duckdb-python-basics.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "0426c49f",
   "metadata": {},
   "source": [
    "# DuckDB Python Client Basics\n",
    "Author: Mark Bauer"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c460034",
   "metadata": {},
   "source": [
    "This guide is based on the DuckDB documentation here: https://duckdb.org/docs/api/python/overview. To install the DuckdDB Python API, refer to the docs above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ea8b1c86",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# import libraries\n",
    "import duckdb\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import polars as pl\n",
    "import pyarrow as pa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "629b2dcf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Python implementation: CPython\n",
      "Python version       : 3.11.0\n",
      "IPython version      : 8.6.0\n",
      "\n",
      "duckdb : 1.0.0\n",
      "pandas : 1.5.1\n",
      "numpy  : 1.23.4\n",
      "polars : 0.14.28\n",
      "pyarrow: 9.0.0\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# reproducibility\n",
    "%reload_ext watermark\n",
    "%watermark -v -p duckdb,pandas,numpy,polars,pyarrow"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bd1ad04d",
   "metadata": {},
   "source": [
    "# Table of Contents\n",
    "1. Basic Python API Usage\n",
    "2. Data Input\n",
    "3. DataFrames\n",
    "4. Result Conversion\n",
    "5. Writing Data to Disk\n",
    "6. Connection Options  \n",
    "    - 6.1 Using an In-Memory Database  \n",
    "    - 6.2 Persistent Storage\n",
    "7. Loading and Installing Extensions   \n",
    "8. Jupyter Notebooks and Querying Pandas Dataframes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba0d656e",
   "metadata": {},
   "source": [
    "# 1. Basic Python API Usage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "aea81e2e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "┌───────┬──────────────┬──────────────┬─────────┬─────────┐\n",
       "│   a   │      b       │      c       │    d    │    e    │\n",
       "│ int32 │ decimal(2,1) │ decimal(2,1) │ varchar │ boolean │\n",
       "├───────┼──────────────┼──────────────┼─────────┼─────────┤\n",
       "│     1 │          2.0 │          2.0 │ a       │ true    │\n",
       "└───────┴──────────────┴──────────────┴─────────┴─────────┘"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# duckdb.sql command\n",
    "sql = \"\"\"\n",
    "    SELECT\n",
    "        1 AS a,\n",
    "        2.0 AS b,\n",
    "        b AS c,\n",
    "        'a' AS d,\n",
    "        TRUE AS e\n",
    "\"\"\"\n",
    "\n",
    "duckdb.sql(sql)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "3688ea4b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "duckdb.duckdb.DuckDBPyRelation"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# identify type of object returned\n",
    "type(duckdb.sql(sql))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "dfd46552",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "┌───────┬──────────────┬──────────────┬─────────┬─────────┐\n",
      "│   a   │      b       │      c       │    d    │    e    │\n",
      "│ int32 │ decimal(2,1) │ decimal(2,1) │ varchar │ boolean │\n",
      "├───────┼──────────────┼──────────────┼─────────┼─────────┤\n",
      "│     1 │          2.0 │          2.0 │ a       │ true    │\n",
      "└───────┴──────────────┴──────────────┴─────────┴─────────┘\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# you can also use .show() on the relation object to execute query\n",
    "duckdb.sql(sql).show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "c68e7c41",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "┌───────┬──────────────┬──────────────┬─────────┬─────────┐\n",
       "│   a   │      b       │      c       │    d    │    e    │\n",
       "│ int32 │ decimal(2,1) │ decimal(2,1) │ varchar │ boolean │\n",
       "├───────┼──────────────┼──────────────┼─────────┼─────────┤\n",
       "│     1 │          2.0 │          2.0 │ a       │ true    │\n",
       "└───────┴──────────────┴──────────────┴─────────┴─────────┘"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# reference and query the relation object like a table\n",
    "sql = \"\"\"\n",
    "    SELECT\n",
    "        1 AS a,\n",
    "        2.0 AS b,\n",
    "        b AS c,\n",
    "        'a' AS d,\n",
    "        TRUE AS e\n",
    "\"\"\"\n",
    "\n",
    "relation = duckdb.sql(sql)\n",
    "\n",
    "duckdb.sql(\"SELECT * FROM relation\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9bfe67af",
   "metadata": {},
   "source": [
    "# 2. Data Input\n",
    "We will focus on reading CSVs for now. Below are various ways to read in CSV files."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "eb9658fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "┌──────────────────────┬──────────┬──────────┬────────────┬───┬────────────┬────────────────────┬─────────────────┐\n",
       "│       the_geom       │ Asset_ID │  GI_ID   │ DEP_Contra │ … │ Construc_1 │     Program_Ar     │   Status_Gro    │\n",
       "│       varchar        │  int64   │ varchar  │  varchar   │   │  varchar   │      varchar       │     varchar     │\n",
       "├──────────────────────┼──────────┼──────────┼────────────┼───┼────────────┼────────────────────┼─────────────────┤\n",
       "│ POINT (-73.8116762…  │    94002 │ 1A       │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed     │\n",
       "│ POINT (-73.8122857…  │    94012 │ GS6A     │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed     │\n",
       "│ POINT (-73.8122344…  │    94017 │ GS8C     │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed     │\n",
