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16

1

I want to write this code as pythonic. My real array much bigger than this example.

( 5+10+20+3+2 ) / 5

print(np.mean(array,key=lambda x:x[1]))
TypeError: mean() got an unexpected keyword argument 'key'

array = [('a', 5) , ('b', 10), ('c', 20), ('d', 3), ('e', 2)]



sum = 0

for i in range(len(array)):

    sum = sum + array[i][1]



average = sum / len(array)

print(average)



import numpy as np

print(np.mean(array,key=lambda x:x[1]))

How can avoid this?
I want to use second example.

python arrays python-3.x tuples average

share|improve this question

edited 14 hours ago

ruohola

1,940420

asked 16 hours ago

Şevval KahramanŞevval Kahraman

1327

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  What version of Python are you using?
  
  – Peter Wood
  16 hours ago
  

  
  
  
  


• 
  
  
  

  
  1
  

  
  
  
  
  
  

  
  
  @PeterWood python 3.7
  
  – Şevval Kahraman
  15 hours ago
  

  
  
  
  

add a comment | 

16

1

I want to write this code as pythonic. My real array much bigger than this example.

( 5+10+20+3+2 ) / 5

print(np.mean(array,key=lambda x:x[1]))
TypeError: mean() got an unexpected keyword argument 'key'

array = [('a', 5) , ('b', 10), ('c', 20), ('d', 3), ('e', 2)]



sum = 0

for i in range(len(array)):

    sum = sum + array[i][1]



average = sum / len(array)

print(average)



import numpy as np

print(np.mean(array,key=lambda x:x[1]))

How can avoid this?
I want to use second example.

python arrays python-3.x tuples average

share|improve this question

edited 14 hours ago

ruohola

1,940420

asked 16 hours ago

Şevval KahramanŞevval Kahraman

1327

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  What version of Python are you using?
  
  – Peter Wood
  16 hours ago
  

  
  
  
  


• 
  
  
  

  
  1
  

  
  
  
  
  
  

  
  
  @PeterWood python 3.7
  
  – Şevval Kahraman
  15 hours ago
  

  
  
  
  

add a comment | 

I want to write this code as pythonic. My real array much bigger than this example.

( 5+10+20+3+2 ) / 5

print(np.mean(array,key=lambda x:x[1]))
TypeError: mean() got an unexpected keyword argument 'key'

array = [('a', 5) , ('b', 10), ('c', 20), ('d', 3), ('e', 2)]



sum = 0

for i in range(len(array)):

    sum = sum + array[i][1]



average = sum / len(array)

print(average)



import numpy as np

print(np.mean(array,key=lambda x:x[1]))

How can avoid this?
I want to use second example.

python arrays python-3.x tuples average

share|improve this question

edited 14 hours ago

ruohola

1,940420

asked 16 hours ago

Şevval KahramanŞevval Kahraman

1327

array = [('a', 5) , ('b', 10), ('c', 20), ('d', 3), ('e', 2)]



sum = 0

for i in range(len(array)):

    sum = sum + array[i][1]



average = sum / len(array)

print(average)



import numpy as np

print(np.mean(array,key=lambda x:x[1]))

share|improve this question

edited 14 hours ago

ruohola

1,940420

asked 16 hours ago

Şevval KahramanŞevval Kahraman

1327

share|improve this question

edited 14 hours ago

ruohola

1,940420

asked 16 hours ago

Şevval KahramanŞevval Kahraman

1327

edited 14 hours ago

ruohola

1,940420

edited 14 hours ago

ruohola

1,940420

asked 16 hours ago

Şevval KahramanŞevval Kahraman

1327

asked 16 hours ago

Şevval KahramanŞevval Kahraman

1327

8 Answers
8

active

oldest

votes

22

If you are using Python 3.4 or above, you could use the statistics module:

from statistics import mean



average = mean(value[1] for value in array)

Or if you're using a version of Python older than 3.4:

average = sum(value[1] for value in array) / len(array)

If you're using Python 2, and you're summing integers, we will have integer division, which will truncate the result, e.g:

>>> 25 / 4

6



>>> 25 / float(4)

6.25

To ensure we don't have integer division we could set the starting value of sum to be the float value 0.0. However, this also means we have to make the loop over the values in the array into a comprehension expression, otherwise it's a syntax error, and it's less pretty, as noted in the comments:

average = sum((value[1] for value in array), 0.0) / len(array)

It's probably best to use fsum from the math module which will return a float:

from math import fsum



average = fsum(value[1] for value in array) / len(array)

share|improve this answer

edited 14 hours ago

answered 16 hours ago

Peter WoodPeter Wood

16.9k33877

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  I realised there are better ways to do the Python 2 code. sum takes an argument for the starting value. If you pass 0.0 to it, then the numerator will always be floating point, nothing to worry about. Also, there is a function in the math module, fsum.
  
