Summing day data values

I need help on my program with how to add up each day values. So far it looks like this

import csv



def convert(data):

    try:

        return int(data)

    except ValueError:

        return 0



with open('MonthData1.csv', 'r') as file1:

        read_file = csv.reader(file1, delimiter = ';')

        delheader = next(read_file)

        for line in read_file: 

            valuedata = max(0,sum([convert(i) for i in line[1:5]])) 

            print(line[0], valuedata)

At the moment it sums the 3 item values as it should:

1.5.2018 15:00 150

1.5.2018 20:00 95

2.5.2018 18:00 105

4.5.2018 17:00 78

4.5.2018 20:00 0

4.5.2018 20:00 9

But I want it to sum all the values of the same day, so it would be something like this:

1.5.2018 245

2.5.2018 105

4.5.2018 87

How could this be excecuted? I hope for help. Here is a pastebin from all the data used in this: https://pastebin.com/Tw4aYdPc

The base code is not mine originally, edited it a bit to match my needs.

asked Nov 20 at 21:08

Armeija

154

add a comment |

I need help on my program with how to add up each day values. So far it looks like this

import csv



def convert(data):

    try:

        return int(data)

    except ValueError:

        return 0



with open('MonthData1.csv', 'r') as file1:

        read_file = csv.reader(file1, delimiter = ';')

        delheader = next(read_file)

        for line in read_file: 

            valuedata = max(0,sum([convert(i) for i in line[1:5]])) 

            print(line[0], valuedata)

At the moment it sums the 3 item values as it should:

1.5.2018 15:00 150

1.5.2018 20:00 95

2.5.2018 18:00 105

4.5.2018 17:00 78

4.5.2018 20:00 0

4.5.2018 20:00 9

But I want it to sum all the values of the same day, so it would be something like this:

1.5.2018 245

2.5.2018 105

4.5.2018 87

asked Nov 20 at 21:08

Armeija

154

add a comment |

I need help on my program with how to add up each day values. So far it looks like this

import csv



def convert(data):

    try:

        return int(data)

    except ValueError:

        return 0



with open('MonthData1.csv', 'r') as file1:

        read_file = csv.reader(file1, delimiter = ';')

        delheader = next(read_file)

        for line in read_file: 

            valuedata = max(0,sum([convert(i) for i in line[1:5]])) 

            print(line[0], valuedata)

At the moment it sums the 3 item values as it should:

1.5.2018 15:00 150

1.5.2018 20:00 95

2.5.2018 18:00 105

4.5.2018 17:00 78

4.5.2018 20:00 0

4.5.2018 20:00 9

But I want it to sum all the values of the same day, so it would be something like this:

1.5.2018 245

2.5.2018 105

4.5.2018 87

asked Nov 20 at 21:08

Armeija

154

I need help on my program with how to add up each day values. So far it looks like this

import csv



def convert(data):

    try:

        return int(data)

    except ValueError:

        return 0



with open('MonthData1.csv', 'r') as file1:

        read_file = csv.reader(file1, delimiter = ';')

        delheader = next(read_file)

        for line in read_file: 

            valuedata = max(0,sum([convert(i) for i in line[1:5]])) 

            print(line[0], valuedata)

At the moment it sums the 3 item values as it should:

1.5.2018 15:00 150

1.5.2018 20:00 95

2.5.2018 18:00 105

4.5.2018 17:00 78

4.5.2018 20:00 0

4.5.2018 20:00 9

But I want it to sum all the values of the same day, so it would be something like this:

1.5.2018 245

2.5.2018 105

4.5.2018 87

python python-3.x list csv sum

asked Nov 20 at 21:08

Armeija

154

asked Nov 20 at 21:08

Armeija

154

asked Nov 20 at 21:08

Armeija

154

asked Nov 20 at 21:08

Armeija

154

asked Nov 20 at 21:08

Armeija

154

add a comment |

1 Answer
1

active

oldest

votes

I used a defaultdict to sum your valuedatas and ordered it to print:

import csv

from collections import defaultdict, OrderedDict





def convert(data):

    try:

        return int(data)

    except ValueError:

        return 0





with open('MonthData1.csv', 'r') as file1:

        read_file = csv.reader(file1, delimiter=';')

        delheader = next(read_file)

        data = defaultdict(int)

        for line in read_file:

            valuedata = max(0, sum([convert(i) for i in line[1:5]]))

            data[line[0].split()[0]] += valuedata



        for key in OrderedDict(sorted(data.items())):

            print('{} {}'.format(key, data[key]))

