MultiIndex.ipynb

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  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import itertools\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
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    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>evt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11</td>\n",
       "      <td>101</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12</td>\n",
       "      <td>102</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>13</td>\n",
       "      <td>103</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>14</td>\n",
       "      <td>104</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>15</td>\n",
       "      <td>105</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>16</td>\n",
       "      <td>106</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>17</td>\n",
       "      <td>107</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>18</td>\n",
       "      <td>108</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>19</td>\n",
       "      <td>109</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    a    b  evt\n",
       "0  10  100    1\n",
       "1  11  101    1\n",
       "2  12  102    1\n",
       "3  13  103    1\n",
       "4  14  104    1\n",
       "5  15  105    2\n",
       "6  16  106    2\n",
       "7  17  107    2\n",
       "8  18  108    2\n",
       "9  19  109    2"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(dict(a= range(10, 20), b=range(100, 110), evt=[1]*5 + [2]*5))\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def compute_num(track1, track2):\n",
    "    return track1.a*track2.a + track1.b*track2.b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "series = {}\n",
    "for evt, group in grouped:\n",
    "    index = pd.MultiIndex.from_product([group.index, group.index], names=['track1', 'track2'])\n",
    "    evt_nums = []\n",
    "    for idx1, idx2 in index:\n",
    "        evt_nums.append(compute_num(df.loc[idx1], df.loc[idx2]))\n",
    "    series[evt] = pd.Series(evt_nums, index=index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1: track1  track2\n",
       " 0       0         10100\n",
       "         1         10210\n",
       "         2         10320\n",
       "         3         10430\n",
       "         4         10540\n",
       " 1       0         10210\n",
       "         1         10322\n",
       "         2         10434\n",
       "         3         10546\n",
       "         4         10658\n",
       " 2       0         10320\n",
       "         1         10434\n",
       "         2         10548\n",
       "         3         10662\n",
       "         4         10776\n",
       " 3       0         10430\n",
       "         1         10546\n",
       "         2         10662\n",
       "         3         10778\n",
       "         4         10894\n",
       " 4       0         10540\n",
       "         1         10658\n",
       "         2         10776\n",
       "         3         10894\n",
       "         4         11012\n",
       " dtype: int64, 2: track1  track2\n",
       " 5       5         11250\n",
       "         6         11370\n",
       "         7         11490\n",
       "         8         11610\n",
       "         9         11730\n",
       " 6       5         11370\n",
       "         6         11492\n",
       "         7         11614\n",
       "         8         11736\n",
       "         9         11858\n",
       " 7       5         11490\n",
       "         6         11614\n",
       "         7         11738\n",
       "         8         11862\n",
       "         9         11986\n",
       " 8       5         11610\n",
       "         6         11736\n",
       "         7         11862\n",
       "         8         11988\n",
       "         9         12114\n",
       " 9       5         11730\n",
       "         6         11858\n",
       "         7         11986\n",
       "         8         12114\n",
       "         9         12242\n",
       " dtype: int64}"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Maybe you can combine this dictionary into one big DataFrame/Series with a new MultiIndex?\n",
    "series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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