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

巴特西

python开发笔记-DataFrame的使用

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