  – Peter Wood
  15 hours ago
  

  
  
  
  


• 
  
  
  

  
  4
  

  
  
  
  
  
  

  
  
  I would say the float casting way is little bit more self-explanatory than passing a weird 0.0 value argument for the sum.
  
  – ruohola
  14 hours ago
  
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  @ruohola I think using fsum is probably best for Python 2.
  
  – Peter Wood
  14 hours ago
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Can't you from __future__ import division?
  
  – DanielSank
  2 hours ago
  
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  @DanielSank yes, that's another option. Another advantage of using fsum, if you're summing floats, is it keeps track of partial sums, which compensates for lack of precision in the floating point representation. So, if we stay using fsum we don't need to think about integer division at all, and are generally the better solution too. See my answer about Kahan Summation in c++.
  
  – Peter Wood
  2 hours ago
  

  
  
  
  

add a comment | 

4

If you do want to use numpy, cast it to a numpy.array and select the axis you want using numpy indexing:

import numpy as np



array = np.array([('a', 5) , ('b', 10), ('c', 20), ('d', 3), ('e', 2)])

print(array[:,1].astype(float).mean())

# 8.0

The cast to a numeric type is needed because the original array contains both strings and numbers and is therefore of type object. In this case you could use float or int, it makes no difference.

share|improve this answer

edited 13 hours ago

answered 13 hours ago

GraipherGraipher

4,7191634

add a comment | 

3

You can simply use:

print(sum(tup[1] for tup in array) / len(array))

Or for Python 2:

print(sum(tup[1] for tup in array) / float(len(array)))

Or little bit more concisely for Python 2:

from math import fsum



print(fsum(tup[1] for tup in array) / len(array))

share|improve this answer

edited 14 hours ago

answered 16 hours ago

ruoholaruohola

1,940420

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  it gives this error : 'int' object is not callable
  
  – Şevval Kahraman
  16 hours ago
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  @ŞevvalKahraman it gives no errors for me with your example array, you probably have a typo somewhere.
  
  – ruohola
  15 hours ago
  
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  @ruohola The reason it works for the example is it's 40 / 5 which gives 8 with no remainder. In Python 2, with different numbers, it could truncate the answer.
  
  – Peter Wood
  15 hours ago
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  @PeterWood it will not truncate anything if you use the float(len(array)) casting when using Python 2. Anyways it shouldn't even matter since this question was for Python 3.x.
  
  – ruohola
  14 hours ago
  
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  As it's python 3, just use statistics.mean.
  
  – Peter Wood
  12 hours ago
  

  
  
  
  

add a comment | 

2

With pure Python:

from operator import itemgetter



acc = 0

count = 0



for value in map(itemgetter(1), array):

    acc += value

    count += 1



mean = acc / count

An iterative approach can be preferable if your data cannot fit in memory as a list (since you said it was big). If it can, prefer a declarative approach:

data = [sub[1] for sub in array]

mean = sum(data) / len(data)

If you are open to using numpy, I find this cleaner:

a = np.array(array)



mean = a[:, 1].astype(int).mean()

share|improve this answer

edited 16 hours ago

answered 16 hours ago

gmdsgmds

8,093932

add a comment | 

1

you can use map instead of list comprehension

sum(map(lambda x:int(x[1]), array)) / len(array)

or functools.reduce (if you use Python2.X just reduce not functools.reduce)

import functools

functools.reduce(lambda acc, y: acc + y[1], array, 0) / len(array)

share|improve this answer

edited 16 hours ago

answered 16 hours ago

minjiminji

167110

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  first one gives this error : 'int' object is not callable
  
  – Şevval Kahraman
  15 hours ago
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  @ŞevvalKahraman if array is defined as shown in your question - the first one give 8.0 (tested & verified on same version). So either the array your using has a different value somewhere or you made a typo
  
  – JGreenwell
  11 hours ago
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  x[1] is already an integer, why do you need to call int()?
  
  – Barmar
  6 hours ago
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Using a lambda is 30% slower than a generator comprehension. But if you prefer map, I recommend using operator.itemgetter(1) instead of the lambda.
  
  – Mateen Ulhaq
  52 mins ago
  
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Similarly, functools.reduce is 72% slower than a generator comprehension and sum.
  
