Is there any pythonic way to find average of specific tuple elements in array?





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10















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

























  • What version of Python are you using?

    – Peter Wood
    5 hours ago






  • 1





    @PeterWood python 3.7

    – Şevval Kahraman
    4 hours ago


















10















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

























  • What version of Python are you using?

    – Peter Wood
    5 hours ago






  • 1





    @PeterWood python 3.7

    – Şevval Kahraman
    4 hours ago














10












10








10


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
















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




python arrays python-3.x tuples average






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited 4 hours ago









ruohola

1,902420




1,902420










asked 6 hours ago









Şevval KahramanŞevval Kahraman

966




966













  • What version of Python are you using?

    – Peter Wood
    5 hours ago






  • 1





    @PeterWood python 3.7

    – Şevval Kahraman
    4 hours ago



















  • What version of Python are you using?

    – Peter Wood
    5 hours ago






  • 1





    @PeterWood python 3.7

    – Şevval Kahraman
    4 hours ago

















What version of Python are you using?

– Peter Wood
5 hours ago





What version of Python are you using?

– Peter Wood
5 hours ago




1




1





@PeterWood python 3.7

– Şevval Kahraman
4 hours ago





@PeterWood python 3.7

– Şevval Kahraman
4 hours ago












7 Answers
7






active

oldest

votes


















10














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


























  • 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
    5 hours ago






  • 1





    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
    4 hours ago













  • @ruohola I think using fsum is probably best for Python 2.

    – Peter Wood
    3 hours ago



















1














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

































    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


























    • first one gives this error : 'int' object is not callable

      – Şevval Kahraman
      5 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
      1 hour ago



















    1














    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


























    • it gives this error : 'int' object is not callable

      – Şevval Kahraman
      5 hours ago











    • @ŞevvalKahraman it gives no errors for me with your example array, you probably have a typo somewhere.

      – ruohola
      4 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
      4 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
      4 hours ago













    • As it's python 3, just use statistics.mean.

      – Peter Wood
      1 hour ago



















    1














    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

































      0














      You could use map:



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






      share|improve this answer
























      • works, thanks a lot

        – Şevval Kahraman
        5 hours ago



















      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


























      • Fixed it, Thank you for the suggestion @PeterWood

        – Devesh Kumar Singh
        5 hours ago












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      7 Answers
      7






      active

      oldest

      votes








      7 Answers
      7






      active

      oldest

      votes









      active

      oldest

      votes






      active

      oldest

      votes









      10














      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


























      • 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
        5 hours ago






      • 1





        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
        4 hours ago













      • @ruohola I think using fsum is probably best for Python 2.

        – Peter Wood
        3 hours ago
















      10














      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


























      • 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
        5 hours ago






      • 1





        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
        4 hours ago













      • @ruohola I think using fsum is probably best for Python 2.

        – Peter Wood
        3 hours ago














      10












      10








      10







      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















      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














      share|improve this answer



      share|improve this answer








      edited 4 hours ago

























      answered 5 hours ago









      Peter WoodPeter Wood

      16.8k33877




      16.8k33877













      • 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
        5 hours ago






      • 1





        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
        4 hours ago













      • @ruohola I think using fsum is probably best for Python 2.

        – Peter Wood
        3 hours ago



















      • 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
        5 hours ago






      • 1





        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
        4 hours ago













      • @ruohola I think using fsum is probably best for Python 2.

        – Peter Wood
        3 hours ago

















      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
      5 hours ago





      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
      5 hours ago




      1




      1





      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
      4 hours ago







      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
      4 hours ago















      @ruohola I think using fsum is probably best for Python 2.

      – Peter Wood
      3 hours ago





      @ruohola I think using fsum is probably best for Python 2.

      – Peter Wood
      3 hours ago













      1














      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






























        1














        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




























          1












          1








          1







          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















          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














          share|improve this answer



          share|improve this answer








          edited 5 hours ago

























          answered 5 hours ago









          gmdsgmds

          8,085932




          8,085932























              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


























              • first one gives this error : 'int' object is not callable

                – Şevval Kahraman
                5 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
                1 hour ago
















              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


























              • first one gives this error : 'int' object is not callable

                – Şevval Kahraman
                5 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
                1 hour ago














              1












              1








              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















              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














              share|improve this answer



              share|improve this answer








              edited 5 hours ago

























              answered 5 hours ago









              minjiminji

              167110




              167110













              • first one gives this error : 'int' object is not callable

                – Şevval Kahraman
                5 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
                1 hour ago



















              • first one gives this error : 'int' object is not callable

                – Şevval Kahraman
                5 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
                1 hour ago

















              first one gives this error : 'int' object is not callable

              – Şevval Kahraman
              5 hours ago





              first one gives this error : 'int' object is not callable

              – Şevval Kahraman
              5 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
              1 hour 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
              1 hour ago











              1














              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


























              • it gives this error : 'int' object is not callable

                – Şevval Kahraman
                5 hours ago











              • @ŞevvalKahraman it gives no errors for me with your example array, you probably have a typo somewhere.

