pandas series to np array

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

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.

:6]# results: 3 562.9876854 13495.1274665 9388.688523dtype:float64(2) Cycle: for inch life_expectancy: Print ' examining life expectancy {} '. Format (country_life_expectancy)# results...Examining life expectancy 70.6(3) commonly used functions:Print Life_expectancy.mean () # Find Average# resultsPrint life_expectancy.std () # ask for standard deviation# resultsPrint # Ask for maximum value# resultsprint gdp.sum () # results182957.59833(4) Vectorization operatio

Using Python for data analysis (7)-pandas (Series and DataFrame), pandasdataframe 1. What is pandas? Pandas is a Python data analysis package based on NumPy for data analysis. It provides a large number of advanced data structures and data processing methods. Pandas has two

The difference between resample and GroupBy:Resample: Resampling within a given time unitGroupBy: Statistics on a given data entryFunction Prototypes:Dataframe.resample (rule, How=none, axis=0, Fill_method=none, Closed=none, Label=none, convention= ' start ', Kind=None, Loffset=none, Limit=none, base=0)Where the parameters are deprecated.Let's start practicing.Import NumPy as NP import Pandas as PDStart by

span generation date range, Pd.date_range () can generate a specified length of datetimeindex, parameters can be the start end date result = Pd.date_range (' 00:00 ', ' 12:00 ', freq= ' 1h20min ') result = Pd.date_range (' 20100101 ', ' 20100601 ', freq= ' M ') ran = Pd.period_range (' 2010-01 ', ' 2010-05 ', freq= ' M ') p = pd. Period (freq= ' M ') print P + 2 6 time series data aggregation processing dates = PD. Datetimeindex ([' 2017-01-01 ', ' 2

This question mainly writes the method of sorting series and dataframe according to index or value Code: #coding =utf-8 Import pandas as PD import numpy as NP #以下实现排序功能. SERIES=PD. Series ([3,4,1,6],index=[' B ', ' A ', ' d ', ' C ']) FRAME=PD. Dataframe ([[2,4,1,5],[3,1,4,