Is there a way to find the probability of different values in matrices
I thought there would be a library that would help me to do this task instead of writing many lines of codes. I tried finding some solutions from books related to my problem, but I could not find any.
One of the recent books I did read related to probability:
Python for Probability, Statistics, and Machine Learning for José
Unpingco
The task is that I have a matrix like this one below
0 1
213 vha
342 gha
523 xha
121 gha
812 gha
612 vha
123 gha
and I want the program to calculate the steps of moving from, say, vha to gha in the second row. and from gha to xha in the third row. If any step is repeated, it will be added to the previous step. For example vha to gha in the first and second rows is repeated at the end of the matrix.
The desired output is will be the similar steps added together/ total number of rows-1. In the first case it is vha to gha prob = 2/7-1
Desired output
vha to gha prob = 0.3
gha to xha prob = 0.16
xha to gha prob = 0.16
gha to gha prob = 0.16
gha to vha prob = 0.16
Total probs = 1
python python-3.x probability
asked Nov 11 '18 at 20:58
Abdulaziz Al JumaiaAbdulaziz Al Jumaia
118113
add a comment |
I thought there would be a library that would help me to do this task instead of writing many lines of codes. I tried finding some solutions from books related to my problem, but I could not find any.
One of the recent books I did read related to probability:
Python for Probability, Statistics, and Machine Learning for José
Unpingco
The task is that I have a matrix like this one below
0 1
213 vha
342 gha
523 xha
121 gha
812 gha
612 vha
123 gha
and I want the program to calculate the steps of moving from, say, vha to gha in the second row. and from gha to xha in the third row. If any step is repeated, it will be added to the previous step. For example vha to gha in the first and second rows is repeated at the end of the matrix.
The desired output is will be the similar steps added together/ total number of rows-1. In the first case it is vha to gha prob = 2/7-1
Desired output
vha to gha prob = 0.3
gha to xha prob = 0.16
xha to gha prob = 0.16
gha to gha prob = 0.16
gha to vha prob = 0.16
Total probs = 1
python python-3.x probability
asked Nov 11 '18 at 20:58
Abdulaziz Al JumaiaAbdulaziz Al Jumaia
118113
1
What datatype is this "matrix"?
– timgeb
Nov 11 '18 at 20:59
it is<class 'list'>
– Abdulaziz Al Jumaia
Nov 11 '18 at 21:04
add a comment |
I thought there would be a library that would help me to do this task instead of writing many lines of codes. I tried finding some solutions from books related to my problem, but I could not find any.
One of the recent books I did read related to probability:
Python for Probability, Statistics, and Machine Learning for José
Unpingco
The task is that I have a matrix like this one below
0 1
213 vha
342 gha
523 xha
121 gha
812 gha
612 vha
123 gha
and I want the program to calculate the steps of moving from, say, vha to gha in the second row. and from gha to xha in the third row. If any step is repeated, it will be added to the previous step. For example vha to gha in the first and second rows is repeated at the end of the matrix.
The desired output is will be the similar steps added together/ total number of rows-1. In the first case it is vha to gha prob = 2/7-1
Desired output
vha to gha prob = 0.3
gha to xha prob = 0.16
xha to gha prob = 0.16
gha to gha prob = 0.16
gha to vha prob = 0.16
Total probs = 1
python python-3.x probability
asked Nov 11 '18 at 20:58
Abdulaziz Al JumaiaAbdulaziz Al Jumaia
118113
I thought there would be a library that would help me to do this task instead of writing many lines of codes. I tried finding some solutions from books related to my problem, but I could not find any.
One of the recent books I did read related to probability:
Python for Probability, Statistics, and Machine Learning for José
Unpingco
The task is that I have a matrix like this one below
0 1
213 vha
342 gha
523 xha
121 gha
812 gha
612 vha
123 gha
and I want the program to calculate the steps of moving from, say, vha to gha in the second row. and from gha to xha in the third row. If any step is repeated, it will be added to the previous step. For example vha to gha in the first and second rows is repeated at the end of the matrix.
The desired output is will be the similar steps added together/ total number of rows-1. In the first case it is vha to gha prob = 2/7-1
Desired output
vha to gha prob = 0.3
gha to xha prob = 0.16
xha to gha prob = 0.16
gha to gha prob = 0.16
gha to vha prob = 0.16
Total probs = 1
python python-3.x probability
python python-3.x probability
asked Nov 11 '18 at 20:58
Abdulaziz Al JumaiaAbdulaziz Al Jumaia
118113
asked Nov 11 '18 at 20:58
Abdulaziz Al JumaiaAbdulaziz Al Jumaia
118113
asked Nov 11 '18 at 20:58
Abdulaziz Al JumaiaAbdulaziz Al Jumaia
118113
asked Nov 11 '18 at 20:58
Abdulaziz Al JumaiaAbdulaziz Al Jumaia
118113
asked Nov 11 '18 at 20:58
Abdulaziz Al JumaiaAbdulaziz Al Jumaia
118113
118113
1
What datatype is this "matrix"?
