How can I sum of groups of varying sizes of numbers presented as a list and find the highest sum

if anyone could help me out with this advent of code (Day 1 2022 - haven't got very far!): You have to add up all the numbers of each group of varying sizes (100,2000,3000 is group 1, 4000 is group 2), separated by a line break. You then have to add up each group and find the highest.

1000
2000
3000

4000

5000
6000

7000
8000
9000

10000

I've tried replacing each line break in the list with the group number, but still doesn't help, presume it needs to be turned into a dataframe but unsure with varying lengths of group how to do this, any help would be much appreciated!

No need for pandas.

x = '''1000 2000 3000
4000
5000 6000
7000 8000 9000
10000'''

group_sums = []
for line in x.split('\n'):
    current = [int(el) for el in line.split(' ')]
    group_sums.append(sum(current))
    
group_sums
Out[4]: [6000, 4000, 11000, 24000, 10000]

max(group_sums)
Out[5]: 24000

Having taken a look at the original problem question, the groups of numbers are separated by two newline characters. Since you would probably like to solve the problem yourself, I will just point you in the right direction. Consider using the .split(c) method, which decomposes a given string into a list of strings breaking it at all occurences of c. And you can typecast strings to integers by using int(str_here).

A simple solution in python for the sake of completeness:

groups = open("input.txt").read().split("\n\n")
groups = [group.split("\n") for group in groups]
groups = [[int(item) for item in group] for group in groups]
groups = [sum(group) for group in groups]
print(max(groups))

Of course this is not the fastest solution, and python itself is very slow, but I hope it is easy to understand. List comprehensions (expressions such as[thing for thing in group_of_things]) are a powerful tool in python.

Here is a sample solution:

input_data = '''1000 2000 3000
4000
5000 6000
7000 8000 9000
10000'''

groups = input_data.split('\n')  # Split input into groups based on line breaks

max_sum = 0
max_sum_line = -1

for i, group in enumerate(groups):
    numbers = group.split()  # Split group into individual numbers
    numbers = [int(num) for num in numbers]  # Convert numbers from string to integer
    group_sum = sum(numbers)  # Calculate the sum of each group
    if group_sum > max_sum:
        max_sum = group_sum
        max_sum_line = i + 1  # Line numbers start from 1, not 0

print("Maximum sum:", max_sum)
print("Line number with the biggest sum:", max_sum_line)

output is:

Maximum sum: 24000
Line number with the biggest sum: 4

I'm not very strong, there are probably improvements to be made, but here's what I did:

data = """1000 2000 3000
4000
5000 6000
7000 8000 9000
10000"""

groups = data.split("\n")

groups_sums = []

for i in groups:
    fragment = i.split(" ")
    somme = 0
    for i in fragment:
        somme += int(i)
    groups_sums.append(somme)

max_sum = max(groups_sums)
max_sum_index = groups_sums.index(max_sum)

print("Group with the max sum, number :",max_sum_index + 1,"value :",max_sum,"data :", groups[max_sum_index])

Since you have a [tag:dataframe] tag and assuming the input is a txt-csv.. file, you can use :

tmp = pd.read_csv("file.txt", header=None, skip_blank_lines=False)[0]
​
grp = (tmp.shift().isnull() & tmp.notnull()).cumsum()
​
grp_sums = tmp.groupby(grp).sum().to_frame("values").rename_axis("group")
​
highest = grp_sums.loc[grp_sums.idxmax()] # `.iat[0, 0]` to return a scalar

​
Output :

print(grp_sums)
​
        values
group         
1      6000.00
2      4000.00
3     11000.00
4     24000.00
5     10000.00

print(highest)

        values
group         
4     24000.00