EDIT:
To calculate cumulative values:

import csv

from collections import defaultdict, OrderedDict





def convert(data):

    try:

        return int(data)

    except ValueError:

        return 0





with open('MonthData1.csv', 'r') as file1:

        read_file = csv.reader(file1, delimiter=';')

        delheader = next(read_file)

        data = defaultdict(int)

        for line in read_file:

            valuedata = max(0, sum([convert(i) for i in line[1:5]]))

            data[line[0].split()[0]] += valuedata



        previous_values = 

        for key, value in OrderedDict(sorted(data.items())).items():

            print('{} {}'.format(key, value + sum(previous_values)))

            previous_values.append(value)

Results:

1.5.2018 245

2.5.2018 350

4.5.2018 433

edited Nov 20 at 21:57

answered Nov 20 at 21:26

Aurora Wang

682216

Wow thank you very much. Is it possible to add that after it has printed sums of the days, it calculates the cumulative values? It would pretty much be like: 1.5.2018 245, 2.5.2018 350, 4.5.2018 437 This would be helpful for me to analyze the values
– Armeija
Nov 20 at 21:38

Do you mean to maintain the prints you already did?
– Aurora Wang
Nov 20 at 21:42

After each day it maintains the value and sums the next values to the current one
– Armeija
Nov 20 at 21:46

Check if my edit does what you want.
– Aurora Wang
Nov 20 at 21:57

Can you print first the normal sum, and after it has printed the normal values it would print the cumulative values, something like this:1.5.2018 245 2.5.2018 105 4.5.2018 87 Then straight after it prints these 1.5.2018 245, 2.5.2018 350, 4.5.2018 437
– Armeija
Nov 20 at 22:03

|
show 3 more comments

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1 Answer
1

active

oldest

votes

1 Answer
1

active

oldest

votes

I used a defaultdict to sum your valuedatas and ordered it to print:

import csv

from collections import defaultdict, OrderedDict





def convert(data):

    try:

        return int(data)

    except ValueError:

        return 0





with open('MonthData1.csv', 'r') as file1:

        read_file = csv.reader(file1, delimiter=';')

        delheader = next(read_file)

        data = defaultdict(int)

        for line in read_file:

            valuedata = max(0, sum([convert(i) for i in line[1:5]]))

            data[line[0].split()[0]] += valuedata



        for key in OrderedDict(sorted(data.items())):

            print('{} {}'.format(key, data[key]))

EDIT:
To calculate cumulative values:

import csv

from collections import defaultdict, OrderedDict





def convert(data):

    try:

        return int(data)

    except ValueError:

        return 0





with open('MonthData1.csv', 'r') as file1:

        read_file = csv.reader(file1, delimiter=';')

        delheader = next(read_file)

        data = defaultdict(int)

        for line in read_file:

            valuedata = max(0, sum([convert(i) for i in line[1:5]]))

            data[line[0].split()[0]] += valuedata



        previous_values = 

        for key, value in OrderedDict(sorted(data.items())).items():

            print('{} {}'.format(key, value + sum(previous_values)))

            previous_values.append(value)

Results:

1.5.2018 245

2.5.2018 350

4.5.2018 433

edited Nov 20 at 21:57

answered Nov 20 at 21:26

Aurora Wang

682216

Wow thank you very much. Is it possible to add that after it has printed sums of the days, it calculates the cumulative values? It would pretty much be like: 1.5.2018 245, 2.5.2018 350, 4.5.2018 437 This would be helpful for me to analyze the values
– Armeija
Nov 20 at 21:38

Do you mean to maintain the prints you already did?
– Aurora Wang
Nov 20 at 21:42

After each day it maintains the value and sums the next values to the current one
– Armeija
Nov 20 at 21:46