– timgeb
Nov 11 '18 at 20:59
it is<class 'list'>
– Abdulaziz Al Jumaia
Nov 11 '18 at 21:04
add a comment |
1
What datatype is this "matrix"?
– timgeb
Nov 11 '18 at 20:59
it is<class 'list'>
– Abdulaziz Al Jumaia
Nov 11 '18 at 21:04
1
1
What datatype is this "matrix"?
– timgeb
Nov 11 '18 at 20:59
What datatype is this "matrix"?
– timgeb
Nov 11 '18 at 20:59
it is
<class 'list'>– Abdulaziz Al Jumaia
Nov 11 '18 at 21:04
it is
<class 'list'>– Abdulaziz Al Jumaia
Nov 11 '18 at 21:04
add a comment |
1 Answer
1
active
oldest
votes
You can use a Counter to count how many times a transition occurs and then calculate probabilities for each transition.
You can use zip to combine two slices of the list m - one with the last element removed and another with the first element removed - to get tuples for adjacent elements. zip(m[:-1], m[1:]) does that. Then can you can count similar tuples - which represent transitions - with a Counter:
from collections import Counter
m = [[213, 'vha'],
[342, 'gha'],
[523, 'xha'],
[121, 'gha'],
[812, 'gha'],
[612, 'vha'],
[123, 'gha']]
c = Counter([(x[1], y[1]) for x, y in zip(m[:-1], m[1:])])
probs = [(e, v / (len(m) - 1)) for e, v in c.items()]
for p in probs:
print(p)
Output
(('vha', 'gha'), 0.3333333333333333)
(('gha', 'xha'), 0.16666666666666666)
(('xha', 'gha'), 0.16666666666666666)
(('gha', 'gha'), 0.16666666666666666)
(('gha', 'vha'), 0.16666666666666666)
answered Nov 11 '18 at 21:12
sliderslider
8,21811129
Amazing! the code is working. I have accepted your answer. I am just wondering if you can explain how the program works or refer me to a link with an explanation. Regards
– Abdulaziz Al Jumaia
Nov 12 '18 at 22:44
@AbdulazizAlJumaia I've added links to documentation an a more detailed explanation. Hope that helps!
– slider
Nov 12 '18 at 23:06
It does :). Thanks
– Abdulaziz Al Jumaia
Nov 13 '18 at 8:31
add a comment |
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1 Answer
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1 Answer
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active
oldest
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oldest
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active
oldest
votes
You can use a Counter to count how many times a transition occurs and then calculate probabilities for each transition.
You can use zip to combine two slices of the list m - one with the last element removed and another with the first element removed - to get tuples for adjacent elements. zip(m[:-1], m[1:]) does that. Then can you can count similar tuples - which represent transitions - with a Counter:
from collections import Counter
m = [[213, 'vha'],
[342, 'gha'],
[523, 'xha'],
[121, 'gha'],
[812, 'gha'],
[612, 'vha'],
[123, 'gha']]
c = Counter([(x[1], y[1]) for x, y in zip(m[:-1], m[1:])])
probs = [(e, v / (len(m) - 1)) for e, v in c.items()]
for p in probs:
print(p)
Output
(('vha', 'gha'), 0.3333333333333333)
(('gha', 'xha'), 0.16666666666666666)
(('xha', 'gha'), 0.16666666666666666)
(('gha', 'gha'), 0.16666666666666666)
(('gha', 'vha'), 0.16666666666666666)
answered Nov 11 '18 at 21:12
sliderslider
8,21811129
Amazing! the code is working. I have accepted your answer. I am just wondering if you can explain how the program works or refer me to a link with an explanation. Regards
– Abdulaziz Al Jumaia
Nov 12 '18 at 22:44
@AbdulazizAlJumaia I've added links to documentation an a more detailed explanation. Hope that helps!
– slider
Nov 12 '18 at 23:06
It does :). Thanks
– Abdulaziz Al Jumaia
Nov 13 '18 at 8:31
add a comment |
You can use a Counter to count how many times a transition occurs and then calculate probabilities for each transition.
You can use zip to combine two slices of the list m - one with the last element removed and another with the first element removed - to get tuples for adjacent elements. zip(m[:-1], m[1:]) does that. Then can you can count similar tuples - which represent transitions - with a Counter:
from collections import Counter
m = [[213, 'vha'],
[342, 'gha'],
[523, 'xha'],
[121, 'gha'],
[812, 'gha'],
[612, 'vha'],
[123, 'gha']]
c = Counter([(x[1], y[1]) for x, y in zip(m[:-1], m[1:])])
probs = [(e, v / (len(m) - 1)) for e, v in c.items()]
for p in probs:
print(p)
Output
(('vha', 'gha'), 0.3333333333333333)
(('gha', 'xha'), 0.16666666666666666)
(('xha', 'gha'), 0.16666666666666666)
(('gha', 'gha'), 0.16666666666666666)
(('gha', 'vha'), 0.16666666666666666)
answered Nov 11 '18 at 21:12
sliderslider
8,21811129
Amazing! the code is working. I have accepted your answer. I am just wondering if you can explain how the program works or refer me to a link with an explanation. Regards
– Abdulaziz Al Jumaia
Nov 12 '18 at 22:44
@AbdulazizAlJumaia I've added links to documentation an a more detailed explanation. Hope that helps!