  – Mateen Ulhaq
  51 mins ago
  
  
  

  
  
  
  

add a comment | 

1

If you're open to more golf-like solutions, you can transpose your array with vanilla python, get a list of just the numbers, and calculate the mean with

sum(zip(*array)[1])/len(array)

share|improve this answer

answered 2 hours ago

Nick AminNick Amin

111

New contributor

Nick Amin is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

add a comment | 

0

You could use map:

np.mean(list(map(lambda x: x[1], array)))

share|improve this answer

answered 16 hours ago

pdpinopdpino

1647

add a comment | 

0

Just find the average using sum and number of elements of the list.

array = [('a', 5) , ('b', 10), ('c', 20), ('d', 3), ('e', 2)]

avg = float(sum(value[1] for value in array)) / float(len(array))

print(avg)

#8.0

share|improve this answer

edited 16 hours ago

answered 16 hours ago

Devesh Kumar SinghDevesh Kumar Singh

3,6401425

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Fixed it, Thank you for the suggestion @PeterWood
  
  – Devesh Kumar Singh
  16 hours ago
  

  
  
  
  

add a comment | 

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22

If you are using Python 3.4 or above, you could use the statistics module:

from statistics import mean



average = mean(value[1] for value in array)

Or if you're using a version of Python older than 3.4:

average = sum(value[1] for value in array) / len(array)

If you're using Python 2, and you're summing integers, we will have integer division, which will truncate the result, e.g:

>>> 25 / 4

6



>>> 25 / float(4)

6.25

To ensure we don't have integer division we could set the starting value of sum to be the float value 0.0. However, this also means we have to make the loop over the values in the array into a comprehension expression, otherwise it's a syntax error, and it's less pretty, as noted in the comments:

average = sum((value[1] for value in array), 0.0) / len(array)

It's probably best to use fsum from the math module which will return a float:

from math import fsum



average = fsum(value[1] for value in array) / len(array)

share|improve this answer

edited 14 hours ago

answered 16 hours ago

Peter WoodPeter Wood

16.9k33877

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  I realised there are better ways to do the Python 2 code. sum takes an argument for the starting value. If you pass 0.0 to it, then the numerator will always be floating point, nothing to worry about. Also, there is a function in the math module, fsum.
  
  – Peter Wood
  15 hours ago
  

  
  
  
  


• 
  
  
  

  
  4
  

  
  
  
  
  
  

  
  
  I would say the float casting way is little bit more self-explanatory than passing a weird 0.0 value argument for the sum.
  
  – ruohola
  14 hours ago
  
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  @ruohola I think using fsum is probably best for Python 2.
  
  – Peter Wood
  14 hours ago
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Can't you from __future__ import division?
  
  – DanielSank
  2 hours ago
  
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  @DanielSank yes, that's another option. Another advantage of using fsum, if you're summing floats, is it keeps track of partial sums, which compensates for lack of precision in the floating point representation. So, if we stay using fsum we don't need to think about integer division at all, and are generally the better solution too. See my answer about Kahan Summation in c++.
  
  – Peter Wood
  2 hours ago
  

  
  
  
  

add a comment | 

22

If you are using Python 3.4 or above, you could use the statistics module:

from statistics import mean



average = mean(value[1] for value in array)

Or if you're using a version of Python older than 3.4:

average = sum(value[1] for value in array) / len(array)

If you're using Python 2, and you're summing integers, we will have integer division, which will truncate the result, e.g:

>>> 25 / 4

6



>>> 25 / float(4)

6.25

To ensure we don't have integer division we could set the starting value of sum to be the float value 0.0. However, this also means we have to make the loop over the values in the array into a comprehension expression, otherwise it's a syntax error, and it's less pretty, as noted in the comments:

average = sum((value[1] for value in array), 0.0) / len(array)

It's probably best to use fsum from the math module which will return a float:

from math import fsum



average = fsum(value[1] for value in array) / len(array)

share|improve this answer

edited 14 hours ago

answered 16 hours ago

Peter WoodPeter Wood

16.9k33877

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  I realised there are better ways to do the Python 2 code. sum takes an argument for the starting value. If you pass 0.0 to it, then the numerator will always be floating point, nothing to worry about. Also, there is a function in the math module, fsum.
  
  – Peter Wood
  15 hours ago
  

  
  
  
  


• 
  
  
  

  
  4
  

  
  
  
  
  
  

  
  
  I would say the float casting way is little bit more self-explanatory than passing a weird 0.0 value argument for the sum.
  
  – ruohola
  14 hours ago
  
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  @ruohola I think using fsum is probably best for Python 2.
  
  – Peter Wood
  14 hours ago
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Can't you from __future__ import division?
  
