Как найти сумму элементов столбца питон

How do I add up all of the values of a column in a python array? Ideally I want to do this without importing any additional libraries.

input_val = [[1, 2, 3, 4, 5],
             [1, 2, 3, 4, 5],
             [1, 2, 3, 4, 5]]

output_val = [3, 6, 9, 12, 15]

I know I this can be done in a nested for loop, wondering if there was a better way (like a list comprehension)?

Stephen Rauch's user avatar

Stephen Rauch

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asked Apr 17, 2017 at 21:04

Alexander's user avatar

0

zip and sum can get that done:

Code:

[sum(x) for x in zip(*input_val)]

zip takes the contents of the input list and transposes them so that each element of the contained lists is produced at the same time. This allows the sum to see the first elements of each contained list, then next iteration will get the second element of each list, etc…

Test Code:

input_val = [[1, 2, 3, 4, 5],
             [1, 2, 3, 4, 5],
             [1, 2, 3, 4, 5]]

print([sum(x) for x in zip(*input_val)])

Results:

[3, 6, 9, 12, 15]

answered Apr 17, 2017 at 21:08

Stephen Rauch's user avatar

Stephen RauchStephen Rauch

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0

In case you decide to use any library, numpy easily does this:

np.sum(input_val,axis=0)

answered Apr 17, 2017 at 21:09

JavNoor's user avatar

JavNoorJavNoor

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You may also use sum with zip within the map function:

# In Python 3.x 
>>> list(map(sum, zip(*input_val)))
[3, 6, 9, 12, 15]
# explicitly type-cast it to list as map returns generator expression

# In Python 2.x, explicit type-casting to list is not needed as `map` returns list
>>> map(sum, zip(*input_val))
[3, 6, 9, 12, 15]

answered Apr 17, 2017 at 21:10

Moinuddin Quadri's user avatar

Moinuddin QuadriMoinuddin Quadri

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Try this:

input_val = [[1, 2, 3, 4, 5],
         [1, 2, 3, 4, 5],
         [1, 2, 3, 4, 5]]

output_val = [sum([i[b] for i in input_val]) for b in range(len(input_val[0]))]

print output_val

answered Apr 17, 2017 at 21:12

Ajax1234's user avatar

Ajax1234Ajax1234

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Please construct your array using the NumPy library:

import numpy as np

create the array using the array( ) function and save it in a variable:

 arr = np.array(([1, 2, 3, 4, 5],[1, 2, 3, 4, 5],[1, 2, 3, 4, 5]))

apply sum( ) function to the array specifying it for the columns by setting the axis parameter to zero:

arr.sum(axis = 0)

answered Aug 1, 2020 at 22:15

Zhannie's user avatar

ZhannieZhannie

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This should work:

[sum(i) for i in zip(*input_val)]

answered Apr 17, 2017 at 21:09

Alex's user avatar

AlexAlex

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I guess you can use:

import numpy as np
new_list = sum(map(np.array, input_val))

answered Apr 17, 2017 at 21:11

Pedro Lobito's user avatar

Pedro LobitoPedro Lobito

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I think this is the most pythonic way of doing this

map(sum, [x for x in zip(*input_val)])

answered Apr 17, 2017 at 21:14

Asav Patel's user avatar

Asav PatelAsav Patel

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One-liner using list comprehensions: for each column (length of one row), make a list of all the entries in that column, and sum that list.

output_val = [sum([input_val[i][j] for i in range(len(input_val))]) 
                 for j in range(len(input_val[0]))]

answered Apr 17, 2017 at 21:10

Prune's user avatar

PrunePrune

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Try this code. This will make output_val end up as [3, 6, 9, 12, 15] given your input_val:

input_val = [[1, 2, 3, 4, 5],
             [1, 2, 3, 4, 5],
             [1, 2, 3, 4, 5]]

vals_length = len(input_val[0])
output_val = [0] * vals_length # init empty output array with 0's
for i in range(vals_length): # iterate for each index in the inputs
    for vals in input_val:
        output_val[i] += vals[i] # add to the same index

print(output_val) # [3, 6, 9, 12, 15]