Check if my edit does what you want.
– Aurora Wang
Nov 20 at 21:57

Can you print first the normal sum, and after it has printed the normal values it would print the cumulative values, something like this:1.5.2018 245 2.5.2018 105 4.5.2018 87 Then straight after it prints these 1.5.2018 245, 2.5.2018 350, 4.5.2018 437
– Armeija
Nov 20 at 22:03

|
show 3 more comments

I used a defaultdict to sum your valuedatas and ordered it to print:

import csv

from collections import defaultdict, OrderedDict





def convert(data):

    try:

        return int(data)

    except ValueError:

        return 0





with open('MonthData1.csv', 'r') as file1:

        read_file = csv.reader(file1, delimiter=';')

        delheader = next(read_file)

        data = defaultdict(int)

        for line in read_file:

            valuedata = max(0, sum([convert(i) for i in line[1:5]]))

            data[line[0].split()[0]] += valuedata



        for key in OrderedDict(sorted(data.items())):

            print('{} {}'.format(key, data[key]))

EDIT:
To calculate cumulative values:

import csv

from collections import defaultdict, OrderedDict





def convert(data):

    try:

        return int(data)

    except ValueError:

        return 0





with open('MonthData1.csv', 'r') as file1:

        read_file = csv.reader(file1, delimiter=';')

        delheader = next(read_file)

        data = defaultdict(int)

        for line in read_file:

            valuedata = max(0, sum([convert(i) for i in line[1:5]]))

            data[line[0].split()[0]] += valuedata



        previous_values = 

        for key, value in OrderedDict(sorted(data.items())).items():

            print('{} {}'.format(key, value + sum(previous_values)))

            previous_values.append(value)

Results:

1.5.2018 245

2.5.2018 350

4.5.2018 433

edited Nov 20 at 21:57

answered Nov 20 at 21:26

Aurora Wang

682216

Wow thank you very much. Is it possible to add that after it has printed sums of the days, it calculates the cumulative values? It would pretty much be like: 1.5.2018 245, 2.5.2018 350, 4.5.2018 437 This would be helpful for me to analyze the values
– Armeija
Nov 20 at 21:38

Do you mean to maintain the prints you already did?
– Aurora Wang
Nov 20 at 21:42

After each day it maintains the value and sums the next values to the current one
– Armeija
Nov 20 at 21:46

Check if my edit does what you want.
– Aurora Wang
Nov 20 at 21:57

Can you print first the normal sum, and after it has printed the normal values it would print the cumulative values, something like this:1.5.2018 245 2.5.2018 105 4.5.2018 87 Then straight after it prints these 1.5.2018 245, 2.5.2018 350, 4.5.2018 437
– Armeija
Nov 20 at 22:03

|
show 3 more comments

I used a defaultdict to sum your valuedatas and ordered it to print:

import csv

from collections import defaultdict, OrderedDict





def convert(data):

    try:

        return int(data)

    except ValueError:

        return 0





with open('MonthData1.csv', 'r') as file1:

        read_file = csv.reader(file1, delimiter=';')

        delheader = next(read_file)

        data = defaultdict(int)

        for line in read_file:

            valuedata = max(0, sum([convert(i) for i in line[1:5]]))

            data[line[0].split()[0]] += valuedata



        for key in OrderedDict(sorted(data.items())):

            print('{} {}'.format(key, data[key]))

EDIT:
To calculate cumulative values:

import csv

from collections import defaultdict, OrderedDict





def convert(data):

    try:

        return int(data)

    except ValueError:

        return 0





with open('MonthData1.csv', 'r') as file1:

        read_file = csv.reader(file1, delimiter=';')

        delheader = next(read_file)

        data = defaultdict(int)

        for line in read_file:

            valuedata = max(0, sum([convert(i) for i in line[1:5]]))

            data[line[0].split()[0]] += valuedata



        previous_values = 

        for key, value in OrderedDict(sorted(data.items())).items():

            print('{} {}'.format(key, value + sum(previous_values)))

            previous_values.append(value)

Results:

