Python uses NumPy to read and write array files, including text files, binary files, CSV files, etc

Preparation work: Before using NumPy to read and write array files, we need to first build the corresponding environment and download the necessary class libraries. Environmental construction: 1. Install Python: If you haven't already installed Python, you can download it from the official website（ https://www.python.org/downloads/ ）Download and install the latest version of Python. 2. Install NumPy: Open a command line window and execute the following command to install NumPy: pip install numpy 3. Install Pandas: Open a command line window and execute the following command to install Pandas: pip install pandas Dataset download: In this example, we will use an example dataset called iris.csv. You can download and save as an iris.csv file from the following website. Dataset download website: https://archive.ics.uci.edu/ml/datasets/iris Sample data description: Iris.csv is a commonly used machine learning dataset that contains 150 rows and 4 columns of data. Each row represents a sample, with the first four columns representing feature data and the last column representing categories. We will read this data from the file and write it to files in different formats. The following is the complete sample code: python import numpy as np import pandas as pd #Read Text File data_txt = np.loadtxt('iris.csv', delimiter=',', skiprows=1) Print ('Read text file: ') print(data_txt) #Write Text File np.savetxt('iris.txt', data_txt, delimiter=',') #Read binary files data_binary = np.fromfile('iris.csv', dtype=float, sep=',', count=-1) print(' Read binary file: ') print(data_binary) #Write binary file data_binary.tofile('iris.bin') #Read CSV file data_csv = pd.read_csv('iris.csv') print(' Reading CSV file: ') print(data_csv) #Write CSV file data_csv.to_csv('iris_new.csv', index=False) In the above code, we implemented read and write operations for text files, binary files, and CSV files using NumPy. We first used the 'np. loadtxt ()' function to read the iris. csv file, specifying the separator as', 'and skipping the header of the first line. Then use the 'np. savetxt ()' function to write the read data into the iris.txt file. Next, we used the 'np. fromfile()' function to read the binary file and the 'tofile()' function to write the data to the iris. bin file. Finally, we use the 'read' in the Pandas library_ The csv() function reads a CSV file and uses' to '_ The csv() function writes data to iris_ In the new.csv file. The above is the complete sample code for reading and writing array files using NumPy.