Al Sweigart's user avatar

Al Sweigart

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answered Apr 17, 2017 at 21:11

LLL's user avatar

LLLLLL

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Using Numpy you can easily solve this issue in one line:

1: Input

input_val = [[1, 2, 3, 4, 5],
             [1, 2, 3, 4, 5],
             [1, 2, 3, 4, 5]]

2: Numpy does the math for you

np.sum(input_val,axis=0)

3: Then finally the results

array([ 3,  6,  9, 12, 15])

answered Nov 22, 2018 at 7:30

Tom Souza's user avatar

output_val=input_val.sum(axis=0)

this would make the code even simpler I guess

Stephen Rauch's user avatar

Stephen Rauch

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answered Jan 28, 2018 at 1:26

Rop Shan's user avatar

1

You can use the sum function instead of np.sum simply.

input_val = np.array([[1, 2, 3, 4, 5],
         [1, 2, 3, 4, 5],
         [1, 2, 3, 4, 5]])
sum(input_val)

output: array([ 3,  6,  9, 12, 15])

answered Jun 21, 2022 at 7:40

Nadir's user avatar

I can sum the items in column zero fine. But where do I change the code to sum column 2, or 3, or 4 in the matrix?
I’m easily stumped.

def main():
    matrix = []

    for i in range(2):
        s = input("Enter a 4-by-4 matrix row " + str(i) + ": ") 
        items = s.split() # Extracts items from the string
        list = [ eval(x) for x in items ] # Convert items to numbers   
        matrix.append(list)

    print("Sum of the elements in column 0 is", sumColumn(matrix))

def sumColumn(m):
    for column in range(len(m[0])):
        total = 0
        for row in range(len(m)):
            total += m[row][column]
        return total

main()

lvc's user avatar

lvc

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asked Apr 18, 2014 at 0:40

vonbraun's user avatar

numpy could do this for you quite easily:

def sumColumn(matrix):
    return numpy.sum(matrix, axis=1)  # axis=1 says "get the sum along the columns"

Of course, if you wanted do it by hand, here’s how I would fix your code:

def sumColumn(m):
    answer = []
    for column in range(len(m[0])):
        t = 0
        for row in m:
            t += row[column]
        answer.append(t)
    return answer

Still, there is a simpler way, using zip:

def sumColumn(m):
    return [sum(col) for col in zip(*m)]

answered Apr 18, 2014 at 0:49

inspectorG4dget's user avatar

inspectorG4dgetinspectorG4dget

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3

One-liner:

column_sums = [sum([row[i] for row in M]) for i in range(0,len(M[0]))]

also

row_sums = [sum(row) for row in M]

for any rectangular, non-empty matrix (list of lists) M. e.g.

>>> M = [[1,2,3],
>>>     [4,5,6],
>>>     [7,8,9]]
>>>
>>> [sum([row[i] for row in M]) for i in range(0,len(M[0]))]
[12, 15, 18] 
>>> [sum(row) for row in M]
[6, 15, 24]

answered Jan 30, 2015 at 17:55

ChrisW's user avatar

ChrisWChrisW

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1

Here is your code changed to return the sum of whatever column you specify:

def sumColumn(m, column):
    total = 0
    for row in range(len(m)):
        total += m[row][column]
    return total

column = 1
print("Sum of the elements in column", column, "is", sumColumn(matrix, column))

answered Apr 18, 2014 at 1:08

user3286261's user avatar

user3286261user3286261

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To get the sum of all columns in the matrix you can use the below python numpy code:

matrixname.sum(axis=0)

Karol Dowbecki's user avatar

answered Oct 30, 2018 at 10:43

Vaka Chiranjeevi's user avatar

1

import numpy as np
np.sum(M,axis=1)

where M is the matrix

Buddy's user avatar

Buddy

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answered Nov 27, 2018 at 22:47

