``````

In [2]:

import numpy as np
import pandas as pd

``````
score = np.array([[0.95,0.87,0.89],[0.88,0.90,0.91],[0.80,0.90,0.88]])
score
m = score.shape[0] n = score.shape[1]
score.T
score_ = (score.T.dot(np.zeros(m)+1))/m
score_
B = [] for i in range(m): for j in range(n): print score_[j]/score[i,j] B.append(score_[j]/score[i,j]) B
B = np.array(B).reshape(m,n)
score
B
p = np.zeros(m)+1 p
u = score.T.dot(p) u = u/u.sum() u
p = B.dot(u) p = p/p.sum() p
``````

In [98]:

def hits(score,iternum = 10):
m = score.shape[0]
n = score.shape[1]
score_ = (score.T.dot(np.zeros(m)+1.0))/m
B = []
for i in range(m):
for j in range(n):
B.append(score_[j]/score[i,j])
B = np.array(B).reshape(m,n)
p = np.zeros(m)+1
print 'p',0,p
for i in range(iternum):
u = score.T.dot(p)/score.T.dot(p).sum()
print 'u',i,u
p = B.dot(u)/B.dot(u).sum()
print 'p',i+1,p
return p,u

``````
``````

In [86]:

``````
``````

In [87]:

score211f

``````
``````

Out[87]:

31
46
38
47
143
48
557
43
52
558
...
136
128
44
51
37
96
332
199
935
57

0
1.241757
1.144449
1.148650
1.182423
1.090285
1.146862
1.130340
1.009606
1.184987
1.094615
...
1.124140
1.023876
1.061689
1.029915
1.005983
1.052084
1.085621
1.024177
1.054131
1.092388

1
1.304481
1.286889
1.148650
1.182423
1.196000
1.146862
1.130340
1.111074
1.184987
1.197963
...
1.207556
1.111556
1.167519
1.140296
1.083667
1.043074
1.086634
1.020815
1.044444
1.092388

2
1.359925
1.340367
1.240804
1.205480
1.276984
1.146862
1.227457
1.201646
1.184987
1.240499
...
1.256917
1.170336
1.231309
1.190352
1.181426
1.052084
1.085008
1.037105
1.088482
1.092388

3
1.216879
1.196724
1.144879
1.173017
1.160390
1.144113
1.129140
1.131584
1.188659
1.153808
...
1.150305
1.071869
1.125392
1.079413
1.071527
1.052084
1.070553
1.024177
1.054131
1.095070

4
1.248940
1.212397
1.140773
1.113938
1.151629
1.146862
1.128582
1.078958
1.188903
1.146488
...
1.148456
1.065846
1.119248
1.081084
1.056290
1.052084
1.098584
1.024177
1.028224
1.092388

5
1.220869
1.191011
1.114986
1.164019
1.135872
1.128401
1.106699
1.086049
1.184987
1.117932
...
1.141423
1.085311
1.111381
1.102095
1.074000
1.049640
1.062819
1.030015
1.055217
1.092388

6
1.239862
1.218716
1.141184
1.185641
1.160731
1.145862
1.130154
1.112588
1.192846
1.141123
...
1.146745
1.092402
1.131068
1.101665
1.068238
1.052084
1.094770
1.024177
1.028688
1.094444

7
1.351962
1.323274
1.148650
1.182423
1.213403
1.146862
1.130340
1.106336
1.184987
1.186049
...
1.174473
1.127638
1.183503
1.135253
1.120234
1.052084
1.147377
0.998577
1.031946
1.092388

8
1.185794
1.163258
1.148650
1.152243
1.131966
1.122056
1.107959
1.080855
1.138603
1.124379
...
1.137639
1.095853
1.121929
1.097972
1.084141
1.058002
1.063761
1.017638
1.057101
1.092388

9
1.211694
1.186025
1.125742
1.182423
1.150653
1.127625
1.062914
1.106320
1.184987
1.117839
...
1.141738
1.094820
1.122240
1.093968
1.094773
1.062923
1.113542
1.027505
1.062090
1.095813

10
1.274686
1.250568
1.148650
1.182423
1.178092
1.146862
1.130340
1.106336
1.184987
1.161210
...
1.174473
1.115240
1.153700
1.118314
1.096524
1.052084
1.085621
1.024177
1.054131
1.091349

11
1.174709
1.141653
1.076492
1.113784
1.088618
1.146862
1.062519
1.046939
1.127752
1.084291
...
1.103428
1.055586
1.075602
1.053841
1.032147
1.015622
1.019955
1.024177
1.013010
1.092388

12
1.297583
1.270283
1.148650
1.182423
1.182351
1.146862
1.118730
1.105149
1.184987
1.169064
...
1.184198
1.129009
1.170303
1.117983
1.079501
1.052496
1.076120
0.998113
1.039544
1.092388

13
1.361139
1.319461
1.247315
1.171299
1.221276
1.146862
1.207681
1.175063
1.184987
1.260874
...
1.280117
1.169352
1.222361
1.149329
1.146653
1.052084
1.121976
1.016724
1.070010
1.092388

14
1.185129
1.116619
1.080171
1.099084
1.088892
1.059670
1.048025
1.039346
1.103495
1.090380
...
1.109326
1.033490
1.080180
1.045160
1.027701
1.052084
1.020400
1.012872
1.007276
1.033456

15
1.219676
1.193392
1.100884
1.182423
1.122327
1.107302
1.130340
1.071970
1.138300
1.109491
...
1.128072
1.079335
1.112163
1.075568
1.062626
1.022412
1.053220
0.985859
1.025189
1.092388

16
1.249202
1.223580
1.157598
1.196168
1.179657
1.156699
1.142926
1.119110
1.190579
1.157545
...
1.154808
1.105417
1.145677
1.109087
1.109019
1.059582
1.081553
1.021066
1.068706
1.110985

17
1.243259
1.213517
1.134064
1.182423
1.158669
1.139588
1.117672
1.103494
1.184987
1.130313
...
1.147533
1.108073
1.138849
1.103141
1.102520
1.052084
1.078537
1.022920
1.062174
1.097175

18
1.274686
1.250568
1.148650
1.182423
1.178092
1.146862
1.130340
1.106336
1.184987
1.161210
...
1.174473
1.115240
1.153700
1.118314
1.096524
1.052084
1.085621
1.024177
1.054131
1.058234

19
1.292825
1.331491
1.148650
1.262594
1.213788
1.146862
1.130340
1.130794
1.274293
1.219160
...
1.221744
1.140193
1.188143
1.118314
1.097479
1.052084
1.085621
1.024177
1.065153
1.092388

20
1.274686
1.250568
1.148650
1.182423
1.178092
1.146862
1.130340
1.106336
1.184987
1.161210
...
1.174473
1.115240
1.153700
1.118314
1.096524
1.052084
1.085621
1.024177
1.054131
1.092388

21
1.267455
1.216930
1.131401
1.182423
1.156767
1.142144
1.102465
1.096272
1.165404
1.138077
...
1.146859
1.113940
1.140142
1.109121
1.091432
1.076892
1.081773
1.015541
1.072052
1.092388

22
1.253058
1.210554
1.130219
1.183339
1.149311
1.139869
1.113381
1.099106
1.170854
1.139581
...
1.152050
1.107709
1.149103
1.102118
1.088714
1.062386
1.075582
1.012277
1.067945
1.092388

23
1.294745
1.268745
1.153303
1.182423
1.184086
1.146862
1.141955
1.088757
1.184987
1.160955
...
1.171310
1.106823
1.159876
1.122185
1.115895
1.052084
1.084974
1.037836
1.052316
1.092388

24
1.235712
1.210747
1.147109
1.187603
1.165907
1.146862
1.127073
1.101192
1.184987
1.158080
...
1.170461
1.124710
1.153651
1.132246
1.100114
1.052084
1.101109
1.023726
1.086162
1.092388

25
1.274686
1.493290
1.148650
1.182423
1.289610
1.146862
1.130340
1.106336
1.184987
1.256012
...
1.270197
1.336364
1.225605
1.264556
1.171570
1.052084
1.085621
1.024177
1.054131
1.092388

26
1.347078
1.308984
1.148650
1.182423
1.208317
1.146862
1.130340
1.117784
1.237398
1.172070
...
1.212549
1.124944
1.198932
1.152361
1.104710
1.054096
1.092929
1.005324
1.022264
1.092388

27
1.288491
1.254340
1.188472
1.233189
1.205585
1.194925
1.173264
1.143434
1.236623
1.189358
...
1.206302
1.127340
1.174925
1.133623
1.118057
1.052084
1.097962
1.025321
1.061472
1.092388

28
1.203488
1.172046
1.102189
1.096021
1.128376
1.146862
1.107420
1.084719
1.149341
1.124899
...
1.133625
1.079472
1.108297
1.092570
1.069866
1.044536
1.064623
1.016587
1.052396
1.092388

29
1.353002
1.323468
1.194301
1.278615
1.235355
1.206924
1.194179
1.132414
1.271752
1.214828
...
1.225429
1.137132
1.197181
1.149326
1.145343
1.075429
1.105086
1.036152
1.077635
1.154963

30
1.476851
1.415569
1.148650
1.182423
1.288171
1.146862
1.130340
1.106336
1.184987
1.170461
...
1.162377
1.143085
1.216722
1.165950
1.130794
1.052084
1.098605
1.024177
1.054131
1.092388

31
1.365650
1.318709
1.221118
1.285150
1.229701
1.240887
1.186950
1.190514
1.184987
1.208947
...
1.249953
1.180488
1.224299
1.182609
1.164784
1.052084
1.148698
1.145753
1.113778
1.092388

32 rows × 100 columns

