pandas之索引

 

 

 

In [1]:

import pandas as pd
import numpy as np

In [3]:

d1 = pd.DataFrame(np.arange(12).reshape(3,4),index=list("ABC"),columns=list("WXYZ"))
print(d1)

 

   W  X   Y   Z
A  0  1   2   3
B  4  5   6   7
C  8  9  10  11

In [5]:

d1.index = ["O","P","Q"]
print(d1)

 

   W  X   Y   Z
O  0  1   2   3
P  4  5   6   7
Q  8  9  10  11

In [9]:

#使用reindex，和以前對不上的會被賦nan
d1.reindex(index=list("Opq"))

Out[9]:

 

	W	X	Y	Z
O	0.0	1.0	2.0	3.0
p	NaN	NaN	NaN	NaN
q	NaN	NaN	NaN	NaN

In [10]:

#將其中一列設爲索引
d1.set_index("W")

Out[10]:

 

	X	Y	Z
W
0	1	2	3
4	5	6	7
8	9	10	11

In [11]:

d1.set_index("W",drop=False)

Out[11]:

 

	W	X	Y	Z
W
0	0	1	2	3
4	4	5	6	7
8	8	9	10	11

In [13]:

d1.set_index(["W","X"],drop=False)

Out[13]:

 

		W	X	Y	Z
W	X
0	1	0	1	2	3
4	5	4	5	6	7
8	9	8	9	10	11

In [14]:

d1.set_index("W").index.unique()

Out[14]:

Int64Index([0, 4, 8], dtype='int64', name='W')

In [15]:

a = pd.DataFrame({'a': range(7),'b': range(7, 0, -1),'c': ['one','one','one','two','two','two', 'two'],'d': list("hjklmno")})
print(a)

 

   a  b    c  d
0  0  7  one  h
1  1  6  one  j
2  2  5  one  k
3  3  4  two  l
4  4  3  two  m
5  5  2  two  n
6  6  1  two  o

In [18]:

b = a.set_index(["d","c"])
print(b)
print(type(b))

 

       a  b
d c        
h one  0  7
j one  1  6
k one  2  5
l two  3  4
m two  4  3
n two  5  2
o two  6  1
<class 'pandas.core.frame.DataFrame'>

In [40]:

#想取b裏的one索引
b = b.swaplevel()
print(b)
print("*"*20)
print(b.loc["one"])#DataFrame[""]形式只能用於取列，沒法用來取行索引
print("*"*20)
print(b.loc["one"].loc["h"])

 

       a  b
c   d      
one h  0  7
    j  1  6
    k  2  5
two l  3  4
    m  4  3
    n  5  2
    o  6  1
********************
   a  b
d      
h  0  7
j  1  6
k  2  5
********************
a    0
b    7
Name: h, dtype: int64

In [41]:

c = b["a"]
print(type(c),"\n",c)
print("*"*20)
print(c["one","h"])#對於Series直接用[]取值就行了，不須要用loc

 

<class 'pandas.core.series.Series'> 
 c    d
one  h    0
     j    1
     k    2
two  l    3
     m    4
     n    5
     o    6
Name: a, dtype: int64
********************
0