Fernando's user avatar

This can be made easier if you represent the matrix as a flat array:

m = [
    1,2,3,4,
    10,11,12,13,
    100,101,102,103,
    1001,1002,1003,1004
]

def sum_column(m, n):
    return sum(m[i] for i in range(n, 4 * 4, 4))

answered Apr 18, 2014 at 0:50

michaelmeyer's user avatar

michaelmeyermichaelmeyer

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  • Редакция Кодкампа

17 авг. 2022 г.
читать 1 мин


Часто вас может заинтересовать вычисление суммы одного или нескольких столбцов в кадре данных pandas. К счастью, вы можете легко сделать это в pandas, используя функцию sum() .

В этом руководстве показано несколько примеров использования этой функции.

Пример 1: найти сумму одного столбца

Предположим, у нас есть следующие Pandas DataFrame:

import pandas as pd
import numpy as np

#create DataFrame
df = pd.DataFrame({'rating': [90, 85, 82, 88, 94, 90, 76, 75, 87, 86],
 'points': [25, 20, 14, 16, 27, 20, 12, 15, 14, 19],
 'assists': [5, 7, 7, 8, 5, 7, 6, 9, 9, 5],
 'rebounds': [np.nan, 8, 10, 6, 6, 9, 6, 10, 10, 7]})

#view DataFrame 
df

 rating points assists rebounds
0 90 25 5 NaN
1 85 20 7 8
2 82 14 7 10
3 88 16 8 6
4 94 27 5 6
5 90 20 7 9
6 76 12 6 6
7 75 15 9 10
8 87 14 9 10
9 86 19 5 7

Мы можем найти сумму столбца под названием «баллы», используя следующий синтаксис:

df['points']. sum ()

182

Функция sum() также будет исключать NA по умолчанию. Например, если мы найдем сумму столбца «рикошеты», первое значение «NaN» будет просто исключено из расчета:

df['rebounds']. sum ()

72.0

Пример 2. Найдите сумму нескольких столбцов

Мы можем найти сумму нескольких столбцов, используя следующий синтаксис:

#find sum of points and rebounds columns
df[['rebounds', 'points']]. sum ()

rebounds 72.0
points 182.0
dtype: float64

Пример 3: найти сумму всех столбцов

Мы также можем найти сумму всех столбцов, используя следующий синтаксис:

#find sum of all columns in DataFrame
df.sum ()

rating 853.0
points 182.0
assists 68.0
rebounds 72.0
dtype: float64

Для столбцов, которые не являются числовыми, функция sum() просто не будет вычислять сумму этих столбцов.

Вы можете найти полную документацию по функции sum() здесь .

In today’s recipe we’ll touch on the basics of adding numeric values in a pandas DataFrame.

We’ll cover the following cases:

  • Sum all rows of one or multiple columns
  • Sum by column name/label into a new column
  • Adding values by index
  • Dealing with nan values
  • Sum values that meet a certain condition

Creating the dataset

We’ll start by creating a simple dataset

# Python3
# import pandas into your Python environment.
import pandas as pd

# Now, let's create the dataframe 
budget = pd.DataFrame({"person": ["John", "Kim", "Bob"],
                        "quarter": [1, 1, 1] ,
                        "consumer_budg": [15000, 35000, 45000],
                         "enterprise_budg": [20000, 30000, 40000] })
budget.head()
person quarter consumer_budg enterprise_budg
0 John 1 15000 20000
1 Kim 1 35000 30000
2 Bob 1 45000 40000

How to sum a column? (or more)

For a single column we’ll simply use the Series Sum() method.

