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