notebooks/examples.ipynb

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  {
   "cell_type": "markdown",
   "id": "848b55cd-3166-4797-9364-01e8e8a3f08d",
   "metadata": {},
   "source": [
    "# PDX: Helper functions to run SQL on Pandas DataFrames\n",
    "\n",
    "Leverages DuckDB, which has some nice SQL language extensions:\n",
    "\n",
    "- https://duckdb.org/2022/05/04/friendlier-sql.html\n",
    "- https://duckdb.org/2022/11/14/announcing-duckdb-060.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "238b080c-f228-4a37-a3e2-ba5851683b45",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.5.0\n"
     ]
    }
   ],
   "source": [
    "import pdx\n",
    "print(pdx.__version__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "6e21f088-b248-4b02-95a3-8440c0e32790",
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "      <th>species</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
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       "      <th>145</th>\n",
       "      <td>6.7</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>6.3</td>\n",
       "      <td>2.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>virginica</td>\n",
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       "      <td>6.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>6.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>5.4</td>\n",
       "      <td>2.3</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>5.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>1.8</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>150 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     sepal_length  sepal_width  petal_length  petal_width    species\n",
       "0             5.1          3.5           1.4          0.2     setosa\n",
       "1             4.9          3.0           1.4          0.2     setosa\n",
       "2             4.7          3.2           1.3          0.2     setosa\n",
       "3             4.6          3.1           1.5          0.2     setosa\n",
       "4             5.0          3.6           1.4          0.2     setosa\n",
       "..            ...          ...           ...          ...        ...\n",
       "145           6.7          3.0           5.2          2.3  virginica\n",
       "146           6.3          2.5           5.0          1.9  virginica\n",
       "147           6.5          3.0           5.2          2.0  virginica\n",
       "148           6.2          3.4           5.4          2.3  virginica\n",
       "149           5.9          3.0           5.1          1.8  virginica\n",
       "\n",
       "[150 rows x 5 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris = pdx.data.get_iris()\n",
    "iris"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "eb25e668-f1f8-42f2-8953-25546d0fba9f",
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    {
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       "\u001b[0;31mSignature:\u001b[0m \u001b[0miris\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msql\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ms\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m''\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtbl_name\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'_df'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
       "\u001b[0;31mDocstring:\u001b[0m\n",
       "Run a DuckDB SQL query against Pandas DataFrame.\n",
       "\n",
       "DataFrame will be referred to by string given in `tbl_name`.\n",
       "The query starts with a `from {table_name}` clause.\n",
       "Since DuckDB 0.6, the `select` clause is optional, defaulting to `select *`.\n",
       "\n",
       "Examples\n",
       "--------\n",
       "\n",
       "```\n",
       "df.sql('select col_a where col_b > 0')\n",
       "```\n",
       "\n",
       "is equivalent to the query\n",
       "\n",
       "```\n",
       "select\n",
       "    col_a\n",
       "from\n",
       "    _df\n",
       "where\n",
       "    col_b > 0\n",
       "```\n",
       "\n",
       "\n",
       "`df.sql('where col_b > 0')` is equivalent to\n",
       "\n",
       "```\n",
       "select\n",
       "    *\n",
       "from\n",
       "    _df\n",
       "where\n",
       "    col_b > 0\n",
       "```\n",
       "\n",
       "Note that `df.sql()` is equivalent to\n",
       "\n",
       "```\n",
       "select * from _df\n",
       "```\n",
       "\u001b[0;31mFile:\u001b[0m      ~/work/pdx/src/pdx/_pandas.py\n",
       "\u001b[0;31mType:\u001b[0m      method"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "iris.sql?"