       "│ POINT (-73.8120597…  │    94019 │ GS8E     │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed     │\n",
       "│ POINT (-73.8131019…  │    94021 │ 10A      │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed     │\n",
       "│ POINT (-73.8126597…  │    94031 │ 16A      │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed     │\n",
       "│ POINT (-73.8125273…  │    94033 │ 16C      │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed     │\n",
       "│ POINT (-73.8124855…  │    94034 │ 16D      │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed     │\n",
       "│ POINT (-73.8123016…  │    94036 │ GS18A    │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed     │\n",
       "│ POINT (-73.8130240…  │    94037 │ 19A      │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed     │\n",
       "│          ·           │      ·   │  ·       │     ·      │ · │ ·          │         ·          │      ·          │\n",
       "│          ·           │      ·   │  ·       │     ·      │ · │ ·          │         ·          │      ·          │\n",
       "│          ·           │      ·   │  ·       │     ·      │ · │ ·          │         ·          │      ·          │\n",
       "│ POINT (-73.9075750…  │   181581 │ IB3034B  │ GKCI05-03  │ … │ 1          │ Right of Way (ROW) │ In Construction │\n",
       "│ POINT (-73.9122467…  │   181582 │ IB4076A  │ GKCI05-03  │ … │ 3          │ Right of Way (ROW) │ In Construction │\n",
       "│ POINT (-73.9122977…  │   181583 │ IB4076B  │ GKCI05-03  │ … │ 3          │ Right of Way (ROW) │ In Construction │\n",
       "│ POINT (-73.9123395…  │   181584 │ IB4076C  │ GKCI05-03  │ … │ 3          │ Right of Way (ROW) │ In Construction │\n",
       "│ POINT (-73.9123865…  │   181585 │ IB4076D  │ GKCI05-03  │ … │ 3          │ Right of Way (ROW) │ In Construction │\n",
       "│ POINT (-73.9122600…  │   181588 │ IB4091AA │ GKCI05-03  │ … │ 3          │ Right of Way (ROW) │ In Construction │\n",
       "│ POINT (-73.9107345…  │   181589 │ IB4102A  │ GKCI05-03  │ … │ 3          │ Right of Way (ROW) │ In Construction │\n",
       "│ POINT (-73.9107849…  │   181590 │ IB4102B  │ GKCI05-03  │ … │ 3          │ Right of Way (ROW) │ In Construction │\n",
       "│ POINT (-73.9108867…  │   181591 │ IB4102C  │ GKCI05-03  │ … │ 3          │ Right of Way (ROW) │ In Construction │\n",
       "│ POINT (-73.9093459…  │   181596 │ IB4138A  │ GKCI05-03  │ … │ 3          │ Right of Way (ROW) │ In Construction │\n",
       "├──────────────────────┴──────────┴──────────┴────────────┴───┴────────────┴────────────────────┴─────────────────┤\n",
       "│ ? rows (>9999 rows, 20 shown)                                                              30 columns (7 shown) │\n",
       "└─────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# reading a CSV file into a Relation object\n",
    "path = \"data/green_infrastructure.csv\"\n",
    "\n",
    "duckdb.read_csv(path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "ec888da3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "┌──────────────────────┬──────────┬─────────┬────────────┬───┬────────────┬────────────────────┬─────────────┐\n",
       "│       the_geom       │ Asset_ID │  GI_ID  │ DEP_Contra │ … │ Construc_1 │     Program_Ar     │ Status_Gro  │\n",
       "│       varchar        │  int64   │ varchar │  varchar   │   │  varchar   │      varchar       │   varchar   │\n",
       "├──────────────────────┼──────────┼─────────┼────────────┼───┼────────────┼────────────────────┼─────────────┤\n",
       "│ POINT (-73.8116762…  │    94002 │ 1A      │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed │\n",
       "│ POINT (-73.8122857…  │    94012 │ GS6A    │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed │\n",
       "│ POINT (-73.8122344…  │    94017 │ GS8C    │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed │\n",
       "│ POINT (-73.8120597…  │    94019 │ GS8E    │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed │\n",
       "│ POINT (-73.8131019…  │    94021 │ 10A     │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed │\n",
       "│ POINT (-73.8126597…  │    94031 │ 16A     │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed │\n",
       "│ POINT (-73.8125273…  │    94033 │ 16C     │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed │\n",
       "│ POINT (-73.8124855…  │    94034 │ 16D     │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed │\n",
       "│ POINT (-73.8123016…  │    94036 │ GS18A   │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed │\n",
       "│ POINT (-73.8130240…  │    94037 │ 19A     │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed │\n",
       "├──────────────────────┴──────────┴─────────┴────────────┴───┴────────────┴────────────────────┴─────────────┤\n",
       "│ 10 rows                                                                               30 columns (7 shown) │\n",
       "└────────────────────────────────────────────────────────────────────────────────────────────────────────────┘"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# directly query a CSV file as a Relation\n",
    "duckdb.sql(\"\"\"\n",
    "    SELECT *\n",
    "    FROM read_csv(\"data/green_infrastructure.csv\")\n",
    "    LIMIT 10\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "d32a2553",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "┌──────────────────────┬──────────┬──────────┬────────────┬───┬────────────┬────────────────────┬─────────────────┐\n",
       "│       the_geom       │ Asset_ID │  GI_ID   │ DEP_Contra │ … │ Construc_1 │     Program_Ar     │   Status_Gro    │\n",
       "│       varchar        │  int64   │ varchar  │  varchar   │   │  varchar   │      varchar       │     varchar     │\n",