                – ruohola
                4 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
                4 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
                4 hours ago













              • As it's python 3, just use statistics.mean.

                – Peter Wood
                1 hour ago
















              1














              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


























              • it gives this error : 'int' object is not callable

                – Şevval Kahraman
                5 hours ago











              • @ŞevvalKahraman it gives no errors for me with your example array, you probably have a typo somewhere.

                – ruohola
                4 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
                4 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
                4 hours ago













              • As it's python 3, just use statistics.mean.

                – Peter Wood
                1 hour ago














              1












              1








              1







              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















              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














              share|improve this answer



              share|improve this answer








              edited 3 hours ago

























              answered 5 hours ago









              ruoholaruohola

              1,902420




              1,902420













              • it gives this error : 'int' object is not callable

                – Şevval Kahraman
                5 hours ago











              • @ŞevvalKahraman it gives no errors for me with your example array, you probably have a typo somewhere.

                – ruohola
                4 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
                4 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
                4 hours ago













              • As it's python 3, just use statistics.mean.

                – Peter Wood
                1 hour ago



















              • it gives this error : 'int' object is not callable

                – Şevval Kahraman
                5 hours ago











              • @ŞevvalKahraman it gives no errors for me with your example array, you probably have a typo somewhere.

                – ruohola
                4 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
                4 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
                4 hours ago













              • As it's python 3, just use statistics.mean.

                – Peter Wood
                1 hour ago

















              it gives this error : 'int' object is not callable

              – Şevval Kahraman
              5 hours ago





              it gives this error : 'int' object is not callable

              – Şevval Kahraman
              5 hours ago













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

              – ruohola
              4 hours ago







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

              – ruohola
              4 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
              4 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
              4 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
              4 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
              4 hours ago















              As it's python 3, just use statistics.mean.

              – Peter Wood
              1 hour ago





              As it's python 3, just use statistics.mean.

              – Peter Wood
              1 hour ago











              1














              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






























                1














                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




























                  1












                  1








                  1







                  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















                  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














                  share|improve this answer



                  share|improve this answer








                  edited 2 hours ago

























                  answered 3 hours ago









                  GraipherGraipher

                  4,6891634




                  4,6891634























                      0














                      You could use map:



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






                      share|improve this answer
























                      • works, thanks a lot

                        – Şevval Kahraman
                        5 hours ago
















                      0














                      You could use map:



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






                      share|improve this answer
























                      • works, thanks a lot

                        – Şevval Kahraman
                        5 hours ago














                      0












                      0








                      0







                      You could use map:



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






                      share|improve this answer













                      You could use map:



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







                      share|improve this answer












                      share|improve this answer



                      share|improve this answer










                      answered 5 hours ago









                      pdpinopdpino

                      1647




                      1647













                      • works, thanks a lot

                        – Şevval Kahraman
                        5 hours ago



















                      • works, thanks a lot

                        – Şevval Kahraman
                        5 hours ago

















                      works, thanks a lot

                      – Şevval Kahraman
                      5 hours ago





                      works, thanks a lot

                      – Şevval Kahraman
                      5 hours ago











                      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


























                      • Fixed it, Thank you for the suggestion @PeterWood

                        – Devesh Kumar Singh
                        5 hours ago
















                      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


























                      • Fixed it, Thank you for the suggestion @PeterWood

                        – Devesh Kumar Singh
                        5 hours ago














                      0












                      0








                      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















                      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














                      share|improve this answer



                      share|improve this answer








                      edited 5 hours ago

























                      answered 5 hours ago









                      Devesh Kumar SinghDevesh Kumar Singh

                      3,4951425




                      3,4951425













                      • Fixed it, Thank you for the suggestion @PeterWood

                        – Devesh Kumar Singh
                        5 hours ago



















                      • Fixed it, Thank you for the suggestion @PeterWood

                        – Devesh Kumar Singh
                        5 hours ago

















                      Fixed it, Thank you for the suggestion @PeterWood

                      – Devesh Kumar Singh
                      5 hours ago





                      Fixed it, Thank you for the suggestion @PeterWood

                      – Devesh Kumar Singh
                      5 hours ago


















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