numpy find the max value in a row and return back to it's column index
I have a 180295* 10 numpy array called lda_trans, row means words, and column means 10 topics.
array([[0.01841009, 0.01840699, 0.35798764, ..., 0.38443892, 0.01841072,
0.12870054],
[0.1 , 0.1 , 0.1 , ..., 0.1 , 0.1 ,
0.1 ],
[0.1 , 0.1 , 0.1 , ..., 0.1 , 0.1 ,
0.1 ],
...,
[0.0416964 , 0.62473603, 0.0416964 , ..., 0.04169395, 0.04169796,
0.04169232],
[0.03772096, 0.03775132, 0.66048403, ..., 0.03771698, 0.03772411,
0.0377139 ],
[0.03754747, 0.03756587, 0.66206395, ..., 0.03754399, 0.037551 ,
0.03753927]])
Now I want to turn back each row's maximum value's column name, I only know how to extract the max value in each row, but I don't know how to get the column name.
I know in pandas can use idxmax. But is there any similar function in Numpy? Thanks!
for i in range(180295):
lda_trans_max.append(np.max(lda_trans[i]))
python numpy
asked Nov 12 at 11:27
Shin Yu Wu
968
add a comment |
I have a 180295* 10 numpy array called lda_trans, row means words, and column means 10 topics.
array([[0.01841009, 0.01840699, 0.35798764, ..., 0.38443892, 0.01841072,
0.12870054],
[0.1 , 0.1 , 0.1 , ..., 0.1 , 0.1 ,
0.1 ],
[0.1 , 0.1 , 0.1 , ..., 0.1 , 0.1 ,
0.1 ],
...,
[0.0416964 , 0.62473603, 0.0416964 , ..., 0.04169395, 0.04169796,
0.04169232],
[0.03772096, 0.03775132, 0.66048403, ..., 0.03771698, 0.03772411,
0.0377139 ],
[0.03754747, 0.03756587, 0.66206395, ..., 0.03754399, 0.037551 ,
0.03753927]])
Now I want to turn back each row's maximum value's column name, I only know how to extract the max value in each row, but I don't know how to get the column name.
I know in pandas can use idxmax. But is there any similar function in Numpy? Thanks!
for i in range(180295):
lda_trans_max.append(np.max(lda_trans[i]))
python numpy
asked Nov 12 at 11:27
Shin Yu Wu
968
Could you make an example array that we can copy-paste? It does not have to be that large to demonstrate the desired output.
– timgeb
Nov 12 at 11:29
numpy.ndarray.argmaxand specifyaxis.
– jpp
Nov 12 at 11:30
You can usenp.argmaxwithaxis=1to get the column index of the maximum value in each row.
– jdehesa
Nov 12 at 11:30
add a comment |
I have a 180295* 10 numpy array called lda_trans, row means words, and column means 10 topics.
array([[0.01841009, 0.01840699, 0.35798764, ..., 0.38443892, 0.01841072,
0.12870054],
[0.1 , 0.1 , 0.1 , ..., 0.1 , 0.1 ,
0.1 ],
[0.1 , 0.1 , 0.1 , ..., 0.1 , 0.1 ,
0.1 ],
...,
[0.0416964 , 0.62473603, 0.0416964 , ..., 0.04169395, 0.04169796,
0.04169232],
[0.03772096, 0.03775132, 0.66048403, ..., 0.03771698, 0.03772411,
0.0377139 ],
[0.03754747, 0.03756587, 0.66206395, ..., 0.03754399, 0.037551 ,
0.03753927]])
Now I want to turn back each row's maximum value's column name, I only know how to extract the max value in each row, but I don't know how to get the column name.
I know in pandas can use idxmax. But is there any similar function in Numpy? Thanks!
for i in range(180295):
lda_trans_max.append(np.max(lda_trans[i]))
python numpy
asked Nov 12 at 11:27
Shin Yu Wu
968
I have a 180295* 10 numpy array called lda_trans, row means words, and column means 10 topics.
array([[0.01841009, 0.01840699, 0.35798764, ..., 0.38443892, 0.01841072,
0.12870054],
[0.1 , 0.1 , 0.1 , ..., 0.1 , 0.1 ,
0.1 ],
[0.1 , 0.1 , 0.1 , ..., 0.1 , 0.1 ,
0.1 ],
...,
[0.0416964 , 0.62473603, 0.0416964 , ..., 0.04169395, 0.04169796,
0.04169232],
[0.03772096, 0.03775132, 0.66048403, ..., 0.03771698, 0.03772411,
0.0377139 ],
[0.03754747, 0.03756587, 0.66206395, ..., 0.03754399, 0.037551 ,
0.03753927]])
Now I want to turn back each row's maximum value's column name, I only know how to extract the max value in each row, but I don't know how to get the column name.
I know in pandas can use idxmax. But is there any similar function in Numpy? Thanks!
for i in range(180295):
lda_trans_max.append(np.max(lda_trans[i]))
python numpy
python numpy
asked Nov 12 at 11:27
Shin Yu Wu
968
asked Nov 12 at 11:27
Shin Yu Wu
968
asked Nov 12 at 11:27
Shin Yu Wu
968
asked Nov 12 at 11:27
Shin Yu Wu
968
asked Nov 12 at 11:27
Shin Yu Wu
968
968
Could you make an example array that we can copy-paste? It does not have to be that large to demonstrate the desired output.
– timgeb
Nov 12 at 11:29
numpy.ndarray.argmaxand specifyaxis.
