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This article mainly introduces "numpy how to achieve direct reading from files to get array objects", in daily operation, I believe many people in numpy how to achieve direct reading from files to get array objects on the problem there are doubts, Xiaobian consulted all kinds of data, sorted out simple and easy to use operation methods, hope to answer "numpy how to achieve direct reading from files to get array objects" doubts helpful! Next, please follow the small series to learn together!

array object

#### numpy data read and write;

import numpy as npimport osos.chdir("D://python_script//")a = np.loadtxt("iris.data", dtype = float64, delimiter=',', usecols = [0, 1, 2, 3])print(a)b = np.loadtxt("iris.data", dtype = "S", delimiter=',', usecols = [4])print(b)for x in range(len(b)): print(a[x], "is ", b[0]) #Specify the data type, import data t = np.dtype([('sepal_length','f'),('sepal_width',' f'),('petal_length','f'),('petal_width',' f'),('class ',' S20')])a = np.loadtxt("iris.data", dtype = t, delimiter =',')print(a)r = np.savetxt("iris.csv", a, fmt='%3.1f:%3.1f:%3.1f:% s') At this point, the study of "numpy how to read array objects directly from files" is over, hoping to solve everyone's doubts. Theory and practice can better match to help everyone learn, go and try it! If you want to continue learning more relevant knowledge, please continue to pay attention to the website, Xiaobian will continue to strive to bring more practical articles for everyone!

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