``````
``````

In [88]:

score = np.array(score211f)

``````
``````

In [89]:

m = score.shape[0]
n = score.shape[1]
m,n

``````
``````

Out[89]:

(32L, 100L)

``````
``````

In [90]:

score_ = (score.T.dot(np.zeros(m)+1.0))/m
score_

``````
``````

Out[90]:

array([ 1.27468625,  1.25056846,  1.14865037,  1.18242267,  1.17809234,
1.14686175,  1.13034012,  1.10633602,  1.1849869 ,  1.16120967,
1.2080692 ,  1.18429913,  1.20842357,  0.99877973,  1.10004221,
1.12602067,  1.14580553,  1.10584764,  1.07404075,  1.08762574,
1.29115331,  1.10100887,  1.18649738,  1.17323036,  1.08676695,
1.15797287,  1.08995158,  1.03781734,  1.25829489,  1.11364391,
1.21189507,  1.13008786,  1.12941091,  1.12592926,  1.10727913,
1.09086752,  1.10861039,  1.14274587,  1.06790351,  1.07512207,
1.12538236,  1.20680894,  1.16727719,  1.16863127,  1.08108097,
1.07847516,  1.11450416,  1.08025997,  1.20148458,  1.09974944,
1.12394746,  1.10840386,  1.05203267,  1.25722602,  1.11536247,
1.09806779,  1.08946523,  1.08359584,  1.08565334,  1.19871246,
1.15111275,  1.15229438,  1.08003738,  1.14576862,  1.10301836,
1.15185158,  1.12384341,  1.06014727,  1.09134423,  1.07715561,
1.04579421,  1.17128888,  1.0956705 ,  1.11190067,  1.037872  ,
0.97627111,  1.21458417,  1.09491708,  1.23519944,  1.22395194,
1.16438074,  1.16739737,  1.20750546,  1.0499905 ,  1.1698981 ,
1.17426031,  1.07832606,  1.03851382,  1.09924592,  1.10599723,
1.1744734 ,  1.11524025,  1.15369957,  1.11831372,  1.09652437,
1.05208379,  1.08562111,  1.02417743,  1.05413093,  1.09238767])

``````
``````

In [91]:

B = []
for i in range(m):
for j in range(n):
B.append(score_[j]/score[i,j])
B = np.array(B).reshape(m,n)
B

``````
``````

Out[91]:

array([[ 1.02651795,  1.09272547,  1.        , ...,  1.        ,
1.        ,  1.        ],
[ 0.97715933,  0.97177656,  1.        , ...,  1.00329405,
1.0092743 ,  1.        ],
[ 0.93732109,  0.93300466,  0.9257307 , ...,  0.98753512,
0.9684417 ,  1.        ],
...,
[ 0.94211673,  0.94491769,  0.9617759 , ...,  0.98844327,
0.97818939,  0.9458203 ],
[ 0.86311102,  0.88343892,  1.        , ...,  1.        ,
1.        ,  1.        ],
[ 0.93339141,  0.94832796,  0.94065468, ...,  0.89389019,
0.94644658,  1.        ]])

``````
``````

In [92]:

p = np.zeros(m)+1
p

``````
``````

Out[92]:

array([ 1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,
1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,
1.,  1.,  1.,  1.,  1.,  1.])

``````
``````

In [93]:

u = score.T.dot(p)/score.T.dot(p).sum()
u,u.sum()

``````
``````

Out[93]:

(array([ 0.01130125,  0.01108742,  0.01018383,  0.01048325,  0.01044486,
0.01016797,  0.01002149,  0.00980867,  0.01050598,  0.01029518,
0.01071063,  0.01049989,  0.01071377,  0.00885509,  0.00975287,
0.0099832 ,  0.01015861,  0.00980434,  0.00952235,  0.00964279,
0.01144725,  0.00976144,  0.01051938,  0.01040175,  0.00963518,
0.01026648,  0.00966341,  0.00920119,  0.01115593,  0.00987346,
0.01074455,  0.01001925,  0.01001325,  0.00998238,  0.00981703,
0.00967153,  0.00982884,  0.01013148,  0.00946793,  0.00953193,
0.00997754,  0.01069946,  0.01034897,  0.01036098,  0.00958476,
0.00956166,  0.00988109,  0.00957749,  0.01065225,  0.00975028,
0.00996481,  0.00982701,  0.00932722,  0.01114645,  0.0098887 ,
0.00973537,  0.0096591 ,  0.00960706,  0.0096253 ,  0.01062767,
0.01020566,  0.01021614,  0.00957551,  0.01015828,  0.00977926,
0.01021221,  0.00996389,  0.00939917,  0.00967576,  0.00954996,
0.00927191,  0.01038454,  0.00971411,  0.00985801,  0.00920168,
0.00865553,  0.01076839,  0.00970743,  0.01095116,  0.01085144,
0.01032329,  0.01035004,  0.01070563,  0.00930912,  0.01037221,
0.01041088,  0.00956034,  0.00920737,  0.00974581,  0.00980567,
0.01041277,  0.00988762,  0.01022859,  0.00991487,  0.00972168,
0.00932768,  0.00962502,  0.00908026,  0.00934583,  0.00968501]),
0.99999999999999978)

``````
``````

In [94]:

B.dot(u)

``````
``````

Out[94]:

array([ 1.04147202,  0.99308496,  0.95790495,  1.0170451 ,  1.01878089,
1.01854763,  1.01151131,  0.98645682,  1.02135205,  1.01468458,
1.00196658,  1.04498135,  0.99658051,  0.96887038,  1.0594361 ,
1.02827965,  0.99810438,  1.00807809,  1.00363828,  0.98103997,
0.99998962,  1.00557101,  1.00776109,  1.00048144,  0.99863275,
0.97568339,  0.98272309,  0.97980498,  1.02367888,  0.96586226,
0.98031055,  0.95058992])

``````
``````

In [95]:

p = B.dot(u)/B.dot(u).sum()
p,p.sum()

