{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import psycopg2\n",
    "import geopandas as gpd\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "conn = psycopg2.connect( \"dbname=osm_local\")\n",
    "curs = conn.cursor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "tSQL = '''select osm_id, \n",
    "  ST_IsSimple(way) as simple,\n",
    "  ST_NPoints(way) as pts_cnt,\n",
    "  (building is not Null) as bldg, \n",
    "  way as geom from planet_osm_polygon\n",
    "  WHERE ST_NPoints(way) > 7\n",
    "'''\n",
    "\n",
    "res_df = gpd.read_postgis( tSQL, conn)\n",
    "#print( res_df.shape[0],\" rows of \",res_df.shape[1],\" columns\")\n",
    "#res_df.dtypes\n",
    "res_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# make a subset dataframe via a filter expression\n",
    "#  boolean column 'bldg' only keep True entries\n",
    "res_df_A = res_df[ res_df['bldg'] ]\n",
    "\n",
    "#  example test -- exactly 24 poly points\n",
    "res_df_A33 = res_df_A[ res_df_A['pts_cnt'] == 24]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "res_df_A33.plot( figsize=(12,20) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "res_df_A.plot( column='pts_cnt', cmap=None, figsize=(12,20) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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