       "├──────────────────────┼──────────┼──────────┼────────────┼───┼────────────┼────────────────────┼─────────────────┤\n",
       "│ POINT (-73.8116762…  │    94002 │ 1A       │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed     │\n",
       "│ POINT (-73.8122857…  │    94012 │ GS6A     │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed     │\n",
       "│ POINT (-73.8122344…  │    94017 │ GS8C     │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed     │\n",
       "│ POINT (-73.8120597…  │    94019 │ GS8E     │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed     │\n",
       "│ POINT (-73.8131019…  │    94021 │ 10A      │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed     │\n",
       "│ POINT (-73.8126597…  │    94031 │ 16A      │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed     │\n",
       "│ POINT (-73.8125273…  │    94033 │ 16C      │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed     │\n",
       "│ POINT (-73.8124855…  │    94034 │ 16D      │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed     │\n",
       "│ POINT (-73.8123016…  │    94036 │ GS18A    │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed     │\n",
       "│ POINT (-73.8130240…  │    94037 │ 19A      │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed     │\n",
       "│          ·           │      ·   │  ·       │     ·      │ · │ ·          │         ·          │      ·          │\n",
       "│          ·           │      ·   │  ·       │     ·      │ · │ ·          │         ·          │      ·          │\n",
       "│          ·           │      ·   │  ·       │     ·      │ · │ ·          │         ·          │      ·          │\n",
       "│ POINT (-73.9075750…  │   181581 │ IB3034B  │ GKCI05-03  │ … │ 1          │ Right of Way (ROW) │ In Construction │\n",
       "│ POINT (-73.9122467…  │   181582 │ IB4076A  │ GKCI05-03  │ … │ 3          │ Right of Way (ROW) │ In Construction │\n",
       "│ POINT (-73.9122977…  │   181583 │ IB4076B  │ GKCI05-03  │ … │ 3          │ Right of Way (ROW) │ In Construction │\n",
       "│ POINT (-73.9123395…  │   181584 │ IB4076C  │ GKCI05-03  │ … │ 3          │ Right of Way (ROW) │ In Construction │\n",
       "│ POINT (-73.9123865…  │   181585 │ IB4076D  │ GKCI05-03  │ … │ 3          │ Right of Way (ROW) │ In Construction │\n",
       "│ POINT (-73.9122600…  │   181588 │ IB4091AA │ GKCI05-03  │ … │ 3          │ Right of Way (ROW) │ In Construction │\n",
       "│ POINT (-73.9107345…  │   181589 │ IB4102A  │ GKCI05-03  │ … │ 3          │ Right of Way (ROW) │ In Construction │\n",
       "│ POINT (-73.9107849…  │   181590 │ IB4102B  │ GKCI05-03  │ … │ 3          │ Right of Way (ROW) │ In Construction │\n",
       "│ POINT (-73.9108867…  │   181591 │ IB4102C  │ GKCI05-03  │ … │ 3          │ Right of Way (ROW) │ In Construction │\n",
       "│ POINT (-73.9093459…  │   181596 │ IB4138A  │ GKCI05-03  │ … │ 3          │ Right of Way (ROW) │ In Construction │\n",
       "├──────────────────────┴──────────┴──────────┴────────────┴───┴────────────┴────────────────────┴─────────────────┤\n",
       "│ ? rows (>9999 rows, 20 shown)                                                              30 columns (7 shown) │\n",
       "└─────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# reading in a CSV by opening a connection and copying data to a table\n",
    "con = duckdb.connect()\n",
    "\n",
    "con.execute( \"\"\"\n",
    "    CREATE TABLE green_infrastructure\n",
    "    AS SELECT * FROM read_csv('data/green_infrastructure.csv')\n",
    "\"\"\")\n",
    "\n",
    "sql = \"\"\"\n",
    "    SELECT *\n",
    "    FROM green_infrastructure\n",
    "\"\"\"\n",
    "\n",
    "con.sql(sql)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "137f66ea",
   "metadata": {},
   "source": [
    "# 3. DataFrames"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "0287b248",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "┌─────────┐\n",
       "│ numbers │\n",
       "│  int64  │\n",
       "├─────────┤\n",
       "│       1 │\n",
       "│       2 │\n",
       "│       3 │\n",
       "│       4 │\n",
       "└─────────┘"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# pandas\n",
    "df = pd.DataFrame({\"numbers\": [1, 2, 3, 4]})\n",
    "\n",
    "duckdb.sql(\"SELECT * FROM df\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "27a20ed7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "┌─────────┐\n",
       "│ numbers │\n",
       "│  int64  │\n",
       "├─────────┤\n",
       "│       1 │\n",
       "│       2 │\n",
       "│       3 │\n",
       "│       4 │\n",
       "└─────────┘"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# polars\n",
    "df = pl.DataFrame({\"numbers\": [1, 2, 3, 4]})\n",
    "\n",
    "duckdb.sql(\"SELECT * FROM df\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "c37ccf2f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "┌─────────┐\n",
       "│ numbers │\n",
       "│  int64  │\n",
       "├─────────┤\n",
       "│       1 │\n",
       "│       2 │\n",
       "│       3 │\n",
       "│       4 │\n",
       "└─────────┘"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# pyarrow\n",
    "df = pa.Table.from_pydict({\"numbers\": [1, 2, 3, 4]})\n",
    "\n",
    "duckdb.sql(\"SELECT * FROM df\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17958ed3",
   "metadata": {},
   "source": [
    "# 4. Result Conversion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "7276322a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'list'>\n",
      "<class 'dict'>\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "<class 'polars.internals.dataframe.frame.DataFrame'>\n",
      "<class 'pyarrow.lib.Table'>\n"
