python pandas series

The pandas Series is much more powerful than the numpy array , in many waysFirst, the pandas Series has some methods, such as:The describe method can give some analysis data of Series :Import= PD. Series ([1,2,3,4]) d = s.describ

This article describes how the pandas series with the index index is vectorized:1. Index indexed arrays are the same:S1 = PD. Series ([1, 2, 3, 4], index=['a','b','C','D']) S2= PD. Series ([ten, +, +], index=['a','b','C','D'])PrintS1 +s2a11b22C33D44Dtype:int64Add the values corresponding to each index directly2. Index

Import Pandasimport Pandas as PDCountries = ['Albania','Algeria','Andorra','Angola','Antigua and Barbuda', 'Argentina','Armenia','Australia','Austria','Azerbaijan', 'Bahamas','Bahrain','Bangladesh','Barbados','Belarus', 'Belgium','Belize','Benin','Bhutan','Bolivia']life_expectancy_values= [74.7, 75., 83.4, 57.6, 74.6, 75.4, 72.3, 81.5, 80.2, 70.3, 72.1, 76.4, 68.1, 75.2, 69.8, 79.4, 70.8, 62

First of all, for those unfamiliar with Pandas, Pandas is the most popular data analysis library in the Python ecosystem. It can accomplish many tasks, including: Read/write data in different formats Select a subset of data Cross-row/column calculations Find and fill in missing data Apply actions in a separate group of data Reshape da

Data conversionDelete duplicate elements　　The duplicated () function of the Dataframe object can be used to detect duplicate rows and return a series object with the Boolean type. Each element pairsshould be a row, if the row repeats with other rows (that is, the row is not the first occurrence), the element is true, and if it is not repeated with the preceding, the metaThe vegetarian is false.A Series obje

The following for you to share a Python data Analysis Library Pandas basic operation method, has a good reference value, I hope to help you. Come and see it together. What is Pandas? Is it it? 。。。。 Apparently pandas is not so cute as this guy .... Let's take a look at how Pandas's official website defines itself:

The pandas of Python is simply introduced and used Introduction of Pandas 1. The Python data analysis Library or pandas is a numpy based tool that is created to resolve data profiling tasks. Pandas incorporates a large number of

PandasPandas is a popular open source Python project that takes the name of panel data and Python data analysis.Pandas has two important data structures: Dataframe and seriesThe dataframe of PANDAS data structurePandas's DATAFRAME data structure is a tagged two-dimensional object that is very similar to Excel spreadsheets or relational data tables.You can create

I. Introduction of PANDAS1. The Python data analysis Library or pandas is a numpy-based tool that is created to resolve data analytics tasks. Pandas incorporates a number of libraries and a number of standard data models, providing the tools needed to efficiently manipulate large datasets. Pandas provides a number of f

How to quickly get started using Python for financial data analysisIntroduction:This series of posts "quantitative small classroom", through practical cases to teach beginners to use Python, pandas for financial data processing, hope to be helpful to the big home." must -read article": "10 400 times-fold strategy shari

This article describes how to use the pandas library in Python to analyze cdn logs. It also describes the complete sample code of pandas for cdn log analysis, then we will introduce in detail the relevant content of the pandas library. if you need it, you can refer to it for reference. let's take a look at it. Preface

This article mainly introduces how to use Python pandas framework to operate data in Excel files, including basic operations such as unit format conversion and classification and Summarization. For more information, see Introduction The purpose of this article is to show you how to use pandas to execute some common Excel tasks. Some examples are trivial, but I t