``````
``````

Out[95]:

(array([ 0.03250242,  0.03099235,  0.02989445,  0.0317401 ,  0.03179427,
0.03178699,  0.0315674 ,  0.0307855 ,  0.03187452,  0.03166644,
0.03126953,  0.03261194,  0.03110144,  0.03023666,  0.03306305,
0.03209071,  0.031149  ,  0.03146026,  0.0313217 ,  0.03061645,
0.03120783,  0.03138202,  0.03145037,  0.03122318,  0.03116549,
0.03044928,  0.03066898,  0.03057791,  0.03194713,  0.03014278,
0.03059369,  0.02966616]), 1.0)

``````
``````

In [99]:

p,u = hits(score,iternum=10)

``````
``````

p 0 [ 1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.
1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.]
u 0 [ 0.01130125  0.01108742  0.01018383  0.01048325  0.01044486  0.01016797
0.01002149  0.00980867  0.01050598  0.01029518  0.01071063  0.01049989
0.01071377  0.00885509  0.00975287  0.0099832   0.01015861  0.00980434
0.00952235  0.00964279  0.01144725  0.00976144  0.01051938  0.01040175
0.00963518  0.01026648  0.00966341  0.00920119  0.01115593  0.00987346
0.01074455  0.01001925  0.01001325  0.00998238  0.00981703  0.00967153
0.00982884  0.01013148  0.00946793  0.00953193  0.00997754  0.01069946
0.01034897  0.01036098  0.00958476  0.00956166  0.00988109  0.00957749
0.01065225  0.00975028  0.00996481  0.00982701  0.00932722  0.01114645
0.0098887   0.00973537  0.0096591   0.00960706  0.0096253   0.01062767
0.01020566  0.01021614  0.00957551  0.01015828  0.00977926  0.01021221
0.00996389  0.00939917  0.00967576  0.00954996  0.00927191  0.01038454
0.00971411  0.00985801  0.00920168  0.00865553  0.01076839  0.00970743
0.01095116  0.01085144  0.01032329  0.01035004  0.01070563  0.00930912
0.01037221  0.01041088  0.00956034  0.00920737  0.00974581  0.00980567
0.01041277  0.00988762  0.01022859  0.00991487  0.00972168  0.00932768
0.00962502  0.00908026  0.00934583  0.00968501]
p 1 [ 0.03250242  0.03099235  0.02989445  0.0317401   0.03179427  0.03178699
0.0315674   0.0307855   0.03187452  0.03166644  0.03126953  0.03261194
0.03110144  0.03023666  0.03306305  0.03209071  0.031149    0.03146026
0.0313217   0.03061645  0.03120783  0.03138202  0.03145037  0.03122318
0.03116549  0.03044928  0.03066898  0.03057791  0.03194713  0.03014278
0.03059369  0.02966616]
u 1 [ 0.01129668  0.01107966  0.01018324  0.01048292  0.01044101  0.01016985
0.01002112  0.00980742  0.01050756  0.0102926   0.01070589  0.01049588
0.01070842  0.00886203  0.00975552  0.00998493  0.01015361  0.00981016
0.00952364  0.00964244  0.0114415   0.00976241  0.01051719  0.01040149
0.0096351   0.0102687   0.00966781  0.00920327  0.01114977  0.00987825
0.0107424   0.01001943  0.01001241  0.00998594  0.00981582  0.00967381
0.00983468  0.01013571  0.00946931  0.00953504  0.00998108  0.01069887
0.01034788  0.01036345  0.0095854   0.00956333  0.00988031  0.00957838
0.01064593  0.00975081  0.00996321  0.00982836  0.0093284   0.01114006
0.00989289  0.00973573  0.00966374  0.00960631  0.00962443  0.01062395
0.01019753  0.01021454  0.00957491  0.01015646  0.00978134  0.01021044
0.00996859  0.00940452  0.00967394  0.00955212  0.00927787  0.0103835
0.00971564  0.00985683  0.00920713  0.00866301  0.01076185  0.00971245
0.01094547  0.0108495   0.01031881  0.01035075  0.01069983  0.00931286
0.01036753  0.01040652  0.0095603   0.00921086  0.00974906  0.00980527
0.01041024  0.00988486  0.01022555  0.00991263  0.00971978  0.00933247
0.00962663  0.00908352  0.00934843  0.00968929]
p 2 [ 0.03250211  0.03099247  0.02989476  0.03173998  0.03179425  0.03178686
0.03156733  0.03078566  0.03187432  0.03166627  0.03126952  0.03261165
0.03110149  0.03023705  0.0330627   0.03209058  0.03114891  0.03146016
0.03132168  0.03061659  0.03120784  0.03138194  0.03145029  0.03122329
0.03116541  0.03044959  0.03066915  0.03057793  0.03194696  0.03014291
0.03059402  0.02966632]
u 2 [ 0.01129669  0.01107966  0.01018324  0.01048292  0.01044101  0.01016985
0.01002112  0.00980742  0.01050756  0.0102926   0.01070589  0.01049588
0.01070842  0.00886203  0.00975552  0.00998493  0.01015361  0.00981015
0.00952364  0.00964244  0.0114415   0.00976241  0.01051719  0.01040149
0.0096351   0.01026869  0.00966781  0.00920327  0.01114977  0.00987825
0.0107424   0.01001943  0.01001241  0.00998594  0.00981583  0.00967381
0.00983468  0.01013571  0.00946931  0.00953504  0.00998108  0.01069887
0.01034788  0.01036345  0.0095854   0.00956333  0.00988031  0.00957838
0.01064593  0.00975081  0.00996321  0.00982836  0.0093284   0.01114006
0.00989289  0.00973573  0.00966373  0.00960631  0.00962443  0.01062395
0.01019753  0.01021454  0.00957491  0.01015646  0.00978134  0.01021044
0.00996859  0.00940452  0.00967394  0.00955211  0.00927787  0.0103835
0.00971564  0.00985683  0.00920713  0.00866301  0.01076185  0.00971245
0.01094547  0.0108495   0.01031881  0.01035075  0.01069983  0.00931285
0.01036753  0.01040652  0.0095603   0.00921086  0.00974906  0.00980527
0.01041024  0.00988486  0.01022555  0.00991263  0.00971978  0.00933247
0.00962663  0.00908351  0.00934843  0.00968928]
p 3 [ 0.03250211  0.03099247  0.02989476  0.03173998  0.03179425  0.03178686
0.03156733  0.03078566  0.03187432  0.03166627  0.03126952  0.03261165
0.03110149  0.03023705  0.0330627   0.03209058  0.03114891  0.03146016
0.03132168  0.03061659  0.03120784  0.03138194  0.03145029  0.03122329
0.03116541  0.03044959  0.03066915  0.03057793  0.03194696  0.03014291
0.03059402  0.02966632]
u 3 [ 0.01129669  0.01107966  0.01018324  0.01048292  0.01044101  0.01016985
0.01002112  0.00980742  0.01050756  0.0102926   0.01070589  0.01049588
0.01070842  0.00886203  0.00975552  0.00998493  0.01015361  0.00981015
0.00952364  0.00964244  0.0114415   0.00976241  0.01051719  0.01040149
0.0096351   0.01026869  0.00966781  0.00920327  0.01114977  0.00987825
0.0107424   0.01001943  0.01001241  0.00998594  0.00981583  0.00967381
0.00983468  0.01013571  0.00946931  0.00953504  0.00998108  0.01069887
0.01034788  0.01036345  0.0095854   0.00956333  0.00988031  0.00957838
0.01064593  0.00975081  0.00996321  0.00982836  0.0093284   0.01114006
0.00989289  0.00973573  0.00966373  0.00960631  0.00962443  0.01062395
0.01019753  0.01021454  0.00957491  0.01015646  0.00978134  0.01021044
0.00996859  0.00940452  0.00967394  0.00955211  0.00927787  0.0103835
0.00971564  0.00985683  0.00920713  0.00866301  0.01076185  0.00971245
0.01094547  0.0108495   0.01031881  0.01035075  0.01069983  0.00931285
0.01036753  0.01040652  0.0095603   0.00921086  0.00974906  0.00980527
0.01041024  0.00988486  0.01022555  0.00991263  0.00971978  0.00933247
0.00962663  0.00908351  0.00934843  0.00968928]
p 4 [ 0.03250211  0.03099247  0.02989476  0.03173998  0.03179425  0.03178686
0.03156733  0.03078566  0.03187432  0.03166627  0.03126952  0.03261165
0.03110149  0.03023705  0.0330627   0.03209058  0.03114891  0.03146016
0.03132168  0.03061659  0.03120784  0.03138194  0.03145029  0.03122329
0.03116541  0.03044959  0.03066915  0.03057793  0.03194696  0.03014291
0.03059402  0.02966632]
u 4 [ 0.01129669  0.01107966  0.01018324  0.01048292  0.01044101  0.01016985
0.01002112  0.00980742  0.01050756  0.0102926   0.01070589  0.01049588
0.01070842  0.00886203  0.00975552  0.00998493  0.01015361  0.00981015
0.00952364  0.00964244  0.0114415   0.00976241  0.01051719  0.01040149
0.0096351   0.01026869  0.00966781  0.00920327  0.01114977  0.00987825
0.0107424   0.01001943  0.01001241  0.00998594  0.00981583  0.00967381
0.00983468  0.01013571  0.00946931  0.00953504  0.00998108  0.01069887
0.01034788  0.01036345  0.0095854   0.00956333  0.00988031  0.00957838
0.01064593  0.00975081  0.00996321  0.00982836  0.0093284   0.01114006
0.00989289  0.00973573  0.00966373  0.00960631  0.00962443  0.01062395
0.01019753  0.01021454  0.00957491  0.01015646  0.00978134  0.01021044
0.00996859  0.00940452  0.00967394  0.00955211  0.00927787  0.0103835
0.00971564  0.00985683  0.00920713  0.00866301  0.01076185  0.00971245
0.01094547  0.0108495   0.01031881  0.01035075  0.01069983  0.00931285
0.01036753  0.01040652  0.0095603   0.00921086  0.00974906  0.00980527
0.01041024  0.00988486  0.01022555  0.00991263  0.00971978  0.00933247
0.00962663  0.00908351  0.00934843  0.00968928]
p 5 [ 0.03250211  0.03099247  0.02989476  0.03173998  0.03179425  0.03178686
