DataFrame定义：

DataFrame是pandas的两个主要数据结构之一，另一个是Series

—一个表格型的数据结构

—含有一组有序的列

—大致可看成共享同一个index的Series集合

DataFrame创建方式：

默认方式创建：

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

name pay

0 Wangdachui4000

1 Linling 5000

2 Niuyun 6000

传入索引的方式创建：

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

name pay1 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)

DataFrame的基本操作：

取DataFrame对象的行和列

>>> frame

name pay

1 Wangdachui 4000

2 Linling 5000

3 Niuyun 6000

>>> frame['name']1Wangdachui2Linling3Niuyun

Name: name, dtype: object>>>frame.pay1 4000

2 5000

3 6000Name: pay, dtype: object

取特定的行或列

>>> frame.iloc[:2,1]#取第0,1行的第1列1 4000

2 5000Name: pay, dtype: object>>> frame.iloc[:1,0]#取第0行的第0列1Wangdachui

Name: name, dtype: object>>> frame.iloc[2,1]#取第2行的第1列'6000'

>>> frame.iloc[2]#取第2行

name Niuyun

pay6000Name:3, dtype: object

DataFrame对象的修改和删除

>>> frame['name']= 'admin'

>>>frame

name pay1 admin 4000

2 admin 5000

3 admin 6000

>>> del frame['pay']>>>frame

name1admin2admin3 admin

DataFrame的统计功能

找最低工资和工资大于5000的人

>>>frame

name pay1 Wangdachui 4000

2 Linling 5000

3 Niuyun 6000

>>>frame.pay.min()'4000'

>>> frame[frame.pay >= '5000']

name pay2 Linling 5000

3 Niuyun 6000

案例：

已知有一个列表中存放了一组音乐数据：

music_data = [("the rolling stones","Satisfaction"),("Beatles","Let It Be"),("Guns N'Roses","Don't Cry"),("Metallica","Nothing Else Matters")]，请根据这组数据创建一个如下的DataFrame:

singer         song_name

1   the rolling stones         Satisfaction

2   Beatles                        Let It Be

3   Guns N'Roses 　　    Don't Cry

4   Metallica                      Nothing Else Matters

方法如下：

>>> import pandas as pd

>>> music_data = [("the rolling stones","Satisfaction"),("Beatles","Let It Be"),("Guns N'Roses","Don't Cry"),("Metallica","Nothing Else Matters")]

>>> music_table = pd.DataFrame(music_data)

>>> music_table

0 1

0 the rolling stones Satisfaction

1 Beatles Let It Be

2 Guns N'Roses Don't Cry

3 Metallica Nothing Else Matters

>>> music_table.index = range(1,5)

>>> music_table.columns = ['singer','song_name']

>>> print(music_table)

singer song_name

1 the rolling stones Satisfaction

2 Beatles Let It Be

3 Guns N'Roses Don't Cry

4 Metallica Nothing Else Matters

DataFrame基本操作补充

DataFrame对象如下：

>>>frame

name pay1 Wangdachui 4000

2 Linling 5000

3 Niuyun 6000

(1)添加列

添加列可以直接赋值，例如给frame添加tax列：

>>> frame['tax'] = [0.05,0.05,0.1]>>>frame

name pay tax1 Wangdachui 4000 0.05

2 Linling 5000 0.05

3 Niuyun 6000 0.10

(2)添加行

添加行可以用loc(标签)和iloc(位置)索引，也可以用append()和concat()方法，这里用loc()方法

>>> frame.loc[5] = {'name':'Liuxi','pay':5000,'tax':0.05}>>>frame

name pay tax1 Wangdachui 4000 0.05

2 Linling 5000 0.05

3 Niuyun 6000 0.10

5 Liuxi 5000 0.05

(3)删除对象元素

删除数据可直接用“del数据”的方式进行，但这种方式是直接对原始数据操作，不安全，可利用drop()方法删除指定轴上的数据

>>> frame.drop(5)

name pay tax1 Wangdachui 4000 0.05

2 Linling 5000 0.05

3 Niuyun 6000 0.10

>>> frame.drop('tax',axis = 1)

name pay1 Wangdachui 4000

2 Linling 5000

3 Niuyun 6000

5 Liuxi 5000

此时frame没有受影响

>>>frame

name pay tax1 Wangdachui 4000 0.05

2 Linling 5000 0.05

3 Niuyun 6000 0.10

5 Liuxi 5000 0.05

(4)修改

继承上面的frame，对tax统一修改成0.03

>>> frame['tax'] = 0.03

>>>frame

name pay tax1 Wangdachui 4000 0.03

2 Linling 5000 0.03

3 Niuyun 6000 0.03

5 Liuxi 5000 0.03

也可以直接用loc()修改

>>> frame.loc[5] = ['Liuxi',9800,0.05]>>>frame

name pay tax1 Wangdachui 4000 0.03

2 Linling 5000 0.03

3 Niuyun 6000 0.03

5 Liuxi 9800 0.05