In [1]:
import pandas as pd
import numpy as np
In [23]:
embeddings=pd.read_csv('embeddings.csv')
In [28]:
embeddings.head()
Out[28]:
Unnamed: 0
0
1
2
3
4
5
6
7
8
...
118
119
120
121
122
123
124
125
126
127
0
Shriman
0.010654
0.102186
0.085343
0.111366
0.051246
0.113140
0.016714
-0.142586
0.086939
...
0.113959
0.156113
0.084041
-0.055712
-0.074948
0.100123
0.089271
0.078698
0.080655
-0.059964
1
Shriman
0.004630
0.171056
0.037819
0.040723
-0.014402
0.167380
-0.012677
-0.041801
0.106762
...
0.220064
0.116528
0.119928
-0.082288
-0.050742
0.088881
0.136381
-0.039299
0.127808
-0.021552
2
Shriman
0.023361
0.123029
0.050470
0.117905
0.039160
0.155295
-0.047102
-0.143670
0.044940
...
0.104026
0.172125
0.093524
-0.101011
-0.104542
0.044875
0.075668
0.077950
0.104503
-0.023734
3
Shriman
0.065859
0.091799
0.015506
0.124875
0.003298
0.171261
-0.029486
-0.094612
0.024684
...
0.143596
0.133888
0.071432
-0.135525
-0.042875
0.106044
0.115926
0.060736
0.136038
0.005710
4
Shriman
-0.016684
0.051855
0.005324
-0.021940
0.055423
0.110600
-0.062536
0.057446
-0.045964
...
0.059726
0.081304
0.084345
0.045121
0.002741
0.141093
0.026653
-0.020410
0.140133
0.090626
5 rows × 129 columns
In [32]:
embeddings.columns
Out[32]:
Index([u'Unnamed: 0', u'0', u'1', u'2', u'3', u'4', u'5', u'6', u'7', u'8',
...
u'118', u'119', u'120', u'121', u'122', u'123', u'124', u'125', u'126',
u'127'],
dtype='object', length=129)
In [34]:
embeddings.index=embeddings['Unnamed: 0']
In [ ]:
Content source: nmabhi/Webface
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