     ]
    }
   ],
   "source": [
    "# Python objects\n",
    "print(type(duckdb.sql(\"SELECT 1 as num\").fetchall()))\n",
    "\n",
    "# NumPy Arrays\n",
    "print(type(duckdb.sql(\"SELECT 1 as num\").fetchnumpy())) \n",
    "\n",
    "# Pandas DataFrame\n",
    "print(type(duckdb.sql(\"SELECT 1 as num\").df()))\n",
    "\n",
    "# Polars DataFrame\n",
    "print(type(duckdb.sql(\"SELECT 1 as num\").pl()))\n",
    "\n",
    "# Arrow Table\n",
    "print(type(duckdb.sql(\"SELECT 1 as num\").arrow()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "09876990",
   "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>num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   num\n",
       "0    1"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Example: pandas DataFrame\n",
    "df = duckdb.sql(\"SELECT 1 as num\").df()\n",
    "\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "a000685c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# confirm pandas dataframe\n",
    "type(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b5d1563",
   "metadata": {},
   "source": [
    "# 5. Writing Data to Disk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "e96114dc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Write to a CSV file\n",
    "duckdb.sql(\"SELECT 100\").write_csv(\"data/out.csv\") \n",
    "\n",
    "# Write to a Parquet file\n",
    "duckdb.sql(\"SELECT 100\").write_parquet(\"data/out.parquet\") \n",
    "\n",
    "# Copy to a Parquet file\n",
    "duckdb.sql(\"COPY (SELECT 100) TO 'data/out.parquet'\")      "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "2cf98826",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "data-dictionary.xlsx      nynta2020_24c.zip         out.parquet\r\n",
      "green_infrastructure.csv  out.csv\r\n"
     ]
    }
   ],
   "source": [
    "ls data/"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c0f58f3",
   "metadata": {},
   "source": [
    "# 6. Connection Options"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eade746e",
   "metadata": {},
   "source": [
    "## 6.1 Using an In-Memory Database"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "cf649c71",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "duckdb.duckdb.DuckDBPyConnection"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create a DuckDB database instance\n",
    "con = duckdb.connect()\n",
    "\n",
    "type(con)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "e6a16bbb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "┌───────┬─────────┐\n",
      "│  num  │ letter  │\n",
      "│ int32 │ varchar │\n",
      "├───────┼─────────┤\n",
      "│     1 │ a       │\n",
      "└───────┴─────────┘\n",
      "\n"
     ]
    }
   ],
   "source": [
    "(con\n",
    " .sql(\"SELECT 1 AS num, 'a' AS letter\")\n",
    " .show()\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "95fa83d3",
   "metadata": {},
   "source": [
    "## 6.2 Persistent Storage"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "556988e8",
   "metadata": {},
   "source": [
    "A connection to a persistent database can be created using the `connect` function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "7595887f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "┌───────┐\n",
      "│   i   │\n",
      "│ int32 │\n",
      "├───────┤\n",
      "│     1 │\n",
      "│     2 │\n",
      "└───────┘\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# create a new file.db file\n",
    "con = duckdb.connect(\"data/file.db\")\n",
    "\n",
    "con.execute(\"CREATE TABLE IF NOT EXISTS integers (i INTEGER)\")\n",
    "con.execute(\"INSERT INTO integers VALUES (1), (2)\")\n",
    "\n",
    "con.sql(\"SELECT * FROM integers\").show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "8d6d63c4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "data-dictionary.xlsx      green_infrastructure.csv  out.parquet\r\n",
      "file.db                   nynta2020_24c.zip\r\n",
      "file.db.wal               out.csv\r\n"
     ]
    }
   ],
   "source": [
    "ls data/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "66e02c6d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# close connection\n",
    "con.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "a613fc68",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "data-dictionary.xlsx      green_infrastructure.csv  out.csv\r\n",
      "file.db                   nynta2020_24c.zip         out.parquet\r\n"
     ]
    }
   ],
   "source": [
    "ls data/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "46ca95dd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "┌───────┐\n",
      "│   i   │\n",
      "│ int32 │\n",
      "├───────┤\n",
      "│     1 │\n",
      "│     2 │\n",
      "└───────┘\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# reload the same file.db\n",
    "con = duckdb.connect(\"data/file.db\")\n",
    "\n",
    "con.sql(\"SELECT * FROM integers\").show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "7aa7493a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "┌───────┐\n",
      "│   i   │\n",
      "│ int32 │\n",
      "├───────┤\n",
      "│     1 │\n",
      "│     2 │\n",
      "│     3 │\n",
      "└───────┘\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# create a connection to a file called 'file.db'\n",
    "con = duckdb.connect(\"data/file.db\")\n",
    "\n",
    "# insert new values to file.db\n",
    "con.sql(\"INSERT INTO integers VALUES (3)\")\n",
    "\n",
    "# query the table\n",
    "con.table(\"integers\").show()\n",
    "\n",
    "# explicitly close the connection, Note: connections also closed implicitly when they go out of scope\n",
    "con.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "a7fae280",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "┌───────┐\n",
