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brief introduction We know that there are four types of numbers in Python, namely int, float, bool and complex. As a scientific computing NumPy, its data types are more abundant. Today, I will explain the data types in NumPy in detail. Data type in array NumPy is implemented in C language. We can compare the data types in the array in N ...

1, Vectorization and broadcasting The concepts of vectorization and broadcasting are the basis of numpy's internal implementation. With vectorization, you don't need to use explicit loops when writing code. These loops can not be omitted, but are implemented internally and replaced by other structures in the code. The application of vectorizat ...

datetime64 Foundation In numpy, we can easily convert the string to the time date type datetime64 (datetime has been occupied by the date time library contained in python). datatime64 is a date time type with units as follows: [example] when creating datetime64 type from string, by default, numpy will automatically select the corresponding ...

explain This article will not introduce all array functions and will not explain all parameters. For details, please refer to the official documents.Parameters with square brackets [] can be omitted.The output of each small piece of code is written in the comments below. 1, Array creation 1.1 create an array using existing data function ...

1.reshape reshape is reshaping. Three commonly used expressions are as follows: numpy.arange(n).reshape(a, b) # n natural numbers are generated in turn and displayed in the form of an array of rows a and columns b numpy.arange(a,b,c) # Starting from the number a, the step is c, and ending at b, the array is generated numpy.ara ...

Baidu cloud link of the file used in this article: Link: https://pan.baidu.com/s/15-qbrbtRs4frup24Y1i5og Extraction code: pm2c linear prediction Assuming that a set of data conforms to a linear law, we can predict the data that will appear in the future a b c d e f g h .... ax + by + cz = d bx + cy + dz = e cx + dy + ez = f In ...

Jupyter notebook is used in this article, so numpy is only introduced at the beginning and not later. If it is run in other compilers, please ensure that numpy is introduced 1 create array import numpy as np 1.1 using array() to import vectors vector = np.array([1, 2, 3, 4]) vector array([1, 2, 3, 4]) 1.2 numpy.array() can als ...

Introduction to Numpy NumPy is the basic package of scientific computing in Python. It is a python library, which provides a multi-dimensional array object, various derived objects (such as masked arrays and matrices), and various routines for fast operation of arrays, including mathematics, logic, shape operation, sorting, selection, I/O, di ...

Image graying What is image graying? Image graying is not to turn a simple image into gray, but to integrate the BGR channels of the image with a certain law to make the image display bit gray. The rules are as follows: Manual graying First, we use manual graying: The idea is: First create a blank picture with the same length and width as ...

Chapter II NumPy foundation 1 The input and output in the sample code in this chapter come from the IPython session. 2.1 NumPy array object ndarray in NumPy is a multidimensional array object, which consists of two parts: Actual data;Metadata describing these data. Most array operations only modify the metadata without changing the underly ...