In Python, an array is an important data structure that is used to store data elements of the same type. Unlike lists and tuples, arrays have a fixed length, and each element has the same data type.
This article will provide a comprehensive and in-depth introduction to the use of array in Python.
Basic concepts. In Python, array is a built-in data type that is used to store data elements of the same type.
The array has a fixed length, and each element has the same data type. Unlike lists and tuples, arrays do not support adding or removing elements on the fly.
How it was created. In Python, numpy is a commonly used scientific computing library that provides rich array manipulation functions. Arrays can be created using the array() function in numpy. For example:
import numpy as np arr = np.array([1, 2, 3, 4, 5]) creates an array of 5 integers
Common operations. Access Elements: Elements in an array can be accessed using an index. For example:
print(arr[0]) output: 1
Modify Elements: You can modify the elements in an array by using an index. For example:
arr[0] = 10 modifies the first element to 10
Slicing operations: Slices can be used to get subarrays in an array.
For example: sub arr = arr[1:4] Get a subarray from index 1 to index 3 (with the starting index, not the ending index).
Calculate the length of the array: You can use the len() function to get the length of the array. For example:
print(len(arr)) output: 5
Sorting: Use the sort() method to sort an array in situ. For example:
arr.sort() sorts the array in ascending order.
Maximum and minimum values: Use the max() and min() methods to get the maximum and minimum values in an array, respectively. For example:
max_val = arr.max() gets the maximum value in the array, min val = arrmin() to get the minimum value in the array.
Calculate the sum: Use the sum() method to calculate the sum of all the elements in the array. For example:
total = arr.sum() calculates the sum of all elements in the array.
These operations can greatly simplify the processing of the same type of data, making it more concise and efficient.
Summary. Overall, arrays in Python are a very useful data structure that helps us organize and manipulate data better.
By mastering the basic concepts and common operations of arrays, we can use Python for scientific computing and data analysis more efficiently.