaped with 2 rows and 4 columns : \n", array) # 构造 3D 数组 array = geek.arange(8).reshape(2, 2, 2) print("\nOriginal array reshaped to 3D : \n", array)
Output:
Original array :To create numerical sequences, NumPy provides a function similar to range, which returns an array instead of a list.[0 1 2 3 4 5 6 7]
array reshaped with 2 rows and 4 columns :
[[0 1 2 3]
[4 5 6 7]]
array reshaped with 2 rows and 4 columns :
[[0 1]
[2 3]
[4 5]
[6 7]]
Original array reshaped to 3D :
[[[0 1]
[2 3]]
[[4 5]
[6 7]]]
arange Returns uniformly distributed values within a given interval. StepThe length is specified.
linspace Returns uniformly distributed values within a given interval. The element numbered _ is returned.
arange([start,] stop[, step,][, dtype]): Returns an array with evenly spaced elements based on the interval. The intervals mentioned are half-open, i.e. [start, stop]
# 说明 numpy.arange 方法的 Python 编程 import numpy as geek print("A\n", geek.arange(4).reshape(2, 2), "\n") print("A\n", geek.arange(4, 10), "\n") print("A\n", geek.arange(4, 20, 3), "\n")
Output:
A[[0 1]
[2 3]]
A
[4 5 6 7 8 9]
A
[ 4 7 10 13 16 19]
numpy.linspace(start, stop, num = 50, endpoint = True, retstep = False, dtype = None): Returns numeric space evenly across intervals. Like arange but instead of step it uses sample numbers.
# 说明 numpy.linspace 方法的 Python 编程 import numpy as geek # 重新设置为 True print("B\n", geek.linspace(2.0, 3.0, num=5, retstep=True), "\n") # 长期评估 sin() x = geek.linspace(0, 2, 10) print("A\n", geek.sin(x))
Output:
B(array([ 2. , 2.25, 2.5 , 2.75, 3. ]), 0.25)
Flat array
A
[0. 929743]
: Returns a copy of the array folded into one dimension. # 说明 numpy.flatten() 方法的 Python 程序
import numpy as geek
array = geek.array([[1, 2], [3, 4]])
# 使用扁平化方法
array.flatten()
print(array)
#使用扁平化方法
array.flatten('F')
print(array)
[1, 2, 3, 4]
[1, 3, 2, 4]How to create an array in Numpy
Function
Description
empty()
Returns a new array of the given shape and type without initialization entry
empty_like()
Returns a new array with the same shape and type as the given array
eye()
Returns a two-dimensional array with 1 on the diagonal and 0 in other positions.
identity()
Returns the identity array
Returns an array of the same shape and type as the given arrayones()
Returns a given shape and type, filled with one_like()
Returns a new array of the given shape and type, filled with zeros
zeros()
Returns the same as given A given array has an array of zeros of the same shape and type
zeros_like()
Returns a full array of the same shape and type as the given array.
full_like()
Create an array
array()
Convert input to array
asarray()
Convert input to ndarray, but pass ndarray subclasses
asanyarray()
Returns a contiguous array in memory (C order)
ascontiguousarray()
Interprets input as a matrix
asmatrix()
Returns an array copy of the given object
copy()
Interprets the buffer as a one-dimensional array
frombuffer()
Construct an array from data in a text or binary file
fromfile()
By Execute a function on each coordinate to construct an array
fromfunction()
Create a new one-dimensional array from an iterable object
fromiter()
New one-dimensional array initialized from text data in string fromstring()
Load from text file Data
loadtxt()
Returns evenly spaced values within a given interval
arange()
Returns uniformly distributed numbers within the specified time interval
linspace()
Returns uniformly distributed numbers on a logarithmic scale
logspace()
Returns numbers uniformly distributed on a logarithmic scale (geometric series)
geomspace()
Return the coordinate matrix from the coordinate vector
meshgrid()
nd_grid instance, which returns a dense multi-dimensional "grid"
mgrid()
nd_grid instance, which returns an open multidimensional "meshgrid"
ogrid()
Extract diagonals Or construct a diagonal array
diag()
Create a two-dimensional array with flattened input as diagonal
diagflat()
An array with one at and below a given diagonal and zeros elsewhere tri()
Lower triangle of array
tril()
##triu() Upper triangle of array
vander() Generate Vandermonde matrix
##mat()
Interpret input as matrix
bmat()
Construct a matrix object from a string, nested sequence or array
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