– slider
Nov 12 '18 at 23:06
It does :). Thanks
– Abdulaziz Al Jumaia
Nov 13 '18 at 8:31
add a comment |
You can use a Counter to count how many times a transition occurs and then calculate probabilities for each transition.
You can use zip to combine two slices of the list m - one with the last element removed and another with the first element removed - to get tuples for adjacent elements. zip(m[:-1], m[1:]) does that. Then can you can count similar tuples - which represent transitions - with a Counter:
from collections import Counter
m = [[213, 'vha'],
[342, 'gha'],
[523, 'xha'],
[121, 'gha'],
[812, 'gha'],
[612, 'vha'],
[123, 'gha']]
c = Counter([(x[1], y[1]) for x, y in zip(m[:-1], m[1:])])
probs = [(e, v / (len(m) - 1)) for e, v in c.items()]
for p in probs:
print(p)
Output
(('vha', 'gha'), 0.3333333333333333)
(('gha', 'xha'), 0.16666666666666666)
(('xha', 'gha'), 0.16666666666666666)
(('gha', 'gha'), 0.16666666666666666)
(('gha', 'vha'), 0.16666666666666666)
answered Nov 11 '18 at 21:12
sliderslider
8,21811129
You can use a Counter to count how many times a transition occurs and then calculate probabilities for each transition.
You can use zip to combine two slices of the list m - one with the last element removed and another with the first element removed - to get tuples for adjacent elements. zip(m[:-1], m[1:]) does that. Then can you can count similar tuples - which represent transitions - with a Counter:
from collections import Counter
m = [[213, 'vha'],
[342, 'gha'],
[523, 'xha'],
[121, 'gha'],
[812, 'gha'],
[612, 'vha'],
[123, 'gha']]
c = Counter([(x[1], y[1]) for x, y in zip(m[:-1], m[1:])])
probs = [(e, v / (len(m) - 1)) for e, v in c.items()]
for p in probs:
print(p)
Output
(('vha', 'gha'), 0.3333333333333333)
(('gha', 'xha'), 0.16666666666666666)
(('xha', 'gha'), 0.16666666666666666)
(('gha', 'gha'), 0.16666666666666666)
(('gha', 'vha'), 0.16666666666666666)
answered Nov 11 '18 at 21:12
sliderslider
8,21811129
edited Nov 12 '18 at 23:05
answered Nov 11 '18 at 21:12
sliderslider
8,21811129
answered Nov 11 '18 at 21:12
sliderslider
8,21811129
answered Nov 11 '18 at 21:12
sliderslider
8,21811129
8,21811129
Amazing! the code is working. I have accepted your answer. I am just wondering if you can explain how the program works or refer me to a link with an explanation. Regards
– Abdulaziz Al Jumaia
Nov 12 '18 at 22:44
@AbdulazizAlJumaia I've added links to documentation an a more detailed explanation. Hope that helps!
– slider
Nov 12 '18 at 23:06
It does :). Thanks
– Abdulaziz Al Jumaia
Nov 13 '18 at 8:31
add a comment |
Amazing! the code is working. I have accepted your answer. I am just wondering if you can explain how the program works or refer me to a link with an explanation. Regards
– Abdulaziz Al Jumaia
Nov 12 '18 at 22:44
@AbdulazizAlJumaia I've added links to documentation an a more detailed explanation. Hope that helps!
– slider
Nov 12 '18 at 23:06
It does :). Thanks
– Abdulaziz Al Jumaia
Nov 13 '18 at 8:31
Amazing! the code is working. I have accepted your answer. I am just wondering if you can explain how the program works or refer me to a link with an explanation. Regards
– Abdulaziz Al Jumaia
Nov 12 '18 at 22:44
Amazing! the code is working. I have accepted your answer. I am just wondering if you can explain how the program works or refer me to a link with an explanation. Regards
– Abdulaziz Al Jumaia
Nov 12 '18 at 22:44
@AbdulazizAlJumaia I've added links to documentation an a more detailed explanation. Hope that helps!
– slider
Nov 12 '18 at 23:06
@AbdulazizAlJumaia I've added links to documentation an a more detailed explanation. Hope that helps!
– slider
Nov 12 '18 at 23:06
It does :). Thanks
– Abdulaziz Al Jumaia
Nov 13 '18 at 8:31
It does :). Thanks
– Abdulaziz Al Jumaia
Nov 13 '18 at 8:31
add a comment |
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1
What datatype is this "matrix"?
– timgeb
Nov 11 '18 at 20:59
it is
<class 'list'>– Abdulaziz Al Jumaia
Nov 11 '18 at 21:04