      "│   i   │\n",
      "│ int32 │\n",
      "├───────┤\n",
      "│     1 │\n",
      "│     2 │\n",
      "│     3 │\n",
      "│     4 │\n",
      "└───────┘\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# use a context manager to ensure connection is closed\n",
    "with duckdb.connect(\"data/file.db\") as con:\n",
    "    con.sql(\"INSERT INTO integers VALUES (4)\")\n",
    "    con.table(\"integers\").show()\n",
    "    # the context manager closes the connection automatically"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "49dbd761",
   "metadata": {},
   "source": [
    "# 7. Loading and Installing Extensions\n",
    "Overview of extensions: https://duckdb.org/docs/extensions/overview"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "932f1030",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "┌──────────────────────┬──────────┬─────────┬────────────┬───┬────────────┬────────────────────┬─────────────┐\n",
       "│       the_geom       │ Asset_ID │  GI_ID  │ DEP_Contra │ … │ Construc_1 │     Program_Ar     │ Status_Gro  │\n",
       "│       varchar        │  int64   │ varchar │  varchar   │   │  varchar   │      varchar       │   varchar   │\n",
       "├──────────────────────┼──────────┼─────────┼────────────┼───┼────────────┼────────────────────┼─────────────┤\n",
       "│ POINT (-73.8116762…  │    94002 │ 1A      │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed │\n",
       "│ POINT (-73.8122857…  │    94012 │ GS6A    │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed │\n",
       "│ POINT (-73.8122344…  │    94017 │ GS8C    │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed │\n",
       "│ POINT (-73.8120597…  │    94019 │ GS8E    │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed │\n",
       "│ POINT (-73.8131019…  │    94021 │ 10A     │ GQJA03-02  │ … │ Package-1  │ Right of Way (ROW) │ Constructed │\n",
       "├──────────────────────┴──────────┴─────────┴────────────┴───┴────────────┴────────────────────┴─────────────┤\n",
       "│ 5 rows                                                                                30 columns (7 shown) │\n",
       "└────────────────────────────────────────────────────────────────────────────────────────────────────────────┘"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# install and load duckdb-spatial extension\n",
    "con = duckdb.connect()\n",
    "con.install_extension(\"spatial\")\n",
    "con.load_extension(\"spatial\")\n",
    "\n",
    "# create table from CSV\n",
    "con.execute(\n",
    "    \"\"\"\n",
    "    CREATE TABLE green_infrastructure\n",
    "    AS FROM read_csv('data/green_infrastructure.csv')\n",
    "    \"\"\"\n",
    ")\n",
    "\n",
    "# sanity check on table\n",
    "con.sql(\n",
    "    \"\"\"\n",
    "    SELECT *\n",
    "    FROM green_infrastructure LIMIT 5\n",
    "    \"\"\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "49eb4631",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "┌──────────────────────────────────────────────┬──────────────────────────────────────────────┐\n",
       "│                   the_geom                   │          st_geomfromtext(the_geom)           │\n",
       "│                   varchar                    │                   geometry                   │\n",
       "├──────────────────────────────────────────────┼──────────────────────────────────────────────┤\n",
       "│ POINT (-73.81167623024226 40.69138622900597) │ POINT (-73.81167623024226 40.69138622900597) │\n",
       "│ POINT (-73.81228577606385 40.69238458134393) │ POINT (-73.81228577606385 40.69238458134393) │\n",
       "│ POINT (-73.8122344420821 40.69312522070409)  │ POINT (-73.8122344420821 40.69312522070409)  │\n",
       "│ POINT (-73.8120597400255 40.6931738947353)   │ POINT (-73.8120597400255 40.6931738947353)   │\n",
       "│ POINT (-73.81310191327061 40.69279332424906) │ POINT (-73.81310191327061 40.69279332424906) │\n",
       "└──────────────────────────────────────────────┴──────────────────────────────────────────────┘"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# preview - convert string column to proper geometry type\n",
    "con.sql(\n",
    "    \"\"\"\n",
    "    SELECT the_geom, ST_GeomFromText(the_geom)\n",
    "    FROM green_infrastructure LIMIT 5\n",
    "    \"\"\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "7a4738cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "con.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4d5947b",
   "metadata": {},
   "source": [
    "# 8. Jupyter Notebooks and Querying Pandas Dataframes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "a109ad9b",
   "metadata": {},
   "outputs": [],
   "source": [
    "%reload_ext sql\n",
    "conn = duckdb.connect(config={\"allow_unsigned_extensions\": \"true\"})\n",
    "%sql conn --alias duckdb\n",
    "\n",
    "%config SqlMagic.autopandas = True\n",
    "%config SqlMagic.feedback = False\n",
    "%config SqlMagic.displaycon = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "0f3cfa14",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n"
     ]
    },
    {
     "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>letter</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>a</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  letter\n",
       "0      a"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql res << SELECT 'a' AS letter;\n",
    "\n",
    "print(type(res))\n",
    "res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "e217e58b",
   "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>i</th>\n",