   ]
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   "execution_count": 4,
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       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "      <th>species</th>\n",
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       "      <td>setosa</td>\n",
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       "      <td>virginica</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>virginica</td>\n",
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       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>6.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>5.4</td>\n",
       "      <td>2.3</td>\n",
       "      <td>virginica</td>\n",
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       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>5.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>1.8</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "<p>150 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     sepal_length  sepal_width  petal_length  petal_width    species\n",
       "0             5.1          3.5           1.4          0.2     setosa\n",
       "1             4.9          3.0           1.4          0.2     setosa\n",
       "2             4.7          3.2           1.3          0.2     setosa\n",
       "3             4.6          3.1           1.5          0.2     setosa\n",
       "4             5.0          3.6           1.4          0.2     setosa\n",
       "..            ...          ...           ...          ...        ...\n",
       "145           6.7          3.0           5.2          2.3  virginica\n",
       "146           6.3          2.5           5.0          1.9  virginica\n",
       "147           6.5          3.0           5.2          2.0  virginica\n",
       "148           6.2          3.4           5.4          2.3  virginica\n",
       "149           5.9          3.0           5.1          1.8  virginica\n",
       "\n",
       "[150 rows x 5 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris.sql('select *')"
   ]
  },
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   "execution_count": 5,
   "id": "1d7040a6-3fdd-47c1-a8f8-8a130e6d9520",
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       "      <td>virginica</td>\n",
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       "  </tbody>\n",
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       "<p>150 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     sepal_length  sepal_width  petal_length  petal_width    species\n",
       "0             5.1          3.5           1.4          0.2     setosa\n",
       "1             4.9          3.0           1.4          0.2     setosa\n",
       "2             4.7          3.2           1.3          0.2     setosa\n",
       "3             4.6          3.1           1.5          0.2     setosa\n",
       "4             5.0          3.6           1.4          0.2     setosa\n",
       "..            ...          ...           ...          ...        ...\n",
       "145           6.7          3.0           5.2          2.3  virginica\n",
       "146           6.3          2.5           5.0          1.9  virginica\n",
       "147           6.5          3.0           5.2          2.0  virginica\n",
       "148           6.2          3.4           5.4          2.3  virginica\n",
       "149           5.9          3.0           5.1          1.8  virginica\n",
       "\n",
       "[150 rows x 5 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris.sql('')"
   ]
  },
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   "execution_count": 6,
   "id": "dd44e9a1-359f-4e66-913f-4a7a7887b427",
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       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>6.7</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>6.3</td>\n",
       "      <td>2.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>6.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>6.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>5.4</td>\n",
       "      <td>2.3</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>5.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>1.8</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>150 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     sepal_length  sepal_width  petal_length  petal_width    species\n",
       "0             5.1          3.5           1.4          0.2     setosa\n",
       "1             4.9          3.0           1.4          0.2     setosa\n",
       "2             4.7          3.2           1.3          0.2     setosa\n",
       "3             4.6          3.1           1.5          0.2     setosa\n",
       "4             5.0          3.6           1.4          0.2     setosa\n",
       "..            ...          ...           ...          ...        ...\n",
       "145           6.7          3.0           5.2          2.3  virginica\n",
       "146           6.3          2.5           5.0          1.9  virginica\n",
       "147           6.5          3.0           5.2          2.0  virginica\n",
       "148           6.2          3.4           5.4          2.3  virginica\n",
       "149           5.9          3.0           5.1          1.8  virginica\n",
       "\n",
       "[150 rows x 5 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris.sql()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "bf062341-8ea9-4a3d-ab44-741dd9f4bca9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>species</th>\n",
       "      <th>num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>setosa</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>versicolor</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>virginica</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      species  num\n",
       "0      setosa   50\n",
       "1  versicolor   50\n",
       "2   virginica   50"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris.sql(\"\"\"\n",
    "select\n",
    "    species,\n",
    "    count(*)\n",
    "        as num,\n",
    "group by\n",
    "    1\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "27c8bacd-f217-495c-b21f-d77e8eb51f57",
   "metadata": {},
   "source": [
