Recreating issue #744 in pandas.

Issue_744.ipynb

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   "source": [
    "import pandas as pd\n",
    "from StringIO import StringIO"
   ]
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       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>a=0,b=4,c=6                                   ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>a=10,b=5,c=-1                                 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>a=20,c=60                                     ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>a=430                                         ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>c=200</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      "text/plain": [
       "                                                value\n",
       "id                                                   \n",
       "a   a=0,b=4,c=6                                   ...\n",
       "b   a=10,b=5,c=-1                                 ...\n",
       "c   a=20,c=60                                     ...\n",
       "d   a=430                                         ...\n",
       "e                                               c=200"
      ]
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   "source": [
    "f=StringIO(\"\"\"id\tvalue\n",
    "a\ta=0,b=4,c=6                                                                                                                                 \n",
    "b\ta=10,b=5,c=-1                                                                                                                               \n",
    "c\ta=20,c=60                                                                                                                                   \n",
    "d\ta=430                                                                                                                                       \n",
    "e\tc=200\"\"\")\n",
    "df = pd.read_table(f, index_col=[0])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
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   "outputs": [],
   "source": [
    "import numpy as np                                                                                                                                  \n",
    "def value_convert(value, fields=[\"a\",\"b\",\"c\"]):                                                                                                     \n",
    "    pairs = value.split(\",\")                                                                                                                        \n",
    "    from collections import defaultdict                                                                                                             \n",
    "    d = defaultdict(int)                                                                                                                            \n",
    "    for pair in pairs:                                                                                                                              \n",
    "        k, v = pair.split(\"=\")                                                                                                                      \n",
    "        d[k] = v                                                                                                                                    \n",
    "    results = np.array([d[f] for f in fields],                                                                                                      \n",
    "                       dtype='int64')                                                                                                               \n",
    "    return results    "
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   "execution_count": 4,
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       "<div>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>[0, 4, 6]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>[10, 5, -1]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>[20, 0, 60]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>[430, 0, 0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>[0, 0, 200]</td>\n",
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       "          value\n",
       "id             \n",
       "a     [0, 4, 6]\n",
       "b   [10, 5, -1]\n",
       "c   [20, 0, 60]\n",
       "d   [430, 0, 0]\n",
       "e   [0, 0, 200]"
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     "execution_count": 4,
     "metadata": {},
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   "source": [
    "f.seek(0)\n",
    "pd.read_table(f, index_col=[0], converters={'value': value_convert})"
   ]
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   "cell_type": "code",
   "execution_count": null,
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