0.03156733  0.03078566  0.03187432  0.03166627  0.03126952  0.03261165
0.03110149  0.03023705  0.0330627   0.03209058  0.03114891  0.03146016
0.03132168  0.03061659  0.03120784  0.03138194  0.03145029  0.03122329
0.03116541  0.03044959  0.03066915  0.03057793  0.03194696  0.03014291
0.03059402  0.02966632]
u 5 [ 0.01129669  0.01107966  0.01018324  0.01048292  0.01044101  0.01016985
0.01002112  0.00980742  0.01050756  0.0102926   0.01070589  0.01049588
0.01070842  0.00886203  0.00975552  0.00998493  0.01015361  0.00981015
0.00952364  0.00964244  0.0114415   0.00976241  0.01051719  0.01040149
0.0096351   0.01026869  0.00966781  0.00920327  0.01114977  0.00987825
0.0107424   0.01001943  0.01001241  0.00998594  0.00981583  0.00967381
0.00983468  0.01013571  0.00946931  0.00953504  0.00998108  0.01069887
0.01034788  0.01036345  0.0095854   0.00956333  0.00988031  0.00957838
0.01064593  0.00975081  0.00996321  0.00982836  0.0093284   0.01114006
0.00989289  0.00973573  0.00966373  0.00960631  0.00962443  0.01062395
0.01019753  0.01021454  0.00957491  0.01015646  0.00978134  0.01021044
0.00996859  0.00940452  0.00967394  0.00955211  0.00927787  0.0103835
0.00971564  0.00985683  0.00920713  0.00866301  0.01076185  0.00971245
0.01094547  0.0108495   0.01031881  0.01035075  0.01069983  0.00931285
0.01036753  0.01040652  0.0095603   0.00921086  0.00974906  0.00980527
0.01041024  0.00988486  0.01022555  0.00991263  0.00971978  0.00933247
0.00962663  0.00908351  0.00934843  0.00968928]
p 6 [ 0.03250211  0.03099247  0.02989476  0.03173998  0.03179425  0.03178686
0.03156733  0.03078566  0.03187432  0.03166627  0.03126952  0.03261165
0.03110149  0.03023705  0.0330627   0.03209058  0.03114891  0.03146016
0.03132168  0.03061659  0.03120784  0.03138194  0.03145029  0.03122329
0.03116541  0.03044959  0.03066915  0.03057793  0.03194696  0.03014291
0.03059402  0.02966632]
u 6 [ 0.01129669  0.01107966  0.01018324  0.01048292  0.01044101  0.01016985
0.01002112  0.00980742  0.01050756  0.0102926   0.01070589  0.01049588
0.01070842  0.00886203  0.00975552  0.00998493  0.01015361  0.00981015
0.00952364  0.00964244  0.0114415   0.00976241  0.01051719  0.01040149
0.0096351   0.01026869  0.00966781  0.00920327  0.01114977  0.00987825
0.0107424   0.01001943  0.01001241  0.00998594  0.00981583  0.00967381
0.00983468  0.01013571  0.00946931  0.00953504  0.00998108  0.01069887
0.01034788  0.01036345  0.0095854   0.00956333  0.00988031  0.00957838
0.01064593  0.00975081  0.00996321  0.00982836  0.0093284   0.01114006
0.00989289  0.00973573  0.00966373  0.00960631  0.00962443  0.01062395
0.01019753  0.01021454  0.00957491  0.01015646  0.00978134  0.01021044
0.00996859  0.00940452  0.00967394  0.00955211  0.00927787  0.0103835
0.00971564  0.00985683  0.00920713  0.00866301  0.01076185  0.00971245
0.01094547  0.0108495   0.01031881  0.01035075  0.01069983  0.00931285
0.01036753  0.01040652  0.0095603   0.00921086  0.00974906  0.00980527
0.01041024  0.00988486  0.01022555  0.00991263  0.00971978  0.00933247
0.00962663  0.00908351  0.00934843  0.00968928]
p 7 [ 0.03250211  0.03099247  0.02989476  0.03173998  0.03179425  0.03178686
0.03156733  0.03078566  0.03187432  0.03166627  0.03126952  0.03261165
0.03110149  0.03023705  0.0330627   0.03209058  0.03114891  0.03146016
0.03132168  0.03061659  0.03120784  0.03138194  0.03145029  0.03122329
0.03116541  0.03044959  0.03066915  0.03057793  0.03194696  0.03014291
0.03059402  0.02966632]
u 7 [ 0.01129669  0.01107966  0.01018324  0.01048292  0.01044101  0.01016985
0.01002112  0.00980742  0.01050756  0.0102926   0.01070589  0.01049588
0.01070842  0.00886203  0.00975552  0.00998493  0.01015361  0.00981015
0.00952364  0.00964244  0.0114415   0.00976241  0.01051719  0.01040149
0.0096351   0.01026869  0.00966781  0.00920327  0.01114977  0.00987825
0.0107424   0.01001943  0.01001241  0.00998594  0.00981583  0.00967381
0.00983468  0.01013571  0.00946931  0.00953504  0.00998108  0.01069887
0.01034788  0.01036345  0.0095854   0.00956333  0.00988031  0.00957838
0.01064593  0.00975081  0.00996321  0.00982836  0.0093284   0.01114006
0.00989289  0.00973573  0.00966373  0.00960631  0.00962443  0.01062395
0.01019753  0.01021454  0.00957491  0.01015646  0.00978134  0.01021044
0.00996859  0.00940452  0.00967394  0.00955211  0.00927787  0.0103835
0.00971564  0.00985683  0.00920713  0.00866301  0.01076185  0.00971245
0.01094547  0.0108495   0.01031881  0.01035075  0.01069983  0.00931285
0.01036753  0.01040652  0.0095603   0.00921086  0.00974906  0.00980527
0.01041024  0.00988486  0.01022555  0.00991263  0.00971978  0.00933247
0.00962663  0.00908351  0.00934843  0.00968928]
p 8 [ 0.03250211  0.03099247  0.02989476  0.03173998  0.03179425  0.03178686
0.03156733  0.03078566  0.03187432  0.03166627  0.03126952  0.03261165
0.03110149  0.03023705  0.0330627   0.03209058  0.03114891  0.03146016
0.03132168  0.03061659  0.03120784  0.03138194  0.03145029  0.03122329
0.03116541  0.03044959  0.03066915  0.03057793  0.03194696  0.03014291
0.03059402  0.02966632]
u 8 [ 0.01129669  0.01107966  0.01018324  0.01048292  0.01044101  0.01016985
0.01002112  0.00980742  0.01050756  0.0102926   0.01070589  0.01049588
0.01070842  0.00886203  0.00975552  0.00998493  0.01015361  0.00981015
0.00952364  0.00964244  0.0114415   0.00976241  0.01051719  0.01040149
0.0096351   0.01026869  0.00966781  0.00920327  0.01114977  0.00987825
0.0107424   0.01001943  0.01001241  0.00998594  0.00981583  0.00967381
0.00983468  0.01013571  0.00946931  0.00953504  0.00998108  0.01069887
0.01034788  0.01036345  0.0095854   0.00956333  0.00988031  0.00957838
0.01064593  0.00975081  0.00996321  0.00982836  0.0093284   0.01114006
0.00989289  0.00973573  0.00966373  0.00960631  0.00962443  0.01062395
0.01019753  0.01021454  0.00957491  0.01015646  0.00978134  0.01021044
0.00996859  0.00940452  0.00967394  0.00955211  0.00927787  0.0103835
0.00971564  0.00985683  0.00920713  0.00866301  0.01076185  0.00971245
0.01094547  0.0108495   0.01031881  0.01035075  0.01069983  0.00931285
0.01036753  0.01040652  0.0095603   0.00921086  0.00974906  0.00980527
0.01041024  0.00988486  0.01022555  0.00991263  0.00971978  0.00933247
0.00962663  0.00908351  0.00934843  0.00968928]
p 9 [ 0.03250211  0.03099247  0.02989476  0.03173998  0.03179425  0.03178686
0.03156733  0.03078566  0.03187432  0.03166627  0.03126952  0.03261165
0.03110149  0.03023705  0.0330627   0.03209058  0.03114891  0.03146016
0.03132168  0.03061659  0.03120784  0.03138194  0.03145029  0.03122329
0.03116541  0.03044959  0.03066915  0.03057793  0.03194696  0.03014291
0.03059402  0.02966632]
u 9 [ 0.01129669  0.01107966  0.01018324  0.01048292  0.01044101  0.01016985
0.01002112  0.00980742  0.01050756  0.0102926   0.01070589  0.01049588
0.01070842  0.00886203  0.00975552  0.00998493  0.01015361  0.00981015
0.00952364  0.00964244  0.0114415   0.00976241  0.01051719  0.01040149
0.0096351   0.01026869  0.00966781  0.00920327  0.01114977  0.00987825
0.0107424   0.01001943  0.01001241  0.00998594  0.00981583  0.00967381
0.00983468  0.01013571  0.00946931  0.00953504  0.00998108  0.01069887
0.01034788  0.01036345  0.0095854   0.00956333  0.00988031  0.00957838
0.01064593  0.00975081  0.00996321  0.00982836  0.0093284   0.01114006
0.00989289  0.00973573  0.00966373  0.00960631  0.00962443  0.01062395
0.01019753  0.01021454  0.00957491  0.01015646  0.00978134  0.01021044
0.00996859  0.00940452  0.00967394  0.00955211  0.00927787  0.0103835
0.00971564  0.00985683  0.00920713  0.00866301  0.01076185  0.00971245
0.01094547  0.0108495   0.01031881  0.01035075  0.01069983  0.00931285
0.01036753  0.01040652  0.0095603   0.00921086  0.00974906  0.00980527
0.01041024  0.00988486  0.01022555  0.00991263  0.00971978  0.00933247
0.00962663  0.00908351  0.00934843  0.00968928]
p 10 [ 0.03250211  0.03099247  0.02989476  0.03173998  0.03179425  0.03178686
0.03156733  0.03078566  0.03187432  0.03166627  0.03126952  0.03261165
0.03110149  0.03023705  0.0330627   0.03209058  0.03114891  0.03146016
0.03132168  0.03061659  0.03120784  0.03138194  0.03145029  0.03122329
0.03116541  0.03044959  0.03066915  0.03057793  0.03194696  0.03014291
0.03059402  0.02966632]