    "Equivalently, can also run the function and specify the DataFrame/table explicitly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "824ca44f-0802-42e0-955d-d6fbca28b9d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>species</th>\n",
       "      <th>num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>setosa</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>virginica</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>versicolor</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      species  num\n",
       "0      setosa   50\n",
       "1   virginica   50\n",
       "2  versicolor   50"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pdx.sql(\"\"\"\n",
    "select\n",
    "    species,\n",
    "    count(*)\n",
    "        as num,\n",
    "from\n",
    "    tbl\n",
    "group by\n",
    "    1\n",
    "\"\"\", tbl=iris)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d50ecc8a-acab-4ba2-8242-20e088b77fb2",
   "metadata": {},
   "source": [
    "Or, using the usual default table name, `_df`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "269fec1b-ba34-4f8d-b29d-96f70a7d7d29",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>species</th>\n",
       "      <th>num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>virginica</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>setosa</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>versicolor</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      species  num\n",
       "0   virginica   50\n",
       "1      setosa   50\n",
       "2  versicolor   50"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pdx.sql(\"\"\"\n",
    "select\n",
    "    species,\n",
    "    count(*)\n",
    "        as num,\n",
    "from\n",
    "    _df\n",
    "group by\n",
    "    1\n",
    "\"\"\", _df=iris)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c07cd3a-035c-4ad8-8d41-e55ccfb09e0c",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Joining multiple tables/dataframes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "cffe2bd0-ad68-416f-b354-64bb4fc0858e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>species</th>\n",
       "      <th>avg_petal_width</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>setosa</td>\n",
       "      <td>0.246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>versicolor</td>\n",
       "      <td>1.326</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>virginica</td>\n",
       "      <td>2.026</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      species  avg_petal_width\n",
       "0      setosa            0.246\n",
       "1  versicolor            1.326\n",
       "2   virginica            2.026"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = \"\"\"\n",
    "select\n",
    "    species,\n",
    "    avg(petal_width)\n",
    "        as avg_petal_width,\n",
    "group by\n",
    "    1\n",
    "\"\"\"\n",
    "\n",
    "df2 = iris.sql(s)\n",
    "\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "e742cab3-ca83-45df-bff1-598b126f35c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "      <th>species</th>\n",
       "      <th>species_avg_petal_width</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>0.246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>0.246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>0.246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>0.246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>0.246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>6.7</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>virginica</td>\n",
       "      <td>2.026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>6.3</td>\n",
       "      <td>2.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>virginica</td>\n",
       "      <td>2.026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>6.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>virginica</td>\n",
       "      <td>2.026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>6.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>5.4</td>\n",
       "      <td>2.3</td>\n",
       "      <td>virginica</td>\n",
       "      <td>2.026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>5.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>1.8</td>\n",
       "      <td>virginica</td>\n",
       "      <td>2.026</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>150 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     sepal_length  sepal_width  petal_length  petal_width    species  \\\n",
       "0             5.1          3.5           1.4          0.2     setosa   \n",
       "1             4.9          3.0           1.4          0.2     setosa   \n",
       "2             4.7          3.2           1.3          0.2     setosa   \n",
       "3             4.6          3.1           1.5          0.2     setosa   \n",
       "4             5.0          3.6           1.4          0.2     setosa   \n",
       "..            ...          ...           ...          ...        ...   \n",
       "145           6.7          3.0           5.2          2.3  virginica   \n",
       "146           6.3          2.5           5.0          1.9  virginica   \n",
       "147           6.5          3.0           5.2          2.0  virginica   \n",
       "148           6.2          3.4           5.4          2.3  virginica   \n",
       "149           5.9          3.0           5.1          1.8  virginica   \n",
       "\n",
       "     species_avg_petal_width  \n",
       "0                      0.246  \n",
       "1                      0.246  \n",
       "2                      0.246  \n",
       "3                      0.246  \n",
       "4                      0.246  \n",
       "..                       ...  \n",
       "145                    2.026  \n",
       "146                    2.026  \n",
       "147                    2.026  \n",
       "148                    2.026  \n",
       "149                    2.026  \n",
       "\n",
       "[150 rows x 6 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = \"\"\"\n",
    "select\n",
    "      iris.*\n",
    "    , df2.avg_petal_width\n",
    "        as species_avg_petal_width\n",
    "from\n",
    "    iris\n",
    "left join\n",
    "    df2\n",
    "on\n",
    "    iris.species = df2.species\n",
    "\"\"\"\n",
    "\n",