# one column
budget['consumer_budg'].sum()

95000

Also the DataFrame has a Sum() method, which we’ll use to add multiple columns:

#addingmultiple columns
cols = ['consumer_budg', 'enterprise_budg']
budget[cols].sum()

We’ll receive a Series objects with the results:

consumer_budg      95000
enterprise_budg    90000
dtype: int64

Sum row values into a new column

More interesting is the case that we want to compute the values by adding multiple column values in a specific row. See this simple example below

# using the column label names
budget['total_budget'] = budget['consumer_budg'] + budget['enterprise_budg']

We have created a new column as shown below:

person quarter consumer_budg enterprise_budg total_budget
0 John 1 15000 20000 35000
1 Kim 1 35000 30000 65000
2 Bob 1 45000 40000 85000

Note: We could have also used the loc method to subset by label.

Adding columns by index

We can also refer to the columns to sum by index, using the iloc method.

# by index
budget['total_budget'] = budget.iloc[:,2]+ budget.iloc[:,3]

Result will be similar as above

Sum with conditions

In this example, we would like to define a column named high_budget and populate it only if the total_budget is over the 80K threshold.

budget['high_budget'] = budget.query('consumer_budg + enterprise_budg > 80000')['total_budget']

Adding columns with null values

Here we might need a bit of pre-processing to get rid of the null values using fillna().

Let’s quickly create a sample dataset containing null values (see last row).

# with nan
import numpy as np
budget_nan = pd.DataFrame({"person": ["John", "Kim", "Bob", 'Court'],
                        "quarter": [1, 1, 1,1] ,
                        "consumer_budg": [15000, 35000, 45000, 50000],
                         "enterprise_budg": [20000, 30000, 40000, np.nan ] })
person quarter consumer_budg enterprise_budg high_budget
0 John 1 15000 20000.0 35000.0
1 Kim 1 35000 30000.0 65000.0
2 Bob 1 45000 40000.0 85000.0
3 Court 1 50000 NaN NaN

Now lets use the DataFrame fillna() method to mass override the null values with Zeros so that we can sum the column values.

budget_nan.fillna(0, inplace=True)
budget_nan['high_budget'] = budget_nan['consumer_budg'] + budget_nan['enterprise_budg']
budget_nan

Voi’la

person quarter consumer_budg enterprise_budg high_budget
0 John 1 15000 20000.0 35000.0
1 Kim 1 35000 30000.0 65000.0
2 Bob 1 45000 40000.0 85000.0
3 Court 1 50000 0.0 50000.0

Vik1002

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1

Сумма каждой строки и столбца

04.07.2019, 15:03. Показов 34152. Ответов 3

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Добрый день. Строки посчитаны.
Подскажите как можно посчитать сумму столбцов:

Python
1
2
3
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5
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9
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x=[[1,2,3],
   [4,5,6]]
y=[]
z=[]
for i in range (len(x)):
    stroki=0
    stowbtsy=0
    for j in range (len(x[0])):
        stroki+=x[i][j]#вывод суммы отдельной строки
    y.append(stroki)#с занесением в одномерный массив
print(y)



0



m0nte-cr1st0

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Записей в блоге: 1

04.07.2019, 17:09

2

Лучший ответ Сообщение было отмечено Vik1002 как решение

Решение

Python
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x=[[1,2,3],
   [4,5,6]]
y=[]
z=[]
for i in range (len(x)):
    stroki=0
    for j in range (len(x[0])):
        stroki+=x[i][j]#вывод суммы отдельной строки
    y.append(stroki)#с занесением в одномерный массив
 
for i in range (len(x[0])):
    stowbtsy=0
    for j in range (len(x)):
        stowbtsy+=x[j][i]#вывод суммы отдельного столбца
    z.append(stowbtsy)#с занесением в одномерный массив
 
print(y)
print(z)



3



Garry Galler

Эксперт Python

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04.07.2019, 19:14

3

Цитата
Сообщение от Vik1002
Посмотреть сообщение

подсчитать суммы столбцов:

Python
1
2
3
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>>> x=[[1,2,3],
   [4,5,6]]
>>> list(map(sum,zip(*x)))
 
[5, 7, 9]
>>>



4



Автоматизируй это!

Эксперт Python

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04.07.2019, 19:16

4

Garry Galler, блин, оригинально!



0



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