python开发笔记-DataFrame的使用

   今天详细做下关于DataFrame的使用，以便以后自己可以翻阅查看

   DataFrame的基本特征：

1、是一个表格型数据结构

2、含有一组有序的列

3、大致可看成共享同一个index的Series集合

   

import pandas as pd  
>>> data={'name':['Wangdachui','Linling','Niuyun'],'pay':[4000,5000,6000]}  
>>> frame=pd.DataFrame(data)  
>>> frame  
         name   pay  
0  Wangdachui  4000  
1     Linling  5000  
2      Niuyun  6000  

　　

import pandas as pd  
>>> import numpy as np  
>>> data=np.array([('Wangdachui',4000),('Linling',5000),('Niuyun',6000)])  
>>> frame=pd.DataFrame(data,index=range(1,4),columns=['name','pay'])  
>>> frame  
         name   pay  
1  Wangdachui  4000  
2     Linling  5000  
3      Niuyun  6000  
>>> frame.index  
RangeIndex(start=1, stop=4, step=1)  
>>> frame.columns  
Index(['name', 'pay'], dtype='object')  
>>> frame.values  
array([['Wangdachui', '4000'],  
       ['Linling', '5000'],  
       ['Niuyun', '6000']], dtype=object)  

　　

frame.index=[2,4,6]  
>>> frame  
         name   pay  
2  Wangdachui  4000  
4     Linling  5000  
6      Niuyun  6000  　　

DataFrame的基本操作

· 取DataFrame对象的行和列可获得Series：

frame['name']  
2    Wangdachui  
4       Linling  
6        Niuyun  
Name: name, dtype: object  
>>> frame.pay  
2    4000  
4    5000  
6    6000  
Name: pay, dtype: object  
>>> frame.iloc[:2,1]  
2    4000  
4    5000  
Name: pay, dtype: object  

　　DataFrame对象的修改和删除：

  

frame['name']='admin'  
>>> frame  
    name   pay  
2  admin  4000  
4  admin  5000  
6  admin  6000  
>>> del frame['pay']  
>>> frame  
    name  
2  admin  
4  admin  
6  admin  

　　DataFrame的统计功能

   

import pandas as pd  
>>> import numpy as np  
>>> data=np.array([('Wangdachui',4000),('Linling',5000),('Niuyun',6000)])  
>>> frame=pd.DataFrame(data,index=range(1,4),columns=['name','pay'])  
>>> frame  
         name   pay  
1  Wangdachui  4000  
2     Linling  5000  
3      Niuyun  6000  
>>> frame.pay.min()  
'4000'  

　　

frame[frame.pay>='5000']  
      name   pay  
2  Linling  5000  
3   Niuyun  6000