       "      <th>j</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>one</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>two</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>three</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   i      j\n",
       "0  1    one\n",
       "1  2    two\n",
       "2  3  three"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dct = {\n",
    "    \"i\": [1, 2, 3],\n",
    "    \"j\": [\"one\", \"two\", \"three\"]\n",
    "}\n",
    "\n",
    "input_df = pd.DataFrame.from_dict(dct)\n",
    "\n",
    "input_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "543bcafc",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%sql output_df <<\n",
    "SELECT sum(i)AS total_i\n",
    "FROM input_df;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "867c98c2",
   "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>total_i</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   total_i\n",
       "0      6.0"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "output_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "118d3187",
   "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",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>the_geom</th>\n",
       "      <th>Asset_ID</th>\n",
       "      <th>GI_ID</th>\n",
       "      <th>DEP_Contra</th>\n",
       "      <th>DEP_Cont_1</th>\n",
       "      <th>Row_Onsite</th>\n",
       "      <th>Project_Na</th>\n",
       "      <th>Asset_Type</th>\n",
       "      <th>Status</th>\n",
       "      <th>Asset_X_Co</th>\n",
       "      <th>...</th>\n",
       "      <th>Asset_Leng</th>\n",
       "      <th>Asset_Widt</th>\n",
       "      <th>Asset_Area</th>\n",
       "      <th>GI_Feature</th>\n",
       "      <th>Tree_Latin</th>\n",
       "      <th>Tree_Commo</th>\n",
       "      <th>Constructi</th>\n",
       "      <th>Construc_1</th>\n",
       "      <th>Program_Ar</th>\n",
       "      <th>Status_Gro</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>POINT (-73.81167623024226 40.69138622900597)</td>\n",
       "      <td>94002</td>\n",
       "      <td>1A</td>\n",
       "      <td>GQJA03-02</td>\n",
       "      <td>2</td>\n",
       "      <td>ROW</td>\n",
       "      <td>DDC JAM-003 Phase 2</td>\n",
       "      <td>ROWB</td>\n",
       "      <td>Constructed (Full Maintenance)</td>\n",
       "      <td>1.036475e+06</td>\n",
       "      <td>...</td>\n",
       "      <td>17.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>Standard</td>\n",
       "      <td>Chionanthus retusus</td>\n",
       "      <td>Chinese Fringetree</td>\n",
       "      <td>GCJA03-2A</td>\n",
       "      <td>Package-1</td>\n",
       "      <td>Right of Way (ROW)</td>\n",
       "      <td>Constructed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>POINT (-73.81228577606385 40.69238458134393)</td>\n",
       "      <td>94012</td>\n",
       "      <td>GS6A</td>\n",
       "      <td>GQJA03-02</td>\n",
       "      <td>2</td>\n",
       "      <td>ROW</td>\n",
       "      <td>DDC JAM-003 Phase 2</td>\n",
       "      <td>ROWGS</td>\n",
       "      <td>Constructed (Full Maintenance)</td>\n",
       "      <td>1.036305e+06</td>\n",
       "      <td>...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>45.5</td>\n",
       "      <td>None</td>\n",
       "      <td>No Tree</td>\n",
       "      <td>N/A</td>\n",
       "      <td>GCJA03-2A</td>\n",
       "      <td>Package-1</td>\n",
       "      <td>Right of Way (ROW)</td>\n",
       "      <td>Constructed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>POINT (-73.8122344420821 40.69312522070409)</td>\n",
       "      <td>94017</td>\n",
       "      <td>GS8C</td>\n",
       "      <td>GQJA03-02</td>\n",
       "      <td>2</td>\n",
       "      <td>ROW</td>\n",
       "      <td>DDC JAM-003 Phase 2</td>\n",
       "      <td>ROWGS</td>\n",
       "      <td>Constructed (Full Maintenance)</td>\n",
       "      <td>1.036319e+06</td>\n",
       "      <td>...</td>\n",
       "      <td>20.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>70.0</td>\n",
       "      <td>None</td>\n",
       "      <td>No Tree</td>\n",
       "      <td>N/A</td>\n",
       "      <td>GCJA03-2A</td>\n",
       "      <td>Package-1</td>\n",
       "      <td>Right of Way (ROW)</td>\n",
       "      <td>Constructed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>POINT (-73.8120597400255 40.6931738947353)</td>\n",
       "      <td>94019</td>\n",
       "      <td>GS8E</td>\n",
       "      <td>GQJA03-02</td>\n",
       "      <td>2</td>\n",
       "      <td>ROW</td>\n",
       "      <td>DDC JAM-003 Phase 2</td>\n",
       "      <td>ROWGS</td>\n",
       "      <td>Constructed (Full Maintenance)</td>\n",
       "      <td>1.036368e+06</td>\n",
       "      <td>...</td>\n",
       "      <td>20.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>70.0</td>\n",
       "      <td>None</td>\n",
       "      <td>No Tree</td>\n",
       "      <td>N/A</td>\n",
       "      <td>GCJA03-2A</td>\n",
       "      <td>Package-1</td>\n",
       "      <td>Right of Way (ROW)</td>\n",
       "      <td>Constructed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>POINT (-73.81310191327061 40.69279332424906)</td>\n",
       "      <td>94021</td>\n",
       "      <td>10A</td>\n",
       "      <td>GQJA03-02</td>\n",
       "      <td>2</td>\n",
       "      <td>ROW</td>\n",
       "      <td>DDC JAM-003 Phase 2</td>\n",
       "      <td>ROWB</td>\n",
       "      <td>Constructed (Full Maintenance)</td>\n",
       "      <td>1.036079e+06</td>\n",
       "      <td>...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>Standard</td>\n",
       "      <td>Quercus palustris</td>\n",
       "      <td>Pin Oak</td>\n",
       "      <td>GCJA03-2A</td>\n",