``````
``````

In [100]:

p

``````
``````

Out[100]:

array([ 0.03250211,  0.03099247,  0.02989476,  0.03173998,  0.03179425,
0.03178686,  0.03156733,  0.03078566,  0.03187432,  0.03166627,
0.03126952,  0.03261165,  0.03110149,  0.03023705,  0.0330627 ,
0.03209058,  0.03114891,  0.03146016,  0.03132168,  0.03061659,
0.03120784,  0.03138194,  0.03145029,  0.03122329,  0.03116541,
0.03044959,  0.03066915,  0.03057793,  0.03194696,  0.03014291,
0.03059402,  0.02966632])

``````
``````

In [101]:

u

``````
``````

Out[101]:

array([ 0.01129669,  0.01107966,  0.01018324,  0.01048292,  0.01044101,
0.01016985,  0.01002112,  0.00980742,  0.01050756,  0.0102926 ,
0.01070589,  0.01049588,  0.01070842,  0.00886203,  0.00975552,
0.00998493,  0.01015361,  0.00981015,  0.00952364,  0.00964244,
0.0114415 ,  0.00976241,  0.01051719,  0.01040149,  0.0096351 ,
0.01026869,  0.00966781,  0.00920327,  0.01114977,  0.00987825,
0.0107424 ,  0.01001943,  0.01001241,  0.00998594,  0.00981583,
0.00967381,  0.00983468,  0.01013571,  0.00946931,  0.00953504,
0.00998108,  0.01069887,  0.01034788,  0.01036345,  0.0095854 ,
0.00956333,  0.00988031,  0.00957838,  0.01064593,  0.00975081,
0.00996321,  0.00982836,  0.0093284 ,  0.01114006,  0.00989289,
0.00973573,  0.00966373,  0.00960631,  0.00962443,  0.01062395,
0.01019753,  0.01021454,  0.00957491,  0.01015646,  0.00978134,
0.01021044,  0.00996859,  0.00940452,  0.00967394,  0.00955211,
0.00927787,  0.0103835 ,  0.00971564,  0.00985683,  0.00920713,
0.00866301,  0.01076185,  0.00971245,  0.01094547,  0.0108495 ,
0.01031881,  0.01035075,  0.01069983,  0.00931285,  0.01036753,
0.01040652,  0.0095603 ,  0.00921086,  0.00974906,  0.00980527,
0.01041024,  0.00988486,  0.01022555,  0.00991263,  0.00971978,
0.00933247,  0.00962663,  0.00908351,  0.00934843,  0.00968928])