– jpp
Nov 12 at 11:30
You can usenp.argmaxwithaxis=1to get the column index of the maximum value in each row.
– jdehesa
Nov 12 at 11:30
add a comment |
Could you make an example array that we can copy-paste? It does not have to be that large to demonstrate the desired output.
– timgeb
Nov 12 at 11:29
numpy.ndarray.argmaxand specifyaxis.
– jpp
Nov 12 at 11:30
You can usenp.argmaxwithaxis=1to get the column index of the maximum value in each row.
– jdehesa
Nov 12 at 11:30
Could you make an example array that we can copy-paste? It does not have to be that large to demonstrate the desired output.
– timgeb
Nov 12 at 11:29
Could you make an example array that we can copy-paste? It does not have to be that large to demonstrate the desired output.
– timgeb
Nov 12 at 11:29
numpy.ndarray.argmax and specify axis.– jpp
Nov 12 at 11:30
numpy.ndarray.argmax and specify axis.– jpp
Nov 12 at 11:30
You can use
np.argmax with axis=1 to get the column index of the maximum value in each row.– jdehesa
Nov 12 at 11:30
You can use
np.argmax with axis=1 to get the column index of the maximum value in each row.– jdehesa
Nov 12 at 11:30
add a comment |
2 Answers
2
active
oldest
votes
Use np.argmax.
Demo:
>>> a
array([[0, 1, 2, 3, 4],
[5, 6, 7, 8, 9]])
>>> np.argmax(a, axis=1)
array([4, 4])
You are getting [4, 4] here because in both rows, the element with the maximum value is at position 4.
Another demo:
>>> a
array([[5, 9, 7, 6, 8],
[8, 7, 7, 6, 9]])
>>> np.argmax(a, axis=1)
array([1, 4])
answered Nov 12 at 11:31
timgeb
48.8k116390
add a comment |
Numpy quite mathematical sometimes. Try with
argmax
answered Nov 12 at 11:30
user3142459
448314
add a comment |
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
Use np.argmax.
Demo:
>>> a
array([[0, 1, 2, 3, 4],
[5, 6, 7, 8, 9]])
>>> np.argmax(a, axis=1)
array([4, 4])
You are getting [4, 4] here because in both rows, the element with the maximum value is at position 4.
Another demo:
>>> a
array([[5, 9, 7, 6, 8],
[8, 7, 7, 6, 9]])
>>> np.argmax(a, axis=1)
array([1, 4])
answered Nov 12 at 11:31
timgeb
48.8k116390
add a comment |
Use np.argmax.
Demo:
>>> a
array([[0, 1, 2, 3, 4],
[5, 6, 7, 8, 9]])
>>> np.argmax(a, axis=1)
array([4, 4])
You are getting [4, 4] here because in both rows, the element with the maximum value is at position 4.
Another demo:
>>> a
array([[5, 9, 7, 6, 8],
[8, 7, 7, 6, 9]])
>>> np.argmax(a, axis=1)
array([1, 4])
answered Nov 12 at 11:31
timgeb
48.8k116390
add a comment |
Use np.argmax.
Demo:
>>> a
array([[0, 1, 2, 3, 4],
[5, 6, 7, 8, 9]])
>>> np.argmax(a, axis=1)
array([4, 4])
You are getting [4, 4] here because in both rows, the element with the maximum value is at position 4.
Another demo:
>>> a
array([[5, 9, 7, 6, 8],
[8, 7, 7, 6, 9]])
>>> np.argmax(a, axis=1)
array([1, 4])
answered Nov 12 at 11:31
timgeb
48.8k116390
Use np.argmax.
Demo:
>>> a
array([[0, 1, 2, 3, 4],
[5, 6, 7, 8, 9]])
>>> np.argmax(a, axis=1)
array([4, 4])
You are getting [4, 4] here because in both rows, the element with the maximum value is at position 4.
Another demo:
>>> a
array([[5, 9, 7, 6, 8],
[8, 7, 7, 6, 9]])
>>> np.argmax(a, axis=1)
array([1, 4])
answered Nov 12 at 11:31
timgeb
48.8k116390
answered Nov 12 at 11:31
timgeb
48.8k116390
answered Nov 12 at 11:31
timgeb
48.8k116390
answered Nov 12 at 11:31
timgeb
48.8k116390
48.8k116390
add a comment |
add a comment |
Numpy quite mathematical sometimes. Try with
argmax
answered Nov 12 at 11:30
user3142459
448314
add a comment |
Numpy quite mathematical sometimes. Try with
argmax
answered Nov 12 at 11:30
user3142459
448314
add a comment |
Numpy quite mathematical sometimes. Try with
argmax
answered Nov 12 at 11:30
user3142459
448314
Numpy quite mathematical sometimes. Try with
argmax
answered Nov 12 at 11:30
user3142459
448314
edited Nov 12 at 13:54
answered Nov 12 at 11:30
user3142459
448314
answered Nov 12 at 11:30
user3142459
448314
answered Nov 12 at 11:30
user3142459
448314
448314
add a comment |
add a comment |
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Could you make an example array that we can copy-paste? It does not have to be that large to demonstrate the desired output.
– timgeb
Nov 12 at 11:29
numpy.ndarray.argmaxand specifyaxis.– jpp
Nov 12 at 11:30
You can use
np.argmaxwithaxis=1to get the column index of the maximum value in each row.– jdehesa
Nov 12 at 11:30