Sum Values Of Dynamically Created Dictionaries Using Counter From Collections

I have this df: import pandas as pd a = [1,1,1,2,2,3,3,3,3,4,4,5,5,5] b = ['pi','pi','k','J','pi','pi','k','k','J','pi','k','pi','k','pi'] bin0 = [0,0,0,1,0,0,1,0,0,0,1,1,0,0] bin1

Solution 1:

Isn't it this what you want to achieve:

df_test.groupby(['a', 'b']).sum().reset_index().groupby('a').sum()

    bin0    bin1    bin2
a           
1   0   3   0
2   1   1   0
3   1   2   1
4   1   0   1
5   1   1   1

Solution 2:

You're going a lot of crazy things here I think are probably unnecessary and I'd really advise against (eval, setattr), but to answer just your question about summing the values of two counters with shared keys:

from collections import Counter
cx = Counter(x)
cy = Counter(y)

totals = {k:cx.get(k,0) + cy.get(k,0) for k in (set(cx) | set(cy))}
print(totals)

You take the union of both dictionary keys, iterate over it, and use the Counter.get(key, default) method to get the value of the associated key and provide a fallback default if it doesn't exist.

This is a dictionary comprehension but you could also do:

for k in (set(cx) | set(cy)):
    total = cx.get(k,0) + cy.get(k,0)
    print(k, total)

For example, using data built with:

from random import choice
x = [choice("abcdefg") for _ in range(100)]
y = [choice("abcdefg") for _ in range(100)]
y.extend(["z"] * 3)

Solution 3:

Try to use update() method of dict https://www.tutorialspoint.com/python/dictionary_update.htm

count.update(other[elem])