    "pdx.sql(s, iris=iris, df2=df2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e1f7c1e9-7724-4f31-a2d8-03b4694e88fd",
   "metadata": {},
   "source": [
    "## Alternatively, using a CTE\n",
    "\n",
    "When a query string starts with \"`with`\", `pdx` won't prepend \"`from {tbl_name}`\" to make working with CTEs (based on a single DataFrame) easier."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1ef65092-85e6-4390-8d98-3a95b34a0fc2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "      <th>species</th>\n",
       "      <th>species_avg_petal_width</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>0.246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>0.246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>0.246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>0.246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>0.246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>6.7</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>virginica</td>\n",
       "      <td>2.026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>6.3</td>\n",
       "      <td>2.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>virginica</td>\n",
       "      <td>2.026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>6.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>virginica</td>\n",
       "      <td>2.026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>6.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>5.4</td>\n",
       "      <td>2.3</td>\n",
       "      <td>virginica</td>\n",
       "      <td>2.026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>5.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>1.8</td>\n",
       "      <td>virginica</td>\n",
       "      <td>2.026</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>150 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     sepal_length  sepal_width  petal_length  petal_width    species  \\\n",
       "0             5.1          3.5           1.4          0.2     setosa   \n",
       "1             4.9          3.0           1.4          0.2     setosa   \n",
       "2             4.7          3.2           1.3          0.2     setosa   \n",
       "3             4.6          3.1           1.5          0.2     setosa   \n",
       "4             5.0          3.6           1.4          0.2     setosa   \n",
       "..            ...          ...           ...          ...        ...   \n",
       "145           6.7          3.0           5.2          2.3  virginica   \n",
       "146           6.3          2.5           5.0          1.9  virginica   \n",
       "147           6.5          3.0           5.2          2.0  virginica   \n",
       "148           6.2          3.4           5.4          2.3  virginica   \n",
       "149           5.9          3.0           5.1          1.8  virginica   \n",
       "\n",
       "     species_avg_petal_width  \n",
       "0                      0.246  \n",
       "1                      0.246  \n",
       "2                      0.246  \n",
       "3                      0.246  \n",
       "4                      0.246  \n",
       "..                       ...  \n",
       "145                    2.026  \n",
       "146                    2.026  \n",
       "147                    2.026  \n",
       "148                    2.026  \n",
       "149                    2.026  \n",
       "\n",
       "[150 rows x 6 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = \"\"\"\n",
    "with\n",
    "\n",
    "  avg as\n",
    "(\n",
    "select\n",
    "    species,\n",
    "    avg(petal_width)\n",
    "        as avg_petal_width,\n",
    "from\n",
    "    _df\n",
    "group by\n",
    "    1\n",
    ")\n",
    "\n",
    "select\n",
    "      d.*\n",
    "    , a.avg_petal_width\n",
    "        as species_avg_petal_width\n",
    "from\n",
    "    _df as d\n",
    "left join\n",
    "    avg as a\n",
    "on\n",
    "    d.species = a.species\n",
    "\"\"\"\n",
    "\n",
    "iris.sql(s)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1cfa150d-7107-4e84-bd7c-7e2a375f389f",
   "metadata": {},
   "source": [
    "Using `using` syntax:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "566808ea-3657-4b42-a690-5a4980f39f6e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "      <th>species</th>\n",
       "      <th>species_avg_petal_width</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>0.246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>0.246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>0.246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>0.246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "      <td>0.246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>6.7</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>virginica</td>\n",
       "      <td>2.026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>6.3</td>\n",
       "      <td>2.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>virginica</td>\n",
       "      <td>2.026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>6.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>virginica</td>\n",
       "      <td>2.026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>6.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>5.4</td>\n",
       "      <td>2.3</td>\n",
       "      <td>virginica</td>\n",
       "      <td>2.026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>5.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>1.8</td>\n",
       "      <td>virginica</td>\n",
       "      <td>2.026</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>150 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     sepal_length  sepal_width  petal_length  petal_width    species  \\\n",
       "0             5.1          3.5           1.4          0.2     setosa   \n",
       "1             4.9          3.0           1.4          0.2     setosa   \n",
       "2             4.7          3.2           1.3          0.2     setosa   \n",
       "3             4.6          3.1           1.5          0.2     setosa   \n",
       "4             5.0          3.6           1.4          0.2     setosa   \n",
       "..            ...          ...           ...          ...        ...   \n",
       "145           6.7          3.0           5.2          2.3  virginica   \n",