  – DanielSank
  2 hours ago
  
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  @DanielSank yes, that's another option. Another advantage of using fsum, if you're summing floats, is it keeps track of partial sums, which compensates for lack of precision in the floating point representation. So, if we stay using fsum we don't need to think about integer division at all, and are generally the better solution too. See my answer about Kahan Summation in c++.
  
  – Peter Wood
  2 hours ago
  

  
  
  
  

add a comment | 

If you are using Python 3.4 or above, you could use the statistics module:

from statistics import mean



average = mean(value[1] for value in array)

Or if you're using a version of Python older than 3.4:

average = sum(value[1] for value in array) / len(array)

If you're using Python 2, and you're summing integers, we will have integer division, which will truncate the result, e.g:

>>> 25 / 4

6



>>> 25 / float(4)

6.25

To ensure we don't have integer division we could set the starting value of sum to be the float value 0.0. However, this also means we have to make the loop over the values in the array into a comprehension expression, otherwise it's a syntax error, and it's less pretty, as noted in the comments:

average = sum((value[1] for value in array), 0.0) / len(array)

It's probably best to use fsum from the math module which will return a float:

from math import fsum



average = fsum(value[1] for value in array) / len(array)

share|improve this answer

edited 14 hours ago

answered 16 hours ago

Peter WoodPeter Wood

16.9k33877

from statistics import mean



average = mean(value[1] for value in array)

average = sum(value[1] for value in array) / len(array)

>>> 25 / 4

6



>>> 25 / float(4)

6.25

average = sum((value[1] for value in array), 0.0) / len(array)

from math import fsum



average = fsum(value[1] for value in array) / len(array)

share|improve this answer

edited 14 hours ago

answered 16 hours ago

Peter WoodPeter Wood

16.9k33877

answered 16 hours ago

Peter WoodPeter Wood

16.9k33877

answered 16 hours ago

Peter WoodPeter Wood

16.9k33877

4

If you do want to use numpy, cast it to a numpy.array and select the axis you want using numpy indexing:

import numpy as np



array = np.array([('a', 5) , ('b', 10), ('c', 20), ('d', 3), ('e', 2)])

print(array[:,1].astype(float).mean())

# 8.0

The cast to a numeric type is needed because the original array contains both strings and numbers and is therefore of type object. In this case you could use float or int, it makes no difference.

share|improve this answer

edited 13 hours ago

answered 13 hours ago

GraipherGraipher

4,7191634

add a comment | 

4

If you do want to use numpy, cast it to a numpy.array and select the axis you want using numpy indexing:

import numpy as np



array = np.array([('a', 5) , ('b', 10), ('c', 20), ('d', 3), ('e', 2)])

print(array[:,1].astype(float).mean())

# 8.0

The cast to a numeric type is needed because the original array contains both strings and numbers and is therefore of type object. In this case you could use float or int, it makes no difference.

share|improve this answer

edited 13 hours ago

answered 13 hours ago

GraipherGraipher

4,7191634

add a comment | 

If you do want to use numpy, cast it to a numpy.array and select the axis you want using numpy indexing:

import numpy as np



array = np.array([('a', 5) , ('b', 10), ('c', 20), ('d', 3), ('e', 2)])

print(array[:,1].astype(float).mean())

# 8.0

The cast to a numeric type is needed because the original array contains both strings and numbers and is therefore of type object. In this case you could use float or int, it makes no difference.

share|improve this answer

edited 13 hours ago

answered 13 hours ago

GraipherGraipher

4,7191634

import numpy as np



array = np.array([('a', 5) , ('b', 10), ('c', 20), ('d', 3), ('e', 2)])

print(array[:,1].astype(float).mean())

# 8.0

share|improve this answer

edited 13 hours ago

answered 13 hours ago

GraipherGraipher

4,7191634

answered 13 hours ago

GraipherGraipher

4,7191634

answered 13 hours ago

GraipherGraipher

4,7191634

3

You can simply use:

print(sum(tup[1] for tup in array) / len(array))

Or for Python 2:

print(sum(tup[1] for tup in array) / float(len(array)))

Or little bit more concisely for Python 2:

from math import fsum



print(fsum(tup[1] for tup in array) / len(array))

share|improve this answer

edited 14 hours ago

answered 16 hours ago

ruoholaruohola

1,940420

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  it gives this error : 'int' object is not callable
  
  – Şevval Kahraman
  16 hours ago
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  @ŞevvalKahraman it gives no errors for me with your example array, you probably have a typo somewhere.
  
  – ruohola
  15 hours ago
  
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  @ruohola The reason it works for the example is it's 40 / 5 which gives 8 with no remainder. In Python 2, with different numbers, it could truncate the answer.
  
