pandas基础-Python3

 1 # Code based on Python 3.x
 2 # _*_ coding: utf-8 _*_
 3 # __Author: "LEMON"
 4 
 5 import pandas as pd
 6 
 7 d = pd.date_range(‘20170101‘, periods=7)
 8 aList = list(range(1,8))
 9 
10 df = pd.DataFrame(aList, index=d, columns=[‘ ‘])
11 df.index.name = ‘value‘
12 
13 print(‘----------df.index---------‘)
14 print(df.index)
15 
16 print(‘---------df.columns---------‘)
17 print(df.columns)
18 
19 print(‘----------df.values---------‘)
20 print(df.values)
21 
22 print(‘----------df.describe--------‘)
23 print(df.describe)
24 
25 print(‘----------information details--------‘)
26 print(df.head(2)) #获取开始的n条记录
27 print(df.tail(3)) #后去最后的n条记录
28 print(df[3:5])  # df[a:b]，获取第a+1至第b-1的记录

 1 ----------df.index---------
 2 DatetimeIndex([‘2017-01-01‘, ‘2017-01-02‘, ‘2017-01-03‘, ‘2017-01-04‘,
 3                ‘2017-01-05‘, ‘2017-01-06‘, ‘2017-01-07‘],
 4               dtype=‘datetime64[ns]‘, name=‘value‘, freq=‘D‘)
 5 ---------df.columns---------
 6 Index([‘ ‘], dtype=‘object‘)
 7 ----------df.values---------
 8 [[1]
 9  [2]
10  [3]
11  [4]
12  [5]
13  [6]
14  [7]]
15 ----------df.describe--------
16 <bound method NDFrame.describe of              
17 value        
18 2017-01-01  1
19 2017-01-02  2
20 2017-01-03  3
21 2017-01-04  4
22 2017-01-05  5
23 2017-01-06  6
24 2017-01-07  7>
25 ----------information details--------
26              
27 value        
28 2017-01-01  1
29 2017-01-02  2
30              
31 value        
32 2017-01-05  5
33 2017-01-06  6
34 2017-01-07  7
35              
36 value        
37 2017-01-04  4
38 2017-01-05  5

 1 # Code based on Python 3.x
 2 # _*_ coding: utf-8 _*_
 3 # __Author: "LEMON"
 4 
 5 from pandas import Series, DataFrame
 6 import pandas as pd
 7 
 8 data = {‘state‘: [‘Ohino‘, ‘Ohino‘, ‘Ohino‘, ‘Nevada‘, ‘Nevada‘],
 9         ‘year‘: [2000, 2001, 2002, 2001, 2002],
10         ‘pop‘: [1.5, 1.7, 3.6, 2.4, 2.9]}
11 
12 df = DataFrame(data, index=list(range(1, 6)),
13                columns=[‘year‘, ‘state‘, ‘pop‘, ‘name‘])
14 print(df)
15 
16 print(‘\n‘, ‘---------------‘)
17 print(list(df.ix[3]))
18 
19 print(‘\n‘, ‘---------------‘)
20 print(list(df[‘year‘]))
21 
22 aList = [‘1‘, ‘2‘, ‘3‘, ‘4‘]
23 bList = [‘aa‘, ‘bb‘, ‘cb‘, ‘dd‘]
24 cList = [‘lemon‘, ‘apple‘, ‘orange‘, ‘banana‘]
25 
26 d = {‘num‘: aList, ‘char‘: bList, ‘fruit‘: cList}
27 
28 
29 df1 = DataFrame(d, index=[‘a‘, ‘b‘, ‘c‘, ‘d‘])
30 # df2 = DataFrame(bList)
31 print(‘\n‘, ‘---------------‘)
32 print(df1)
33 #print(df1.num)
34 
35 print(‘\n‘, ‘---------------‘)
36 print(df1.ix[‘b‘])  # 获取索引号为 ‘b‘ 的行的数据
37 
38 
39 print(‘\n‘, ‘---------------‘)
40 print(df1.ix[:2, 1:3]) # 以切片形式获取部分数据

 1  year   state  pop name
 2 1  2000   Ohino  1.5  NaN
 3 2  2001   Ohino  1.7  NaN
 4 3  2002   Ohino  3.6  NaN
 5 4  2001  Nevada  2.4  NaN
 6 5  2002  Nevada  2.9  NaN
 7 
 8  ---------------
 9 [2002, ‘Ohino‘, 3.6000000000000001, nan]
10 
11  ---------------
12 [2000, 2001, 2002, 2001, 2002]
13 
14  ---------------
15   char   fruit num
16 a   aa   lemon   1
17 b   bb   apple   2
18 c   cb  orange   3
19 d   dd  banana   4
20 
21  ---------------
22 char        bb
23 fruit    apple
24 num          2
25 Name: b, dtype: object
26 
27  ---------------
28    fruit num
29 a  lemon   1
30 b  apple   2