Python how to add sums of multiple lists

Question

The following is a list of lists. How do I add the sums of just "Total Black" and Total Color" into one list keeping just "Account ID" and "Account Name" the same?

[[{'Total Black': 3, 'Total Color': 2, 'Account ID': '2222', 'Account Name': 'Moe'}, 
  {'Total Black': 5, 'Total Color': 4, 'Account ID': '3333', 'Account Name': 'Larry'}, 
  {'Total Black': 9, 'Total Color': 6, 'Account ID': '4444', 'Account Name': 'Curly'}], 
 [{'Total Black': 8, 'Total Color': 4, 'Account ID': '2222', 'Account Name': 'Moe'}, 
  {'Total Black': 2, 'Total Color': 7, 'Account ID': '3333', 'Account Name': 'Larry'}, 
  {'Total Black': 11, 'Total Color': 9, 'Account ID': '4444', 'Account Name': 'Curly'}]]

So the result would be:

[{'Total Black': 11, 'Total Color': 6, 'Account ID': '2222', 'Account Name': 
'Moe'}, {'Total Black': 7, 'Total Color': 11, 'Account ID': '3333', 'Account 
Name': 'Larry'}, {'Total Black': 20, 'Total Color': 15, 'Account ID': 4444, 
'Account Name': 'Curly'}]

Answer 1

Setup

thing = [
    [{'Total Black': 3, 'Total Color': 2, 'Account ID': '2222', 'Account Name': 'Moe'}, 
     {'Total Black': 5, 'Total Color': 4, 'Account ID': '3333', 'Account Name': 'Larry'}, 
     {'Total Black': 9, 'Total Color': 6, 'Account ID': '4444', 'Account Name': 'Curly'}], 
    [{'Total Black': 8, 'Total Color': 4, 'Account ID': '2222', 'Account Name': 'Moe'}, 
     {'Total Black': 2, 'Total Color': 7, 'Account ID': '3333', 'Account Name': 'Larry'}, 
     {'Total Black': 11, 'Total Color': 9, 'Account ID': '4444', 'Account Name': 'Curly'}]
]

---

Very similar to ScottBoston

pd.DataFrame(sum(thing, [])).groupby(
    ['Account ID', 'Account Name'], as_index=False
).sum().to_dict('r')

---

merge_with

from itertools import chain
from toolz.dicttoolz import merge_with
from collections import defaultdict

idkey = ('Account ID', 'Account Name')

x = defaultdict(list)
for d in map(dict, chain(*thing)):
  x[(*map(d.pop, idkey),)].append(d)

[{**dict(zip(idkey, key)), **merge_with(sum, *d)} for key, d in x.items()]

[{'Account ID': '2222',
  'Account Name': 'Moe',
  'Total Black': 11,
  'Total Color': 6},
 {'Account ID': '3333',
  'Account Name': 'Larry',
  'Total Black': 7,
  'Total Color': 11},
 {'Account ID': '4444',
  'Account Name': 'Curly',
  'Total Black': 20,
  'Total Color': 15}]

Answer 2

Let's use pandas.

#From @C14L setup:

li = [
    [
        {'Total Black': 3, 'Total Color': 2, 'Account ID': '2222', 'Account Name': 'Moe'},
        {'Total Black': 5, 'Total Color': 4, 'Account ID': '3333', 'Account Name': 'Larry'},
        {'Total Black': 9, 'Total Color': 6, 'Account ID': '4444', 'Account Name': 'Curly'}
    ],
    [
        {'Total Black': 8, 'Total Color': 4, 'Account ID': '2222', 'Account Name': 'Moe'},
        {'Total Black': 2, 'Total Color': 7, 'Account ID': '3333', 'Account Name': 'Larry'},
        {'Total Black': 11, 'Total Color': 9, 'Account ID': '4444', 'Account Name': 'Curly'}
    ]
]

pd.concat([pd.DataFrame(li[i]) for i in range(len(li))])\
  .groupby(['Account ID','Account Name'])\
  .sum()\
  .reset_index()\
  .to_dict(orient='records')

Output:

[{'Account ID': '2222',
  'Account Name': 'Moe',
  'Total Black': 11,
  'Total Color': 6},
 {'Account ID': '3333',
  'Account Name': 'Larry',
  'Total Black': 7,
  'Total Color': 11},
 {'Account ID': '4444',
  'Account Name': 'Curly',
  'Total Black': 20,
  'Total Color': 15}]

Details:

First we use list comprehension and the pandas dataframe constructor to build dataframes for each element of your original list of list with dictionaries.

Next, use pd.concat to put these two, in this case dataframes together into one combined dataframe.

Use groupby with sum to aggregate values of Total Color and Total Black.

Lastly, reset index and to_dict to output combined dataframe as a dictionary.

Answer 3

li = [
    [
        {'Total Black': 3, 'Total Color': 2, 'Account ID': '2222', 'Account Name': 'Moe'},
        {'Total Black': 5, 'Total Color': 4, 'Account ID': '3333', 'Account Name': 'Larry'},
        {'Total Black': 9, 'Total Color': 6, 'Account ID': '4444', 'Account Name': 'Curly'}
    ],
    [
        {'Total Black': 8, 'Total Color': 4, 'Account ID': '2222', 'Account Name': 'Moe'},
        {'Total Black': 2, 'Total Color': 7, 'Account ID': '3333', 'Account Name': 'Larry'},
        {'Total Black': 11, 'Total Color': 9, 'Account ID': '4444', 'Account Name': 'Curly'}
    ]
]

result = [
    {
        'sum': x['Total Black'] + x['Total Color'],
        'Account ID': x['Account ID'],
        'Account Name': x['Account Name']
    } for x in li[0]
]

Gives as result for the first sub-list

[
    {'sum': 5, 'Account ID': '2222', 'Account Name': 'Moe'},
    {'sum': 9, 'Account ID': '3333', 'Account Name': 'Larry'},
    {'sum': 15, 'Account ID': '4444', 'Account Name': 'Curly'},
]

Is that what you were looking for?

Now you just need to iterate through the outer list to repeat this for each contained list.

Answer 4

Without Pandas Solution:

from itertools import groupby
from operator import itemgetter

orders_list = [[{'Total Black': 3, 'Total Color': 2, 'Account ID': '2222', 'Account Name': 'Moe'}, 
  {'Total Black': 5, 'Total Color': 4, 'Account ID': '3333', 'Account Name': 'Larry'}, 
  {'Total Black': 9, 'Total Color': 6, 'Account ID': '4444', 'Account Name': 'Curly'}], 
 [{'Total Black': 8, 'Total Color': 4, 'Account ID': '2222', 'Account Name': 'Moe'}, 
  {'Total Black': 2, 'Total Color': 7, 'Account ID': '3333', 'Account Name': 'Larry'}, 
  {'Total Black': 11, 'Total Color': 9, 'Account ID': '4444', 'Account Name': 'Curly'}]]


result_list = []

flattened_list = [item for sublist in orders_list for item in sublist]
grouper = itemgetter("Account ID", "Account Name")

for key, grp in groupby(sorted(flattened_list, key = grouper), grouper):
    temp_dict = dict(zip(["Account ID", "Account Name"], key))
    total_black_count = 0
    total_colors_count = 0
    for element in grp:
          total_black_count += element['Total Black']
          total_colors_count += element['Total Color']

    temp_dict["Total Color"] = total_colors_count
    temp_dict["Total Black"] = total_black_count
    result_list.append(temp_dict)

for dictionary in result_list:
    for key, values in dictionary.items():
        print(f"{key}: {values}")

DEMO FIDDLE