       "146           6.3          2.5           5.0          1.9  virginica   \n",
       "147           6.5          3.0           5.2          2.0  virginica   \n",
       "148           6.2          3.4           5.4          2.3  virginica   \n",
       "149           5.9          3.0           5.1          1.8  virginica   \n",
       "\n",
       "     species_avg_petal_width  \n",
       "0                      0.246  \n",
       "1                      0.246  \n",
       "2                      0.246  \n",
       "3                      0.246  \n",
       "4                      0.246  \n",
       "..                       ...  \n",
       "145                    2.026  \n",
       "146                    2.026  \n",
       "147                    2.026  \n",
       "148                    2.026  \n",
       "149                    2.026  \n",
       "\n",
       "[150 rows x 6 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = \"\"\"\n",
    "with\n",
    "\n",
    "  avg as\n",
    "(\n",
    "select\n",
    "    species,\n",
    "    avg(petal_width)\n",
    "        as species_avg_petal_width,\n",
    "from\n",
    "    _df\n",
    "group by\n",
    "    1\n",
    ")\n",
    "\n",
    "select\n",
    "    *\n",
    "from\n",
    "    _df\n",
    "left join\n",
    "    avg\n",
    "using\n",
    "    (species)\n",
    "\"\"\"\n",
    "\n",
    "iris.sql(s)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10d8c300-af1a-4326-b4aa-da24bdb7609a",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Pandas DataFrame helper functions\n",
    "\n",
    "A few helper functions for common patterns to extract data from dataframes."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "471ead30-03cb-496f-b2aa-1f6ac5fd4a61",
   "metadata": {},
   "source": [
    "## `df.aslist()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "58c32268-5ec3-43e8-944e-adc047850fae",
   "metadata": {},
   "outputs": [],
   "source": [
    "out = iris.sql('select species group by 1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "083609de-4ca2-4086-8a05-e85e959a37a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>species</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>versicolor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      species\n",
       "0   virginica\n",
       "1  versicolor\n",
       "2      setosa"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "4ae71369-29dd-4fd8-a888-ca3d2c3625e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['virginica', 'versicolor', 'setosa']"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out.aslist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "59443e79-c4e8-48a5-a52e-586ada54cc38",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['setosa', 'virginica', 'versicolor']"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris.sql('select species group by 1').aslist()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb3f13b5-e555-4077-8524-183d2929e593",
   "metadata": {},
   "source": [
    "## `df.asdict()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "feeda56b-a3d2-4907-967b-0ceac9a567fd",
   "metadata": {},
   "outputs": [],
   "source": [
    "out = iris.sql(\"\"\"\n",
    "select\n",
    "    avg(sepal_length),\n",
    "    avg(sepal_width),\n",
    "    avg(petal_length),\n",
    "    avg(petal_width),\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "f27fb9a6-02d5-4ae0-8aa4-4c12d5ddb35f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>avg(sepal_length)</th>\n",
       "      <th>avg(sepal_width)</th>\n",
       "      <th>avg(petal_length)</th>\n",
       "      <th>avg(petal_width)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.843333</td>\n",
       "      <td>3.057333</td>\n",
       "      <td>3.758</td>\n",
       "      <td>1.199333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   avg(sepal_length)  avg(sepal_width)  avg(petal_length)  avg(petal_width)\n",
       "0           5.843333          3.057333              3.758          1.199333"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "dd385265-0f4d-4898-8f6d-edfe780db9f4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'avg(sepal_length)': np.float64(5.843333333333335),\n",
       " 'avg(sepal_width)': np.float64(3.057333333333334),\n",
       " 'avg(petal_length)': np.float64(3.7580000000000027),\n",
       " 'avg(petal_width)': np.float64(1.199333333333334)}"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out.asdict()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "1879ace9-8c73-4c55-aefd-d2ea417bcca5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'avg(sepal_length)': np.float64(5.843333333333335),\n",
       " 'avg(sepal_width)': np.float64(3.057333333333334),\n",
       " 'avg(petal_length)': np.float64(3.7580000000000027),\n",
       " 'avg(petal_width)': np.float64(1.199333333333334)}"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris.sql(\"\"\"\n",
    "select\n",
    "    avg(sepal_length),\n",
    "    avg(sepal_width),\n",
    "    avg(petal_length),\n",
    "    avg(petal_width),\n",
    "\"\"\").asdict()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2d7eae6b-980e-4041-a034-f0de334c3860",
   "metadata": {},
   "source": [
    "## `df.asitem()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "ca4402a0-c10c-475b-afc9-2682a4146ddf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count_star()</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>150</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   count_star()\n",
       "0           150"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out = iris.sql('select count(*)')\n",
    "out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "ad8fc75a-0d53-4002-8586-423ea3dbc343",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "150"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out.asitem()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "7e4375af-cbe4-429e-b760-0f2e4a7f1278",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "150"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris.sql('select count(*)').asitem()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3be9718a-1b7e-4ec8-93dd-7c033ed353de",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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