Test Install.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "import matplotlib\n",
    "matplotlib.use('TkAgg')\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "print(matplotlib.get_backend())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "print(sys.version)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "print(pd.__version__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "import geopandas as gpd\n",
    "print(gpd.__version__)\n",
    "print(matplotlib.get_backend())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "import pysal as ps\n",
    "print(ps.__version__)\n",
    "print(matplotlib.get_backend())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "import folium as flm\n",
    "print(flm.__version__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import gdal\n",
    "import osgeo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import geopandas as gpd\n",
    "import urllib\n",
    "\n",
    "fn = \"Greenspace.gpkg\"\n",
    "if not (os.path.exists(fn) and os.path.isfile(fn)):\n",
    "    url = 'https://github.com/kingsgeocomp/geocomputation/raw/master/data/Test/Greenspace.gpkg'\n",
    "    urllib.request.urlretrieve(url, fn)\n",
    "\n",
    "greenspace = gpd.read_file(fn)\n",
    "greenspace.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import urllib\n",
    "import pandas as pd\n",
    "import geopandas as gpd\n",
    "from shapely.geometry import Point\n",
    "\n",
    "df = pd.read_csv(\n",
    "        'http://data.insideairbnb.com/the-netherlands/north-holland/amsterdam/2017-04-02/visualisations/listings.csv',\n",
    "        low_memory=False)\n",
    "df.price.plot.hist()\n",
    "plt.title('Price per Night')\n",
    "plt.show()\n",
    "\n",
    "geometry = [Point(xy) for xy in zip(df.longitude, df.latitude)]\n",
    "df.drop(['longitude', 'latitude'], axis=1, inplace=True)\n",
    "crs = {'init': 'epsg:4326'}\n",
    "airbnb = gpd.GeoDataFrame(df, crs=crs, geometry=geometry)\n",
    "airbnb.plot()\n",
    "plt.title('Locations')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#import sompy"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Geocomp 2019 (Alt 2.0.0)",
   "language": "python",
   "name": "gsa2019alt2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}