1.5.2018 245

2.5.2018 350

4.5.2018 433

edited Nov 20 at 21:57

answered Nov 20 at 21:26

Aurora Wang

682216

I used a defaultdict to sum your valuedatas and ordered it to print:

import csv

from collections import defaultdict, OrderedDict





def convert(data):

    try:

        return int(data)

    except ValueError:

        return 0





with open('MonthData1.csv', 'r') as file1:

        read_file = csv.reader(file1, delimiter=';')

        delheader = next(read_file)

        data = defaultdict(int)

        for line in read_file:

            valuedata = max(0, sum([convert(i) for i in line[1:5]]))

            data[line[0].split()[0]] += valuedata



        for key in OrderedDict(sorted(data.items())):

            print('{} {}'.format(key, data[key]))

EDIT:
To calculate cumulative values:

import csv

from collections import defaultdict, OrderedDict





def convert(data):

    try:

        return int(data)

    except ValueError:

        return 0





with open('MonthData1.csv', 'r') as file1:

        read_file = csv.reader(file1, delimiter=';')

        delheader = next(read_file)

        data = defaultdict(int)

        for line in read_file:

            valuedata = max(0, sum([convert(i) for i in line[1:5]]))

            data[line[0].split()[0]] += valuedata



        previous_values = 

        for key, value in OrderedDict(sorted(data.items())).items():

            print('{} {}'.format(key, value + sum(previous_values)))

            previous_values.append(value)

Results:

1.5.2018 245

2.5.2018 350

4.5.2018 433

edited Nov 20 at 21:57

answered Nov 20 at 21:26

Aurora Wang

682216

edited Nov 20 at 21:57

answered Nov 20 at 21:26

Aurora Wang

682216

answered Nov 20 at 21:26

Aurora Wang

682216

answered Nov 20 at 21:26

Aurora Wang

682216

Wow thank you very much. Is it possible to add that after it has printed sums of the days, it calculates the cumulative values? It would pretty much be like: 1.5.2018 245, 2.5.2018 350, 4.5.2018 437 This would be helpful for me to analyze the values
– Armeija
Nov 20 at 21:38

Do you mean to maintain the prints you already did?
– Aurora Wang
Nov 20 at 21:42

After each day it maintains the value and sums the next values to the current one
– Armeija
Nov 20 at 21:46

Check if my edit does what you want.
– Aurora Wang
Nov 20 at 21:57

Can you print first the normal sum, and after it has printed the normal values it would print the cumulative values, something like this:1.5.2018 245 2.5.2018 105 4.5.2018 87 Then straight after it prints these 1.5.2018 245, 2.5.2018 350, 4.5.2018 437
– Armeija
Nov 20 at 22:03

|
show 3 more comments

Wow thank you very much. Is it possible to add that after it has printed sums of the days, it calculates the cumulative values? It would pretty much be like: 1.5.2018 245, 2.5.2018 350, 4.5.2018 437 This would be helpful for me to analyze the values
– Armeija
Nov 20 at 21:38

Do you mean to maintain the prints you already did?
– Aurora Wang
Nov 20 at 21:42

After each day it maintains the value and sums the next values to the current one
– Armeija
Nov 20 at 21:46

Check if my edit does what you want.
– Aurora Wang
Nov 20 at 21:57

Can you print first the normal sum, and after it has printed the normal values it would print the cumulative values, something like this:1.5.2018 245 2.5.2018 105 4.5.2018 87 Then straight after it prints these 1.5.2018 245, 2.5.2018 350, 4.5.2018 437
– Armeija
Nov 20 at 22:03

Wow thank you very much. Is it possible to add that after it has printed sums of the days, it calculates the cumulative values? It would pretty much be like: 1.5.2018 245, 2.5.2018 350, 4.5.2018 437 This would be helpful for me to analyze the values
– Armeija
Nov 20 at 21:38

Do you mean to maintain the prints you already did?
– Aurora Wang
Nov 20 at 21:42

After each day it maintains the value and sums the next values to the current one
– Armeija
Nov 20 at 21:46

Check if my edit does what you want.
– Aurora Wang
Nov 20 at 21:57

Can you print first the normal sum, and after it has printed the normal values it would print the cumulative values, something like this:1.5.2018 245 2.5.2018 105 4.5.2018 87 Then straight after it prints these 1.5.2018 245, 2.5.2018 350, 4.5.2018 437
– Armeija
Nov 20 at 22:03

|
show 3 more comments

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