python數據類型之pandas—DataFrame

DataFrame定義：

DataFrame是pandas的兩個主要數據結構之一，另一個是Series

—一個表格型的數據結構

—含有一組有序的列

—大致可看成共享同一個index的Series集合

DataFrame創建方式：

默認方式創建：

>>> 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

傳入索引的方式創建：

>>> 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)

DataFrame的基本操作：

取DataFrame對象的行和列

  >>> frame
  name pay
  1 Wangdachui 4000
  2 Linling 5000
  3 Niuyun 6000

>>> frame['name']
1    Wangdachui
2       Linling
3        Niuyun
Name: name, dtype: object

>>> frame.pay
1    4000
2    5000
3    6000
Name: 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    5000
Name: pay, dtype: object
>>> frame.iloc[:1,0]#取第0行的第0列
1    Wangdachui
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
pay       6000
Name: 3, dtype: object

DataFrame對象的修改和刪除

>>> frame['name']= 'admin'
>>> frame
    name   pay
1  admin  4000
2  admin  5000
3  admin  6000

>>> del frame['pay']
>>> frame
    name
1  admin
2  admin
3  admin

DataFrame的統計功能

找最低工資和工資大於5000的人

>>> 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

案例：

已知有一個列表中存放了一組音樂數據：

music_data = [("the rolling stones","Satisfaction"),("Beatles","Let It Be"),("Guns N'Roses","Don't Cry"),("Metallica","Nothing Else Matters")]，請根據這組數據創建一個如下的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基本操作補充

DataFrame對象如下：

>>> frame
         name   pay
1  Wangdachui  4000
2     Linling  5000
3      Niuyun  6000

（1）添加列

添加列可以直接賦值，例如給frame添加tax列：

>>> frame['tax'] = [0.05,0.05,0.1]
>>> frame
         name   pay   tax
1  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（標簽）和iloc（位置）索引，也可以用append（）和concat（）方法，這里用loc（）方法

>>> frame.loc[5] = {'name':'Liuxi','pay':5000,'tax':0.05}
>>> frame
         name   pay   tax
1  Wangdachui  4000  0.05
2     Linling  5000  0.05
3      Niuyun  6000  0.10
5       Liuxi  5000  0.05

（3）刪除對象元素 

刪除數據可直接用“del數據”的方式進行，但這種方式是直接對原始數據操作，不安全，可利用drop()方法刪除指定軸上的數據

>>> frame.drop(5)
         name   pay   tax
1  Wangdachui  4000  0.05
2     Linling  5000  0.05
3      Niuyun  6000  0.10

>>> frame.drop('tax',axis = 1)
         name   pay
1  Wangdachui  4000
2     Linling  5000
3      Niuyun  6000
5       Liuxi  5000

此時frame沒有受影響

>>> frame
         name   pay   tax
1  Wangdachui  4000  0.05
2     Linling  5000  0.05
3      Niuyun  6000  0.10
5       Liuxi  5000  0.05

（4）修改

繼承上面的frame，對tax統一修改成0.03

>>> frame['tax'] = 0.03
>>> frame
         name   pay   tax
1  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   tax
1  Wangdachui  4000  0.03
2     Linling  5000  0.03
3      Niuyun  6000  0.03
5       Liuxi  9800  0.05