``````
def hits(score,iternum = 10): m = score.shape[0] n = score.shape[1] score_ = (score.T.dot(np.zeros(m)+1.0))/m B = [] for i in range(m): for j in range(n): B.append(score_[j]/score[i,j]) B = np.array(B).reshape(m,n) p = np.zeros(m)+1 print 'p',0,p for i in range(iternum): u = score.T.dot(p)#/score.T.dot(p).sum() print 'u',i,u p = B.dot(u)#/B.dot(u).sum() print 'p',i+1,p return p,u hits(score)
``````

In [156]:

``````
``````

In [158]:

``````
``````

Out[158]:

schoolname
schoolid

0
������ѧ
31

1
�й������ѧ
46

2
������ͨ��ѧ
38

3
�������պ����ѧ
47

4
��������ѧ
143

``````
``````

In [105]:

province = u'00上海01云南02内蒙古03北京04吉林05四川06天津07宁夏08安徽09山东10山西11广东12广西13新疆14江苏15江西16河北17河南18浙江19海南21湖北22湖南23甘肃24福建25西藏26贵州27辽宁28重庆29陕西30青海31黑龙江32香港33澳门'

``````
``````

In [114]:

import re
province = [(i[:2],i[2:5]) for i in re.findall(u'[0-9]{2}.{2}',province)]

``````
``````

In [115]:

province

``````
``````

Out[115]:

[(u'00', u'\u4e0a\u6d77'),
(u'01', u'\u4e91\u5357'),
(u'02', u'\u5185\u8499'),
(u'03', u'\u5317\u4eac'),
(u'04', u'\u5409\u6797'),
(u'05', u'\u56db\u5ddd'),
(u'06', u'\u5929\u6d25'),
(u'07', u'\u5b81\u590f'),
(u'08', u'\u5b89\u5fbd'),
(u'09', u'\u5c71\u4e1c'),
(u'10', u'\u5c71\u897f'),
(u'11', u'\u5e7f\u4e1c'),
(u'12', u'\u5e7f\u897f'),
(u'13', u'\u65b0\u7586'),
(u'14', u'\u6c5f\u82cf'),
(u'15', u'\u6c5f\u897f'),
(u'16', u'\u6cb3\u5317'),
(u'17', u'\u6cb3\u5357'),
(u'18', u'\u6d59\u6c5f'),
(u'19', u'\u6d77\u5357'),
(u'21', u'\u6e56\u5317'),
(u'22', u'\u6e56\u5357'),
(u'23', u'\u7518\u8083'),
(u'24', u'\u798f\u5efa'),
(u'25', u'\u897f\u85cf'),
(u'26', u'\u8d35\u5dde'),
(u'27', u'\u8fbd\u5b81'),
(u'28', u'\u91cd\u5e86'),
(u'29', u'\u9655\u897f'),
(u'30', u'\u9752\u6d77'),
(u'31', u'\u9ed1\u9f99'),
(u'32', u'\u9999\u6e2f'),
(u'33', u'\u6fb3\u95e8')]

``````
``````

In [116]:

provinced = {}

``````
``````

In [117]:

for k,v in province:
provinced[k] = v
provinced

``````
``````

Out[117]:

{u'00': u'\u4e0a\u6d77',
u'01': u'\u4e91\u5357',
u'02': u'\u5185\u8499',
u'03': u'\u5317\u4eac',
u'04': u'\u5409\u6797',
u'05': u'\u56db\u5ddd',
u'06': u'\u5929\u6d25',
u'07': u'\u5b81\u590f',
u'08': u'\u5b89\u5fbd',
u'09': u'\u5c71\u4e1c',
u'10': u'\u5c71\u897f',
u'11': u'\u5e7f\u4e1c',
u'12': u'\u5e7f\u897f',
u'13': u'\u65b0\u7586',
u'14': u'\u6c5f\u82cf',
u'15': u'\u6c5f\u897f',
u'16': u'\u6cb3\u5317',
u'17': u'\u6cb3\u5357',
u'18': u'\u6d59\u6c5f',
u'19': u'\u6d77\u5357',
u'21': u'\u6e56\u5317',
u'22': u'\u6e56\u5357',
u'23': u'\u7518\u8083',
u'24': u'\u798f\u5efa',
u'25': u'\u897f\u85cf',
u'26': u'\u8d35\u5dde',
u'27': u'\u8fbd\u5b81',
u'28': u'\u91cd\u5e86',
u'29': u'\u9655\u897f',
u'30': u'\u9752\u6d77',
u'31': u'\u9ed1\u9f99',
u'32': u'\u9999\u6e2f',
u'33': u'\u6fb3\u95e8'}

``````
``````

In [131]:

ps = {}
for i in range(len(p)):
if i >= len(p)-1:
break
if i > 19:
i = i+1
k = str(i)
if i < 10:
k = '0'+str(i)
print provinced[k],
print p[i]
ps[provinced[k]] = p[i]

``````
``````

``````
``````

In [140]:

pss = sorted(ps.items(),key= lambda item: item[1],reverse=True)

``````
``````

In [141]:

for k,v in pss:
print k,v

``````
``````

``````
``````

In [177]:

schoold = {}
for row in school.itertuples():
print row.schoolname.decode('gbk')
schoold[row.schoolid] = row.schoolname.decode('gbk')

