Flatten list of dictionaries to a tuple

gistfile1.json

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  {
   "cells": [
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Processing elasticsearch buckets"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "When using the 'terms' aggregation of Elasticsearch, the returned value is a list of buckets. Something like:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "x = [\n",
      "    {\n",
      "        \"key\": \"John\",\n",
      "        \"doc_count\": 174736\n",
      "    },\n",
      "    {\n",
      "        \"key\": \"Martin\",\n",
      "        \"doc_count\": 37789\n",
      "    },\n",
      "    {\n",
      "        \"key\": \"Lev\",\n",
      "        \"doc_count\": 10261\n",
      "    },\n",
      "    {\n",
      "        \"key\": \"Joel\",\n",
      "        \"doc_count\": 8638\n",
      "    },\n",
      "    {\n",
      "        \"key\": \"Smith\",\n",
      "        \"doc_count\": 6672\n",
      "    }\n",
      "]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This output might be hard to work with. It would be nice to convert it into something more friendly."
     ]
    },
    {
     "cell_type": "heading",
     "level": 6,
     "metadata": {},
     "source": [
      "Using <code>tuple</code>s (you can replace tuples with <code>list</code>s):"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "tuple(element for tup in tuple((dic['key'],dic['doc_count']) for dic in x) for element in tup)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 2,
       "text": [
        "('John', 174736, 'Martin', 37789, 'Lev', 10261, 'Joel', 8638, 'Smith', 6672)"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "tuple((dic['key'], dic['doc_count']) for dic in x)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 3,
       "text": [
        "(('John', 174736),\n",
        " ('Martin', 37789),\n",
        " ('Lev', 10261),\n",
        " ('Joel', 8638),\n",
        " ('Smith', 6672))"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "heading",
     "level": 6,
     "metadata": {},
     "source": [
      "Using dictionaries"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "{dic['key']: dic['doc_count'] for dic in x}"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 4,
       "text": [
        "{'Joel': 8638, 'John': 174736, 'Lev': 10261, 'Martin': 37789, 'Smith': 6672}"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Note that once switching to a dictionary the order may be broken! This can be tackled using Pandas; see next."
     ]
    },
    {
     "cell_type": "heading",
     "level": 6,
     "metadata": {},
     "source": [
      "Sorting using Pandas"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pandas as pd"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pd.Series(\n",
      "    {dic['key']: dic['doc_count'] for dic in x}\n",
      ").order(ascending=False)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "John      174736\n",
        "Martin     37789\n",
        "Lev        10261\n",
        "Joel        8638\n",
        "Smith       6672\n",
        "dtype: int64"
       ]
      }
     ],
     "prompt_number": 6
    }
   ],
   "metadata": {}
  }
 ]
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