  – Peter Wood
  15 hours ago
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  @PeterWood it will not truncate anything if you use the float(len(array)) casting when using Python 2. Anyways it shouldn't even matter since this question was for Python 3.x.
  
  – ruohola
  14 hours ago
  
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  As it's python 3, just use statistics.mean.
  
  – Peter Wood
  12 hours ago
  

  
  
  
  

add a comment | 

3

You can simply use:

print(sum(tup[1] for tup in array) / len(array))

Or for Python 2:

print(sum(tup[1] for tup in array) / float(len(array)))

Or little bit more concisely for Python 2:

from math import fsum



print(fsum(tup[1] for tup in array) / len(array))

share|improve this answer

edited 14 hours ago

answered 16 hours ago

ruoholaruohola

1,940420

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  it gives this error : 'int' object is not callable
  
  – Şevval Kahraman
  16 hours ago
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  @ŞevvalKahraman it gives no errors for me with your example array, you probably have a typo somewhere.
  
  – ruohola
  15 hours ago
  
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  @ruohola The reason it works for the example is it's 40 / 5 which gives 8 with no remainder. In Python 2, with different numbers, it could truncate the answer.
  
  – Peter Wood
  15 hours ago
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  @PeterWood it will not truncate anything if you use the float(len(array)) casting when using Python 2. Anyways it shouldn't even matter since this question was for Python 3.x.
  
  – ruohola
  14 hours ago
  
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  As it's python 3, just use statistics.mean.
  
  – Peter Wood
  12 hours ago
  

  
  
  
  

add a comment | 

You can simply use:

print(sum(tup[1] for tup in array) / len(array))

Or for Python 2:

print(sum(tup[1] for tup in array) / float(len(array)))

Or little bit more concisely for Python 2:

from math import fsum



print(fsum(tup[1] for tup in array) / len(array))

share|improve this answer

edited 14 hours ago

answered 16 hours ago

ruoholaruohola

1,940420

print(sum(tup[1] for tup in array) / len(array))

print(sum(tup[1] for tup in array) / float(len(array)))

from math import fsum



print(fsum(tup[1] for tup in array) / len(array))

share|improve this answer

edited 14 hours ago

answered 16 hours ago

ruoholaruohola

1,940420

answered 16 hours ago

ruoholaruohola

1,940420

answered 16 hours ago

ruoholaruohola

1,940420

2

With pure Python:

from operator import itemgetter



acc = 0

count = 0



for value in map(itemgetter(1), array):

    acc += value

    count += 1



mean = acc / count

An iterative approach can be preferable if your data cannot fit in memory as a list (since you said it was big). If it can, prefer a declarative approach:

data = [sub[1] for sub in array]

mean = sum(data) / len(data)

If you are open to using numpy, I find this cleaner:

a = np.array(array)



mean = a[:, 1].astype(int).mean()

share|improve this answer

edited 16 hours ago

answered 16 hours ago

gmdsgmds

8,093932

add a comment | 

2

With pure Python:

from operator import itemgetter



acc = 0

count = 0



for value in map(itemgetter(1), array):

    acc += value

    count += 1



mean = acc / count

An iterative approach can be preferable if your data cannot fit in memory as a list (since you said it was big). If it can, prefer a declarative approach:

data = [sub[1] for sub in array]

mean = sum(data) / len(data)

If you are open to using numpy, I find this cleaner:

a = np.array(array)



mean = a[:, 1].astype(int).mean()

share|improve this answer

edited 16 hours ago

answered 16 hours ago

gmdsgmds

8,093932

add a comment | 

With pure Python:

from operator import itemgetter



acc = 0

count = 0



for value in map(itemgetter(1), array):

    acc += value

    count += 1



mean = acc / count

An iterative approach can be preferable if your data cannot fit in memory as a list (since you said it was big). If it can, prefer a declarative approach:

data = [sub[1] for sub in array]

mean = sum(data) / len(data)

If you are open to using numpy, I find this cleaner:

a = np.array(array)



mean = a[:, 1].astype(int).mean()

share|improve this answer

edited 16 hours ago

answered 16 hours ago

gmdsgmds

8,093932

from operator import itemgetter



acc = 0

count = 0



for value in map(itemgetter(1), array):

    acc += value

    count += 1



mean = acc / count

data = [sub[1] for sub in array]

mean = sum(data) / len(data)

a = np.array(array)



mean = a[:, 1].astype(int).mean()

share|improve this answer

edited 16 hours ago

answered 16 hours ago

gmdsgmds

8,093932