Wrangling -- Intro to pandas.DataFrames.ipynb

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    "# same ol boilerplate, except no csv.DictReader\n",
    "from os import makedirs\n",
    "from os.path import join\n",
    "\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "# but now we got some pandas\n",
    "import pandas as pd\n",
    "\n",
    "DATA_FILENAME = join('data', 'climate', 'extracted', 'nasa-ghgases-co2-mean.csv')"
   ]
  },
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   "cell_type": "code",
   "execution_count": 17,
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   "source": [
    "df = pd.read_csv(DATA_FILENAME)"
   ]
  },
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   "cell_type": "code",
   "execution_count": 18,
   "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>year</th>\n",
       "      <th>co2_ppm_mean</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1850</td>\n",
       "      <td>285.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1851</td>\n",
       "      <td>285.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1852</td>\n",
       "      <td>285.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1853</td>\n",
       "      <td>285.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1854</td>\n",
       "      <td>284.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1855</td>\n",
       "      <td>285.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1856</td>\n",
       "      <td>285.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1857</td>\n",
       "      <td>285.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1858</td>\n",
       "      <td>285.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1859</td>\n",
       "      <td>286.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year  co2_ppm_mean\n",
       "0  1850         285.2\n",
       "1  1851         285.1\n",
       "2  1852         285.0\n",
       "3  1853         285.0\n",
       "4  1854         284.9\n",
       "5  1855         285.1\n",
       "6  1856         285.4\n",
       "7  1857         285.6\n",
       "8  1858         285.9\n",
       "9  1859         286.1"
      ]
     },
     "execution_count": 18,
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   ],
   "source": [
    "df.head(10)"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Subsetting columns with the `iloc` attribute\n",
    "\n",
    "`iloc` provides a way to slice a range of rows of a dataframe. Note the indexes are preserved:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
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   "outputs": [
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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>year</th>\n",
       "      <th>co2_ppm_mean</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1855</td>\n",
       "      <td>285.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1856</td>\n",
       "      <td>285.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1857</td>\n",
       "      <td>285.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1858</td>\n",
       "      <td>285.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1859</td>\n",
       "      <td>286.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year  co2_ppm_mean\n",
       "5  1855         285.1\n",
       "6  1856         285.4\n",
       "7  1857         285.6\n",
       "8  1858         285.9\n",
       "9  1859         286.1"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "df.iloc[5:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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    "collapsed": true
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   "source": []
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Select columns\n",
    "\n",
    "Just pass in a list of column names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
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   "outputs": [
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     "data": {
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       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>co2_ppm_mean</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>285.2</td>\n",
       "      <td>1850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>285.1</td>\n",
       "      <td>1851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>285.0</td>\n",
       "      <td>1852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>285.0</td>\n",
       "      <td>1853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>284.9</td>\n",
       "      <td>1854</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   co2_ppm_mean  year\n",
       "0         285.2  1850\n",
       "1         285.1  1851\n",
       "2         285.0  1852\n",
       "3         285.0  1853\n",
       "4         284.9  1854"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "df[['co2_ppm_mean', 'year']].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Adding a derived column\n",
    "\n",
    "### Add a decade column\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
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   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>co2_ppm_mean</th>\n",
       "      <th>decade</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1850</td>\n",
       "      <td>285.2</td>\n",
       "      <td>1850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1851</td>\n",
       "      <td>285.1</td>\n",
       "      <td>1850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1852</td>\n",
       "      <td>285.0</td>\n",
       "      <td>1850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1853</td>\n",
       "      <td>285.0</td>\n",
       "      <td>1850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1854</td>\n",
       "      <td>284.9</td>\n",
       "      <td>1850</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year  co2_ppm_mean  decade\n",
       "0  1850         285.2    1850\n",
       "1  1851         285.1    1850\n",
       "2  1852         285.0    1850\n",
       "3  1853         285.0    1850\n",
       "4  1854         284.9    1850"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['decade'] = df.round({'year': -1})['year']\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "### Add change over year for the `co2_ppm_mean`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# Grouping"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
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    "collapsed": true
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