.ipynb_checkpoints/convert_categorical_to_numeric_naively-checkpoint.ipynb

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     "cell_type": "markdown",
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     "source": [
      "# Convert A String Categorical Variable To A Numeric Variable Naively\n",
      "\n",
      "- **Author:** [Chris Albon](http://www.chrisalbon.com/), [@ChrisAlbon](https://twitter.com/chrisalbon)\n",
      "- **Date:** -\n",
      "- **Repo:** [Python 3 code snippets for data science](https://github.com/chrisalbon/code_py)\n",
      "- **Note:** Originally from: Data Origami."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### import modules"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pandas as pd"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Create dataframe"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "raw_data = {'patient': [1, 1, 1, 2, 2], \n",
      "        'obs': [1, 2, 3, 1, 2], \n",
      "        'treatment': [0, 1, 0, 1, 0],\n",
      "        'score': ['strong', 'weak', 'normal', 'weak', 'strong']} \n",
      "df = pd.DataFrame(raw_data, columns = ['patient', 'obs', 'treatment', 'score'])\n",
      "df"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>patient</th>\n",
        "      <th>obs</th>\n",
        "      <th>treatment</th>\n",
        "      <th>score</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> strong</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 1</td>\n",
        "      <td> 2</td>\n",
        "      <td> 1</td>\n",
        "      <td>   weak</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 1</td>\n",
        "      <td> 3</td>\n",
        "      <td> 0</td>\n",
        "      <td> normal</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 2</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td>   weak</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> 2</td>\n",
        "      <td> 2</td>\n",
        "      <td> 0</td>\n",
        "      <td> strong</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 3,
       "text": [
        "   patient  obs  treatment   score\n",
        "0        1    1          0  strong\n",
        "1        1    2          1    weak\n",
        "2        1    3          0  normal\n",
        "3        2    1          1    weak\n",
        "4        2    2          0  strong"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Create a function that converts all values of df['score'] into numbers"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def score_to_numeric(x):\n",
      "    if x=='strong':\n",
      "        return 3\n",
      "    if x=='normal':\n",
      "        return 2\n",
      "    if x=='weak':\n",
      "        return 1"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Apply the function to the score variable"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df['score_num'] = df['score'].apply(score_to_numeric)\n",
      "df"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>patient</th>\n",
        "      <th>obs</th>\n",
        "      <th>treatment</th>\n",
        "      <th>score</th>\n",
        "      <th>score_num</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> strong</td>\n",
        "      <td> 3</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 1</td>\n",
        "      <td> 2</td>\n",
        "      <td> 1</td>\n",
        "      <td>   weak</td>\n",
        "      <td> 1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 1</td>\n",
        "      <td> 3</td>\n",
        "      <td> 0</td>\n",
        "      <td> normal</td>\n",
        "      <td> 2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 2</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td>   weak</td>\n",
        "      <td> 1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> 2</td>\n",
        "      <td> 2</td>\n",
        "      <td> 0</td>\n",
        "      <td> strong</td>\n",
        "      <td> 3</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 7,
       "text": [
        "   patient  obs  treatment   score  score_num\n",
        "0        1    1          0  strong          3\n",
        "1        1    2          1    weak          1\n",
        "2        1    3          0  normal          2\n",
        "3        2    1          1    weak          1\n",
        "4        2    2          0  strong          3"
       ]
      }
     ],
     "prompt_number": 7
    },
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     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
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     "outputs": []
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