Lecture 41 - Permutation.ipynb

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   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from pandas import Series, DataFrame"
   ]
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   "cell_type": "code",
   "execution_count": 2,
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   "source": [
    "dframe = DataFrame(np.arange(16).reshape(4,4))"
   ]
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    "blender = np.random.permutation(4)"
   ]
  },
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       "array([0, 3, 1, 2])"
      ]
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    "blender"
   ]
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       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
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       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12</td>\n",
       "      <td>13</td>\n",
       "      <td>14</td>\n",
       "      <td>15</td>\n",
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      "text/plain": [
       "    0   1   2   3\n",
       "0   0   1   2   3\n",
       "1   4   5   6   7\n",
       "2   8   9  10  11\n",
       "3  12  13  14  15"
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     },
     "execution_count": 5,
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    "dframe"
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       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
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       "      <th>0</th>\n",
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       "      <td>0</td>\n",
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       "      <td>2</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
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       "    0   1   2   3\n",
       "0   0   1   2   3\n",
       "3  12  13  14  15\n",
       "1   4   5   6   7\n",
       "2   8   9  10  11"
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   "source": [
    "dframe.take(blender)"
   ]
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   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
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   "source": [
    "box = np.array([1,2,3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "shaker = np.random.randint(0,len(box),size=10)"
   ]
  },
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   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
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    {
     "data": {
      "text/plain": [
       "array([1, 1, 0, 0, 2, 2, 0, 1, 2, 0])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "shaker"
   ]
  },
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   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
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   "source": [
    "hand_grabs = box.take(shaker)"
   ]
  },
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   "execution_count": 11,
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       "array([2, 2, 1, 1, 3, 3, 1, 2, 3, 1])"
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    "hand_grabs"
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   "execution_count": null,
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