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MyTT MyTT is a Swiss Army knife in your quantitative toolbox. It is refined and efficient. It simply transplants the indicator formula indicators such as tongdaxin, tonghuashun, Mandarin Chinese and wheat language into Python. The core library is a single file with only 100 lines of code. It implements and converts all common indicators of ton ...

Time series analysis - missing value processing This article is based on the article of Zhihu boss Cleaning data Data cleaning is an important part of data analysis, and time series data is no exception. This section will introduce the data cleaning methods for time series data in detail. Missing value processingChange time and frequencySmo ...

Numpy can be said to be an important foundation for Python's application to artificial intelligence and scientific computing. I will not repeat the introduction of the library. I mainly share some summarized usage of numpy library. 1. numpy array object The multidimensional array in Numpy is called ndarray, which is the most common array obje ...

Article catalog 1. Mining background and objectives2.2 data exploration and preprocessing * 2.1 Data filtering 2.2 data De duplication2.3 delete prefix score2.4 jieba participle 3 subject analysis based on LDA model4. Weight5. How to compare the similarity between two documents in the topic space This paper is based on the data of Chapte ...

Raw data set python code Edit with Jupiter notebook import pandas as pd import matplotlib.pyplot as plt plt.rcParams['font.sans-serif']=['SimHei'] data = pd.read_excel(r'E:\a business\Data center station\E-commerce cases\Download source data\order.xlsx') data.info() data.sample(10) Operation results: It can be seen from the observation ...

This paper makes a visual data analysis of stock data. (tushare ID: 452043) Introduction to tushareData crawlingData visualization analysis 3.1. Trend in recent three years 3.2. Maximum range of stock points 3.3. Daily low point analysis 3.4. High and low point analysissummary Code part 1. Introduction to tushare Tushare is a free and o ...

↑ ↑ ↑ follow the "Star" Datawhale Daily dry goods& Team learning every month , don't miss it Datawhale dry Author: Chen Kai, member of Datawhale, Sun Yat sen University Recently, many readers have left messages, hoping to have a complete data analysis project to practice. I have collected the recommendations o ...

Content introduction Abnormal data are often encountered in daily data analysis, that is, data beyond a specific area or range is usually defined as abnormal or "noise", also known as outliers. This paper introduces the visualization and processing routine of data outliers in daily work. Distinguish true and false exceptions J ...

Before you start, import numpy and pandas.   import numpy as np import pandas as pd Load all the data in the data folder and observe the relationship between the data. trlu = pd.read_csv('C://Users/22774/Desktop/data/train-left-up.csv') trru = pd.read_csv('C://Users/22774/Desktop/data/train-right-up.csv') trld = pd.read_csv('C://Users/227 ...

catalogue Array creation 1. Create ndarray based on existing data (a) It is created through the array() function. (b) It is created through the asarray() function (c) It is created through the fromfunction() function 2. Fill according to ones and zeros (a) Zero array (b) 1 array (c) Empty array (d) Unit array (e) Diagonal array (f) ...