       "      <td>Package-1</td>\n",
       "      <td>Right of Way (ROW)</td>\n",
       "      <td>Constructed</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                       the_geom  Asset_ID GI_ID DEP_Contra  \\\n",
       "0  POINT (-73.81167623024226 40.69138622900597)     94002    1A  GQJA03-02   \n",
       "1  POINT (-73.81228577606385 40.69238458134393)     94012  GS6A  GQJA03-02   \n",
       "2   POINT (-73.8122344420821 40.69312522070409)     94017  GS8C  GQJA03-02   \n",
       "3    POINT (-73.8120597400255 40.6931738947353)     94019  GS8E  GQJA03-02   \n",
       "4  POINT (-73.81310191327061 40.69279332424906)     94021   10A  GQJA03-02   \n",
       "\n",
       "  DEP_Cont_1 Row_Onsite           Project_Na Asset_Type  \\\n",
       "0          2        ROW  DDC JAM-003 Phase 2       ROWB   \n",
       "1          2        ROW  DDC JAM-003 Phase 2      ROWGS   \n",
       "2          2        ROW  DDC JAM-003 Phase 2      ROWGS   \n",
       "3          2        ROW  DDC JAM-003 Phase 2      ROWGS   \n",
       "4          2        ROW  DDC JAM-003 Phase 2       ROWB   \n",
       "\n",
       "                           Status    Asset_X_Co  ...  Asset_Leng Asset_Widt  \\\n",
       "0  Constructed (Full Maintenance)  1.036475e+06  ...        17.0        5.0   \n",
       "1  Constructed (Full Maintenance)  1.036305e+06  ...        13.0        3.5   \n",
       "2  Constructed (Full Maintenance)  1.036319e+06  ...        20.0        3.5   \n",
       "3  Constructed (Full Maintenance)  1.036368e+06  ...        20.0        3.5   \n",
       "4  Constructed (Full Maintenance)  1.036079e+06  ...        13.0        4.0   \n",
       "\n",
       "  Asset_Area GI_Feature           Tree_Latin          Tree_Commo  Constructi  \\\n",
       "0       85.0   Standard  Chionanthus retusus  Chinese Fringetree   GCJA03-2A   \n",
       "1       45.5       None              No Tree                 N/A   GCJA03-2A   \n",
       "2       70.0       None              No Tree                 N/A   GCJA03-2A   \n",
       "3       70.0       None              No Tree                 N/A   GCJA03-2A   \n",
       "4       52.0   Standard    Quercus palustris             Pin Oak   GCJA03-2A   \n",
       "\n",
       "   Construc_1          Program_Ar   Status_Gro  \n",
       "0   Package-1  Right of Way (ROW)  Constructed  \n",
       "1   Package-1  Right of Way (ROW)  Constructed  \n",
       "2   Package-1  Right of Way (ROW)  Constructed  \n",
       "3   Package-1  Right of Way (ROW)  Constructed  \n",
       "4   Package-1  Right of Way (ROW)  Constructed  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql\n",
    "SELECT *\n",
    "FROM \"data/green_infrastructure.csv\"\n",
    "LIMIT 5;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "cc4d81ac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\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>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>14346</td>\n",
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       "   count\n",
       "0  14346"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql\n",
    "SELECT COUNT(*) AS count\n",
    "FROM \"data/green_infrastructure.csv\";"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "1e007d71",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\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>the_geom</th>\n",
       "      <th>Asset_ID</th>\n",
       "      <th>GI_ID</th>\n",
       "      <th>DEP_Contra</th>\n",
       "      <th>DEP_Cont_1</th>\n",
       "      <th>Row_Onsite</th>\n",
       "      <th>Project_Na</th>\n",
       "      <th>Asset_Type</th>\n",
       "      <th>Status</th>\n",
       "      <th>Asset_X_Co</th>\n",
       "      <th>...</th>\n",
       "      <th>Asset_Leng</th>\n",
       "      <th>Asset_Widt</th>\n",
       "      <th>Asset_Area</th>\n",
       "      <th>GI_Feature</th>\n",
       "      <th>Tree_Latin</th>\n",
       "      <th>Tree_Commo</th>\n",
       "      <th>Constructi</th>\n",
       "      <th>Construc_1</th>\n",
       "      <th>Program_Ar</th>\n",
       "      <th>Status_Gro</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>POINT (-74.00229569924448 40.757951817712886)</td>\n",
       "      <td>138087</td>\n",
       "      <td>JCGR-1</td>\n",
       "      <td>PRIVATE_GR</td>\n",
       "      <td>OA</td>\n",
       "      <td>Onsite</td>\n",
       "      <td>Javits Center Green Roof</td>\n",
       "      <td>Green Roof</td>\n",
       "      <td>Constructed</td>\n",
       "      <td>9.836140e+05</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>435000.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>External</td>\n",
       "      <td>Constructed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>POINT (-74.19545588457119 40.561950486557514)</td>\n",
       "      <td>187241</td>\n",
       "      <td>Freshkills1</td>\n",
       "      <td>RG-12450-506M</td>\n",
       "      <td>1</td>\n",
       "      <td>Onsite</td>\n",
       "      <td>Freshkills Park Owl Hollow Fields Construction</td>\n",
       "      <td>Synthetic Turf Field Storage Layer</td>\n",
       "      <td>Constructed</td>\n",
       "      <td>9.299417e+05</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>303481.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>External</td>\n",
       "      <td>Constructed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>POINT (-73.90532182350593 40.72771532765737)</td>\n",
       "      <td>187205</td>\n",
       "      <td>FrankP1</td>\n",
       "      <td>Q131-115M</td>\n",
       "      <td>1</td>\n",
       "      <td>Onsite</td>\n",
       "      <td>Frank Principe Park Ballfields Reconstruction</td>\n",