``````
``````

``````
``````

In [178]:

schoold

``````
``````

Out[178]:

{30: u'\u5317\u4eac\u5de5\u4e1a\u5927\u5b66',
31: u'\u5317\u4eac\u5927\u5b66',
32: u'\u5185\u8499\u53e4\u5927\u5b66',
33: u'\u5927\u8fde\u6d77\u4e8b\u5927\u5b66',
34: u'\u54c8\u5c14\u6ee8\u5de5\u4e1a\u5927\u5b66',
35: u'\u4e91\u5357\u5927\u5b66',
36: u'\u957f\u5b89\u5927\u5b66',
37: u'\u897f\u5317\u5927\u5b66',
38: u'\u5317\u4eac\u4ea4\u901a\u5927\u5b66',
39: u'\u5317\u4eac\u5916\u56fd\u8bed\u5927\u5b66',
41: u'\u6cb3\u5317\u5de5\u4e1a\u5927\u5b66',
42: u'\u6b66\u6c49\u5927\u5b66',
43: u'\u5317\u4eac\u6797\u4e1a\u5927\u5b66',
44: u'\u6e56\u5357\u5927\u5b66',
45: u'\u4e2d\u592e\u6c11\u65cf\u5927\u5b66',
46: u'\u4e2d\u56fd\u4eba\u6c11\u5927\u5b66',
47: u'\u5317\u4eac\u822a\u7a7a\u822a\u5929\u5927\u5b66',
48: u'\u5317\u4eac\u90ae\u7535\u5927\u5b66',
49: u'\u5317\u4eac\u4e2d\u533b\u836f\u5927\u5b66',
50: u'\u8fbd\u5b81\u5927\u5b66',
51: u'\u897f\u5357\u4ea4\u901a\u5927\u5b66',
52: u'\u5317\u4eac\u5e08\u8303\u5927\u5b66',
53: u'\u5bf9\u5916\u7ecf\u6d4e\u8d38\u6613\u5927\u5b66',
57: u'\u897f\u5b89\u7535\u5b50\u79d1\u6280\u5927\u5b66',
58: u'\u6e56\u5357\u5e08\u8303\u5927\u5b66',
59: u'\u5357\u5f00\u5927\u5b66',
60: u'\u5929\u6d25\u5927\u5b66',
61: u'\u4e2d\u56fd\u6d77\u6d0b\u5927\u5b66',
62: u'\u90d1\u5dde\u5927\u5b66',
63: u'\u5408\u80a5\u5de5\u4e1a\u5927\u5b66',
66: u'\u4e2d\u56fd\u79d1\u5b66\u6280\u672f\u5927\u5b66',
67: u'\u5b89\u5fbd\u5927\u5b66',
73: u'\u540c\u6d4e\u5927\u5b66',
74: u'\u65b0\u7586\u5927\u5b66',
76: u'\u4e0a\u6d77\u5927\u5b66',
77: u'\u5357\u4eac\u822a\u7a7a\u822a\u5929\u5927\u5b66',
78: u'\u5929\u6d25\u533b\u79d1\u5927\u5b66',
86: u'\u6c5f\u5357\u5927\u5b66',
96: u'\u5e7f\u897f\u5927\u5b66',
97: u'\u5170\u5dde\u5927\u5b66',
98: u'\u534e\u5357\u5e08\u8303\u5927\u5b66',
99: u'\u56db\u5ddd\u5927\u5b66',
100: u'\u56db\u5ddd\u519c\u4e1a\u5927\u5b66',
101: u'\u897f\u5357\u8d22\u7ecf\u5927\u5b66',
102: u'\u53a6\u95e8\u5927\u5b66',
103: u'\u798f\u5dde\u5927\u5b66',
104: u'\u4e2d\u5c71\u5927\u5b66',
105: u'\u534e\u5357\u7406\u5de5\u5927\u5b66',
106: u'\u66a8\u5357\u5927\u5b66',
107: u'\u897f\u5317\u5de5\u4e1a\u5927\u5b66',
108: u'\u5357\u660c\u5927\u5b66',
109: u'\u4e1c\u5357\u5927\u5b66',
110: u'\u4e2d\u56fd\u77ff\u4e1a\u5927\u5b66',
111: u'\u5357\u4eac\u5927\u5b66',
112: u'\u5357\u4eac\u7406\u5de5\u5927\u5b66',
113: u'\u5357\u4eac\u519c\u4e1a\u5927\u5b66',
114: u'\u6d59\u6c5f\u5927\u5b66',
115: u'\u5357\u4eac\u5e08\u8303\u5927\u5b66',
116: u'\u6cb3\u6d77\u5927\u5b66',
117: u'\u4e2d\u56fd\u836f\u79d1\u5927\u5b66',
118: u'\u82cf\u5dde\u5927\u5b66',
119: u'\u91cd\u5e86\u5927\u5b66',
122: u'\u5409\u6797\u5927\u5b66',
123: u'\u4e2d\u5357\u5927\u5b66',
124: u'\u54c8\u5c14\u6ee8\u5de5\u7a0b\u5927\u5b66',
125: u'\u4e0a\u6d77\u4ea4\u901a\u5927\u5b66',
126: u'\u5c71\u4e1c\u5927\u5b66',
127: u'\u534e\u4e2d\u79d1\u6280\u5927\u5b66',
128: u'\u6b66\u6c49\u7406\u5de5\u5927\u5b66',
130: u'\u4e0a\u6d77\u8d22\u7ecf\u5927\u5b66',
131: u'\u534e\u4e1c\u5e08\u8303\u5927\u5b66',
132: u'\u590d\u65e6\u5927\u5b66',
133: u'\u534e\u4e1c\u7406\u5de5\u5927\u5b66',
134: u'\u4e1c\u5317\u5927\u5b66',
135: u'\u4e1c\u534e\u5927\u5b66',
136: u'\u4e0a\u6d77\u5916\u56fd\u8bed\u5927\u5b66',
137: u'\u4e1c\u5317\u519c\u4e1a\u5927\u5b66',
138: u'\u5927\u8fde\u7406\u5de5\u5927\u5b66',
139: u'\u592a\u539f\u7406\u5de5\u5927\u5b66',
140: u'\u6e05\u534e\u5927\u5b66',
142: u'\u4e1c\u5317\u5e08\u8303\u5927\u5b66',
143: u'\u5317\u4eac\u7406\u5de5\u5927\u5b66',
144: u'\u5317\u4eac\u79d1\u6280\u5927\u5b66',
199: u'\u77f3\u6cb3\u5b50\u5927\u5b66',
330: u'\u897f\u5b89\u4ea4\u901a\u5927\u5b66',
332: u'\u897f\u5317\u519c\u6797\u79d1\u6280\u5927\u5b66',
334: u'\u9655\u897f\u5e08\u8303\u5927\u5b66',
364: u'\u897f\u85cf\u5927\u5b66',
367: u'\u9752\u6d77\u5927\u5b66',
414: u'\u4e2d\u5357\u8d22\u7ecf\u653f\u6cd5\u5927\u5b66',
417: u'\u534e\u4e2d\u519c\u4e1a\u5927\u5b66',
419: u'\u4e1c\u5317\u6797\u4e1a\u5927\u5b66',
420: u'\u534e\u4e2d\u5e08\u8303\u5927\u5b66',
504: u'\u6d77\u5357\u5927\u5b66',
544: u'\u5b81\u590f\u5927\u5b66',
556: u'\u5317\u4eac\u5316\u5de5\u5927\u5b66',
557: u'\u4e2d\u56fd\u519c\u4e1a\u5927\u5b66',
558: u'\u4e2d\u56fd\u4f20\u5a92\u5927\u5b66',
566: u'\u4e2d\u592e\u8d22\u7ecf\u5927\u5b66',
569: u'\u4e2d\u56fd\u653f\u6cd5\u5927\u5b66',
661: u'\u7535\u5b50\u79d1\u6280\u5927\u5b66',
831: u'\u534e\u5317\u7535\u529b\u5927\u5b66',
866: u'\u5317\u4eac\u4f53\u80b2\u5927\u5b66',
934: u'\u897f\u5357\u5927\u5b66',
935: u'\u8d35\u5dde\u5927\u5b66'}

``````
``````

In [175]:

schooli = score211f.columns.tolist()

``````
``````

In [184]:

us = {}
for i in range(len(u)):
us[schoold[int(schooli[i])]] = u[i]

