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Application of time date correlation - datetime64 numpy.busday_offset (dates, offsets, roll='raise', weekmask='1111100', holidays=None, busdaycal=None, out=None) First adjusts the date to fall on a valid day according to the roll rule, then applies offsets to the given dates counted in valid days. This function is used to determine wheth ...

Import numpy and view version import numpy as np np.__version__ '1.13.1' What is numpy? That is, Numeric Python. After expansion, python can support array and matrix types, including a large number of matrix and array calculation functions Numpy framework is the basis of machine learning and data mining. pandas, scipy and matplotli ...

brief introduction The broadcast describes how NumPy calculates the operation between arrays of different shapes. If it is a larger matrix and a smaller matrix, the smaller matrix will be broadcast to ensure the correct operation. This article will explain in detail the use of broadcast in NumPy with specific examples. Basic broadcasting ...

numpy exercises This article is only for my study notes and is deleted The title comes from https://github.com/nndl/nndl.github.io array operation of numpy 1. Import numpy Library import numpy as np 2. Create a one-dimensional array A and initialize it to [4,5,6], (1) output the type of a, (2) output the size of each dimension of a, (3) ...

introduction Array index refers to the use of square brackets ([]) to index a set of values. The most familiar indexing method is single element indexing. In addition, this paper will also introduce the index method of array slice, as well as index array, Boolean index group and structure index tool. 1. Single element index Note: the sta ...

Vectorization of code means that the problem to be solved is vectorized in essence. It only needs some numpy skills to make the code run faster, but vectorization is not very easy. Vectorization code example: game of life The universe of life game is a two-dimensional orthogonal grid. Each grid (cell) is in two possible states, life or death. ...

brief introduction This article will explain the basic data types Series and DataFrame in Pandas, and explain in detail the creation, indexing and other basic behaviors of these two types. To use Pandas, you need to reference the following lib: In [1]: import numpy as np In [2]: import pandas as pd Series Series is a one-dimensional ...

Article catalog 1. Learning objectives 2. Operation explanation 3. Job results 1. Learning objectives Understand simple and logarithmic returnsCalculate the return on investment for different stocks through Pandas and NumPyCalculate the return of the portfolio by linear summation 2. Operation explanation Starting from this task, we wi ...

preface Viewing official documents is the most effective way to learn: https://pandas.pydata.org/pandas-docs/stable/user_guide/10min.html#selection Only the relevant content of '10min to understand pandas' is posted here for review and consolidation. It is said that numpy and pandas are the basis of python data analysis. You must master th ...

1, Import common libraries import pandas as pd import numpy as np import matplotlib.pyplot as plt 2, Create object (1) By passing a list to create a Series, pandas will create an integer index by default The code is as follows: s = pd.Series([1, 3, 5, np.nan, 6, 8]) print(s) The operation results are as follows: 0 1.0 1 3.0 ...