       "      <td>Synthetic Turf Field Storage Layer</td>\n",
       "      <td>Constructed</td>\n",
       "      <td>1.010492e+06</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>156052.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>External</td>\n",
       "      <td>Constructed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>POINT (-74.00553985329056 40.67329044837725)</td>\n",
       "      <td>187266</td>\n",
       "      <td>SWPS21-113-D01</td>\n",
       "      <td>B126-116M</td>\n",
       "      <td>1</td>\n",
       "      <td>Onsite</td>\n",
       "      <td>Red Hook Recreation Area Remediation and Recon...</td>\n",
       "      <td>Synthetic Turf Field Storage Layer</td>\n",
       "      <td>Constructed</td>\n",
       "      <td>9.827133e+05</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>145471.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>External</td>\n",
       "      <td>Constructed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>POINT (-73.87308060078496 40.67026320022855)</td>\n",
       "      <td>187191</td>\n",
       "      <td>B103-01STa</td>\n",
       "      <td>B103-116M</td>\n",
       "      <td>1</td>\n",
       "      <td>Onsite</td>\n",
       "      <td>Cypress Hills PG - Synthetic Turf Field Constr...</td>\n",
       "      <td>Synthetic Turf Field Storage Layer</td>\n",
       "      <td>Constructed</td>\n",
       "      <td>1.019458e+06</td>\n",
       "      <td>...</td>\n",
       "      <td>439.0</td>\n",
       "      <td>296.0</td>\n",
       "      <td>130383.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>External</td>\n",
       "      <td>Constructed</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        the_geom  Asset_ID           GI_ID  \\\n",
       "0  POINT (-74.00229569924448 40.757951817712886)    138087          JCGR-1   \n",
       "1  POINT (-74.19545588457119 40.561950486557514)    187241     Freshkills1   \n",
       "2   POINT (-73.90532182350593 40.72771532765737)    187205         FrankP1   \n",
       "3   POINT (-74.00553985329056 40.67329044837725)    187266  SWPS21-113-D01   \n",
       "4   POINT (-73.87308060078496 40.67026320022855)    187191      B103-01STa   \n",
       "\n",
       "      DEP_Contra DEP_Cont_1 Row_Onsite  \\\n",
       "0     PRIVATE_GR         OA     Onsite   \n",
       "1  RG-12450-506M          1     Onsite   \n",
       "2      Q131-115M          1     Onsite   \n",
       "3      B126-116M          1     Onsite   \n",
       "4      B103-116M          1     Onsite   \n",
       "\n",
       "                                          Project_Na  \\\n",
       "0                           Javits Center Green Roof   \n",
       "1     Freshkills Park Owl Hollow Fields Construction   \n",
       "2      Frank Principe Park Ballfields Reconstruction   \n",
       "3  Red Hook Recreation Area Remediation and Recon...   \n",
       "4  Cypress Hills PG - Synthetic Turf Field Constr...   \n",
       "\n",
       "                           Asset_Type       Status    Asset_X_Co  ...  \\\n",
       "0                          Green Roof  Constructed  9.836140e+05  ...   \n",
       "1  Synthetic Turf Field Storage Layer  Constructed  9.299417e+05  ...   \n",
       "2  Synthetic Turf Field Storage Layer  Constructed  1.010492e+06  ...   \n",
       "3  Synthetic Turf Field Storage Layer  Constructed  9.827133e+05  ...   \n",
       "4  Synthetic Turf Field Storage Layer  Constructed  1.019458e+06  ...   \n",
       "\n",
       "   Asset_Leng Asset_Widt Asset_Area GI_Feature Tree_Latin  Tree_Commo  \\\n",
       "0         0.0        0.0   435000.0       None       None        None   \n",
       "1         0.0        0.0   303481.0       None       None        None   \n",
       "2         0.0        0.0   156052.0       None       None        None   \n",
       "3         0.0        0.0   145471.0       None       None        None   \n",
       "4       439.0      296.0   130383.0       None       None        None   \n",
       "\n",
       "   Constructi  Construc_1  Program_Ar   Status_Gro  \n",
       "0        None        None    External  Constructed  \n",
       "1        None        None    External  Constructed  \n",
       "2        None        None    External  Constructed  \n",
       "3        None        None    External  Constructed  \n",
       "4        None        None    External  Constructed  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql\n",
    "SELECT *\n",
    "FROM \"data/green_infrastructure.csv\"\n",
    "WHERE Asset_Area > 100000\n",
    "ORDER BY Asset_Area DESC\n",
    "LIMIT 5;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "44943d4b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<span style=\"None\">Skipping execution...</span>"
      ],
      "text/plain": [
       "Skipping execution..."
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%sql --save green_infra --no-execute\n",
    "SELECT *\n",
    "FROM \"data/green_infrastructure.csv\";"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "dcce7244",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: title={'center': \"'Asset_Area' from 'green_infra'\"}, ylabel='Asset_Area'>"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%sqlplot boxplot -t green_infra -c Asset_Area --with green_infra"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "c4aab97f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: title={'center': \"'Asset_Area' from 'green_infra'\"}, xlabel='Asset_Area', ylabel='Count'>"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%sqlplot histogram -t green_infra -c Asset_Area --with green_infra"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "29e016a7",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}