``````
``````

In [185]:

us

``````
``````

Out[185]:

{u'\u4e0a\u6d77\u4ea4\u901a\u5927\u5b66': 0.011140064959194253,
u'\u4e0a\u6d77\u5916\u56fd\u8bed\u5927\u5b66': 0.01041024271404681,
u'\u4e0a\u6d77\u5927\u5b66': 0.010019428170856806,
u'\u4e0a\u6d77\u8d22\u7ecf\u5927\u5b66': 0.01074240454454296,
u'\u4e1c\u5317\u519c\u4e1a\u5927\u5b66': 0.009203274288002149,
u'\u4e1c\u5317\u5927\u5b66': 0.0098052732501449844,
u'\u4e1c\u5317\u5e08\u8303\u5927\u5b66': 0.0096424435559260575,
u'\u4e1c\u5317\u6797\u4e1a\u5927\u5b66': 0.0093283959164428849,
u'\u4e1c\u534e\u5927\u5b66': 0.0097124487909960519,
u'\u4e1c\u5357\u5927\u5b66': 0.010363452619660471,
u'\u4e2d\u5357\u5927\u5b66': 0.010214537680445739,
u'\u4e2d\u5357\u8d22\u7ecf\u653f\u6cd5\u5927\u5b66': 0.010197530941928762,
u'\u4e2d\u56fd\u4eba\u6c11\u5927\u5b66': 0.01107966135913196,
u'\u4e2d\u56fd\u4f20\u5a92\u5927\u5b66': 0.010292598384914762,
u'\u4e2d\u56fd\u519c\u4e1a\u5927\u5b66': 0.01002112356022236,
u'\u4e2d\u56fd\u653f\u6cd5\u5927\u5b66': 0.010495881321468318,
u'\u4e2d\u56fd\u6d77\u6d0b\u5927\u5b66': 0.0099632116488328672,
u'\u4e2d\u56fd\u77ff\u4e1a\u5927\u5b66': 0.009585398897075487,
u'\u4e2d\u56fd\u79d1\u5b66\u6280\u672f\u5927\u5b66': 0.0098346812711759459,
u'\u4e2d\u56fd\u836f\u79d1\u5927\u5b66': 0.0098803086186658885,
u'\u4e2d\u592e\u6c11\u65cf\u5927\u5b66': 0.0098283584665416028,
u'\u4e2d\u592e\u8d22\u7ecf\u5927\u5b66': 0.01076185044148744,
u'\u4e2d\u5c71\u5927\u5b66': 0.010699832988109396,
u'\u4e91\u5357\u5927\u5b66': 0.009552114493065901,
u'\u5170\u5dde\u5927\u5b66': 0.0098568298062331906,
u'\u5185\u8499\u53e4\u5927\u5b66': 0.0088620260693047567,
u'\u5317\u4eac\u4e2d\u533b\u836f\u5927\u5b66': 0.010135706829808419,
u'\u5317\u4eac\u4ea4\u901a\u5927\u5b66': 0.010183243123894665,
u'\u5317\u4eac\u4f53\u80b2\u5927\u5b66': 0.0094693074375509726,
u'\u5317\u4eac\u5316\u5de5\u5927\u5b66': 0.0097624088793884494,
u'\u5317\u4eac\u5916\u56fd\u8bed\u5927\u5b66': 0.010517187388415719,
u'\u5317\u4eac\u5927\u5b66': 0.011296686157090308,
u'\u5317\u4eac\u5de5\u4e1a\u5927\u5b66': 0.0097555234657391004,
u'\u5317\u4eac\u5e08\u8303\u5927\u5b66': 0.010507561646184565,
u'\u5317\u4eac\u6797\u4e1a\u5927\u5b66': 0.0098074209073839708,
u'\u5317\u4eac\u7406\u5de5\u5927\u5b66': 0.010441013096695713,
u'\u5317\u4eac\u79d1\u6280\u5927\u5b66': 0.0099849252380233358,
u'\u5317\u4eac\u822a\u7a7a\u822a\u5929\u5927\u5b66': 0.010482915125301664,
u'\u5317\u4eac\u90ae\u7535\u5927\u5b66': 0.010169853055121357,
u'\u534e\u4e1c\u5e08\u8303\u5927\u5b66': 0.010347879749434767,
u'\u534e\u4e1c\u7406\u5de5\u5927\u5b66': 0.0098782515250773369,
u'\u534e\u4e2d\u5e08\u8303\u5927\u5b66': 0.0097490641173139016,
u'\u534e\u4e2d\u79d1\u6280\u5927\u5b66': 0.010350751847247885,
u'\u534e\u5317\u7535\u529b\u5927\u5b66': 0.010153610403520882,
u'\u534e\u5357\u5e08\u8303\u5927\u5b66': 0.0097813431992943931,
u'\u5357\u4eac\u519c\u4e1a\u5927\u5b66': 0.0095633280862469049,
u'\u5357\u4eac\u5927\u5b66': 0.010945470069332049,
u'\u5357\u4eac\u5e08\u8303\u5927\u5b66': 0.0096738059135334058,
u'\u5357\u4eac\u7406\u5de5\u5927\u5b66': 0.0098928904138509254,
u'\u5357\u4eac\u822a\u7a7a\u822a\u5929\u5927\u5b66': 0.0099859366185302018,
u'\u5357\u5f00\u5927\u5b66': 0.010708424478904773,
u'\u5357\u660c\u5927\u5b66': 0.0096063142755705311,
u'\u53a6\u95e8\u5927\u5b66': 0.010645931422021686,
u'\u5408\u80a5\u5de5\u4e1a\u5927\u5b66': 0.0096637346737199429,
u'\u540c\u6d4e\u5927\u5b66': 0.010698866191469859,
u'\u54c8\u5c14\u6ee8\u5de5\u4e1a\u5927\u5b66': 0.010268694384304861,
u'\u54c8\u5c14\u6ee8\u5de5\u7a0b\u5927\u5b66': 0.009667811427090698,
u'\u56db\u5ddd\u519c\u4e1a\u5927\u5b66': 0.0094045163716619824,
u'\u56db\u5ddd\u5927\u5b66': 0.010367534542074164,
u'\u590d\u65e6\u5927\u5b66': 0.011149772851804813,
u'\u5927\u8fde\u6d77\u4e8b\u5927\u5b66': 0.0096351044183221948,
u'\u5927\u8fde\u7406\u5de5\u5927\u5b66': 0.0099810787699454295,
u'\u5929\u6d25\u533b\u79d1\u5927\u5b66': 0.0098101547955639669,
u'\u5929\u6d25\u5927\u5b66': 0.010401486188872168,
u'\u5b81\u590f\u5927\u5b66': 0.0092108597932755634,
u'\u5b89\u5fbd\u5927\u5b66': 0.0095783811070434197,
u'\u5bf9\u5916\u7ecf\u6d4e\u8d38\u6613\u5927\u5b66': 0.010705894886168386,
u'\u5c71\u4e1c\u5927\u5b66': 0.010318810957081068,
u'\u5e7f\u897f\u5927\u5b66': 0.0093324737548129873,
u'\u65b0\u7586\u5927\u5b66': 0.0086630110617673985,
u'\u66a8\u5357\u5927\u5b66': 0.010156460627534182,
u'\u6b66\u6c49\u5927\u5b66': 0.010623953357133828,
u'\u6b66\u6c49\u7406\u5de5\u5927\u5b66': 0.0098848609304352866,
u'\u6c5f\u5357\u5927\u5b66': 0.0097357261957205597,
u'\u6cb3\u5317\u5de5\u4e1a\u5927\u5b66': 0.0095350438217471425,
u'\u6cb3\u6d77\u5927\u5b66': 0.009815825094498333,
u'\u6d59\u6c5f\u5927\u5b66': 0.010849501969484577,
u'\u6d77\u5357\u5927\u5b66': 0.0093128540106476431,
u'\u6e05\u534e\u5927\u5b66': 0.011441501603551603,
u'\u6e56\u5357\u5927\u5b66': 0.010225552465216739,
u'\u6e56\u5357\u5e08\u8303\u5927\u5b66': 0.0095749129563526998,
u'\u7535\u5b50\u79d1\u6280\u5927\u5b66': 0.0099685900898396594,
u'\u77f3\u6cb3\u5b50\u5927\u5b66': 0.0090835149917455581,
u'\u798f\u5dde\u5927\u5b66': 0.0097508119807711933,
u'\u82cf\u5dde\u5927\u5b66': 0.010012406812894526,
u'\u897f\u5317\u519c\u6797\u79d1\u6280\u5927\u5b66': 0.0096266297472876339,
u'\u897f\u5317\u5927\u5b66': 0.0097197799934966665,
u'\u897f\u5357\u4ea4\u901a\u5927\u5b66': 0.0099126262352779819,
u'\u897f\u5357\u5927\u5b66': 0.0096739449182146713,
u'\u897f\u5357\u8d22\u7ecf\u5927\u5b66': 0.01040652082406144,
u'\u897f\u5b89\u4ea4\u901a\u5927\u5b66': 0.010383498595435931,
u'\u897f\u5b89\u7535\u5b50\u79d1\u6280\u5927\u5b66': 0.0096892839776332122,
u'\u897f\u85cf\u5927\u5b66': 0.0092778693745307408,
u'\u8d35\u5dde\u5927\u5b66': 0.0093484287745769432,
u'\u8fbd\u5b81\u5927\u5b66': 0.0095236369071646371,
u'\u90d1\u5dde\u5927\u5b66': 0.0096244348499457608,
u'\u91cd\u5e86\u5927\u5b66': 0.010210443241618759,
u'\u957f\u5b89\u5927\u5b66': 0.0097156398617498328,
u'\u9655\u897f\u5e08\u8303\u5927\u5b66': 0.0095602980982037577,
u'\u9752\u6d77\u5927\u5b66': 0.0092071322893540735}

``````
``````

In [186]:

uss = sorted(us.items(),key = lambda item:item[1],reverse=True)

``````
``````

In [187]:

for k,v in uss:
print k,v

``````
``````

``````
``````

In [ ]:

``````