pandas库Series使用和ix、loc、iloc基础用法

2023-08-14 04:48| 来源: 网络整理| 查看: 265

1. pandas库Series基础用法：

直接贴出用例：

1. 构造/初始化Series的3种方法：

（1）用列表list构建Series

import pandas as pd my_list=[7,'Beijing','19大',3.1415,-10000,'Happy'] s=pd.Series(my_list) print(type(s)) print(s) 0 7 1 Beijing 2 19大 3 3.1415 4 -10000 5 Happy dtype: object

pandas会默认用0到n来做Series的index,但是我们也可以自己指定index,index可以理解为dict里面的key

s=pd.Series([7,'Beijing','19大',3.1415,-10000,'Happy'], index=['A','B','C','D','E','F']) print(s) A 7 B Beijing C 19大 D 3.1415 E -10000 F Happy dtype: object

（2）用字典dict来构建Series，因为Series本身其实就是key-value的结构

cities={'Beijing':55000,'Shanghai':60000,'shenzhen':50000,'Hangzhou':20000,'Guangzhou':45000,'Suzhou':None} apts=pd.Series(cities,name='income') print(apts) Beijing 55000.0 Guangzhou 45000.0 Hangzhou 20000.0 Shanghai 60000.0 Suzhou NaN shenzhen 50000.0 Name: income, dtype: float64

（3）用numpy array来构建Series

import numpy as np d=pd.Series(np.random.randn(5),index=['a','b','c','d','e']) print(d) a -0.329401 b -0.435921 c -0.232267 d -0.846713 e -0.406585 dtype: float64

以上还是比较容易理解的。

2. Series选择数据

（1）可以像对待一个list一样对待一个Series,完成各种切片的操作

import pandas as pd cities={'Beijing':55000,'Shanghai':60000,'shenzhen':50000,'Hangzhou':20000,'Guangzhou':45000,'Suzhou':None} apts=pd.Series(cities,name='income') print('apts:\n',apts) print('apts[3]:\n',apts[3]) print('apts[[3,4,1]]:\n',apts[[3,4,1]]) print('apts[:-1]:\n',apts[:-1]) print('apts[1:]+apts[:-1]:\n',apts[1:]+apts[:-1]) apts: Beijing 55000.0 Shanghai 60000.0 shenzhen 50000.0 Hangzhou 20000.0 Guangzhou 45000.0 Suzhou NaN Name: income, dtype: float64 apts[3]: 20000.0 apts[[3,4,1]]: Hangzhou 20000.0 Guangzhou 45000.0 Shanghai 60000.0 Name: income, dtype: float64 apts[:-1]: Beijing 55000.0 Shanghai 60000.0 shenzhen 50000.0 Hangzhou 20000.0 Guangzhou 45000.0 Name: income, dtype: float64 apts[1:]+apts[:-1]: Beijing NaN Guangzhou 90000.0 Hangzhou 40000.0 Shanghai 120000.0 Suzhou NaN shenzhen 100000.0 Name: income, dtype: float64

（2）Series可以用来选择数据

（3）和numpy很像，可以使用numpy的各种函数mean,median,max,min

import pandas as pd cities={'Beijing':55000,'Shanghai':60000,'shenzhen':50000,'Hangzhou':20000,'Guangzhou':45000,'Suzhou':None} apts=pd.Series(cities,name='income') less_than_50000=(apts'Beijing':55000,'Shanghai':60000,'shenzhen':50000,'Hangzhou':20000,'Guangzhou':45000,'Suzhou':None} apts=pd.Series(cities,name='income') apts['shenzhen']=70000 less_than_50000=(apts

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