using counter with nested dictionaries in python

Question

i have a list of dicts in python like this:

[
  {
    "25-34": {
      "Clicks": 10
    },
    "45-54": {
      "Clicks": 2
    },

  },
  {
    "25-34": {
      "Clicks": 20
    },
    "45-54": {
      "Clicks": 10
    },

  }   
]

how can i get the sum of keys in each dict of list such that i have:

{
    "25-34": {
        "Clicks": 30
    },
    "45-54": {
        "Clicks": 12
    },

}

I tried using Counter() but it works easily when the dicts inside list are flat but with the nested dicts like above it gives this error:

    /usr/lib/python2.7/collections.pyc in update(self, iterable, **kwds)
        524                     self_get = self.get
        525                     for elem, count in iterable.iteritems():
    --> 526                         self[elem] = self_get(elem, 0) + count
        527                 else:
        528                     super(Counter, self).update(iterable) # fast path when counter is empty

TypeError: unsupported operand type(s) for +: 'dict' and 'dict'

How can i achieve the summation as i described above.

NOTE: i have added clicks just for sample. nested dicts can have any no of keys, another example to make it more clear:

[
  {
    "25-34": {
      "Clicks": 10,
      "Visits": 1
    },
    "45-54": {
      "Clicks": 2,
      "Visits": 2
    },

  },
  {
    "25-34": {
      "Clicks": 20,
      "Visits": 3
    },
    "45-54": {
      "Clicks": 10,
      "Visits": 4
    },

  }   
]

output:

{
    "25-34": {
      "Clicks": 30,
      "Visits": 4
    },
    "45-54": {
      "Clicks": 12,
      "Visits": 6
    },

  }

user_10391013 · Answer

I did like this:

with gzip.open("data/small_fasta.fa.gz", "rt") as handle:
    aac_count = defaultdict(Counter)
    for record in SeqIO.parse(handle, "fasta"):
        aac_count[record.id].update(record.seq)

I used biopython for open the fasta file (https://pt.wikipedia.org/wiki/Formato_FASTA) that are the type of file I use a lot.

It has a header('>proteinx' and in the next line a sequence (string of dna or proteins). And biopython is one easy way to deal with fasta files.

Then I used defaultdic and Counter for collections. Record.id is the header and is the key and I update the counter with the sequence for count the number of given character inside the strings.

The output is somenthing like this in my case:

defaultdict(collections.Counter,
            {'UniRef100_Q6GZX4': Counter({'M': 6,
                      'A': 13,
                      'F': 8,
                      'S': 13,
                      'E': 15,
                      'D': 17,
                      'V': 21,
                      'L': 25,
                      'K': 29,
                      'Y': 14,
                      'R': 15,
                      'P': 11,
                      'N': 8,
                      'W': 4,
                      'Q': 9,
                      'C': 4,
                      'G': 15,
                      'I': 12,
                      'H': 9,
                      'T': 8}),
             'UniRef100_Q6GZX3': Counter({'M': 7,
                      'S': 22,
                      'I': 10,
                      'G': 23,
                      'A': 26,
                      'T': 26,
                      'R': 16,
                      'L': 14,
                      'Q': 13,
                      'N': 9,
                      'D': 24,
                      'K': 17,
                      'Y': 11,
                      'P': 37,
                      'C': 18,
                      'F': 9,
                      'W': 6,
                      'E': 6,
                      'V': 23,
                      'H': 3}),...}

using counter with nested dictionaries in python

5 Answers