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@kjordahl
Created November 9, 2013 17:02
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Working with GeoSeries in GeoPandas
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{
"metadata": {
"name": ""
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Working with GeoSeries"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from geopandas import GeoSeries\n",
"from shapely.geometry import Polygon, Point, LineString\n",
"pylab.rcParams['savefig.dpi'] = 100"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 1
},
{
"cell_type": "heading",
"level": 4,
"metadata": {},
"source": [
"Create some geometries with Shapely:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"poly1 = Polygon([(0, 0), (1, 0), (1, 1)])\n",
"poly2 = Polygon([(2, 0), (3, 0), (3, 1), (2, 1)])\n",
"circle = Point([(1.5, 0.5)]).buffer(0.5)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 2
},
{
"cell_type": "heading",
"level": 4,
"metadata": {},
"source": [
"Create a GeoSeries from a sequence of geometries:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"g = GeoSeries([poly1, circle, poly2])\n",
"print g"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"0 POLYGON ((0.0000000000000000 0.000000000000000...\n",
"1 POLYGON ((2.0000000000000000 0.500000000000000...\n",
"2 POLYGON ((2.0000000000000000 0.000000000000000...\n",
"dtype: object\n"
]
}
],
"prompt_number": 3
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"g.plot()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 4,
"text": [
"<matplotlib.axes.AxesSubplot at 0x105a5b950>"
]
},
{
"metadata": {},
"output_type": "display_data",
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6fRVk9Ey9HKSkpGD79u1QBnqgr2dzseOQCEYFKDCwx6uI/uornD59Wuw4RHqn9SLFkJAQ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\n",
"text": [
"<matplotlib.figure.Figure at 0x105a5bd90>"
]
}
],
"prompt_number": 4
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now we create a new series that has "
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"big_circle = Point([1.5, 1.0]).buffer(0.9)\n",
"g.plot()\n",
"GeoSeries([big_circle]).plot()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 5,
"text": [
"<matplotlib.axes.AxesSubplot at 0x10bf238d0>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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DoOpYEDRcWloa9PT0RMcgIjViYmIC4P9PgibVVKyCcPbsWXTq1Am2traQSCQI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\nQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x105a5bb50>"
]
}
],
"prompt_number": 5
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"g.difference(big_circle)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 6,
"text": [
"0 POLYGON ((1.0000000000000000 0.251669431327654...\n",
"1 POLYGON ((1.8929164090542658 0.191447836648926...\n",
"2 POLYGON ((2.3999999999999999 1.000000000000000...\n",
"dtype: object"
]
}
],
"prompt_number": 6
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"g.difference(big_circle).plot()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 7,
"text": [
"<matplotlib.axes.AxesSubplot at 0x10bcf8690>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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3x+TJk/HTTz9BpVKJHZcAqFQq7N27F2NefBHW1u0QHh4OVeltrHvzBeTEhuP7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\nICIiohpYEIiIiKgGFgQiIiKq4f8BMg2cHOms+lcAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x10bf44050>"
]
}
],
"prompt_number": 7
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"pts = GeoSeries([Point([0,0]), LineString([[1.5, 1], [1.5, 1.5]]), Point([3,0])])\n",
"c = pts.buffer(0.5)\n",
"g.plot()\n",
"c.plot()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 8,
"text": [
"<matplotlib.axes.AxesSubplot at 0x10bcf4250>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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suJ+mYfRvl5SOlOfN2RXP1TsPKV7YgR+mfU9SUpLSkYQwWFImRJ5iiEUCYO7c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\n+Pr6Yt26ddi5cyf279sH7zO/YkP0Wdh2745ZQ4ZiurU1NN9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"text": [
"<matplotlib.figure.Figure at 0x10bf77810>"
]
}
],
"prompt_number": 8
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"g.union(c).plot()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 9,
"text": [
"<matplotlib.axes.AxesSubplot at 0x10bcf1fd0>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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r8nDgwAFEnDqFq1evIu/FC0gkElgYGsLa2BgVzM1RpUwZ1LC0QgVzc5iWNIB5\nyVIw0deHtvb/f4KVyWTILSjA05wcpOfkIDUzE9dSU3Hj0UPcffIE9589w8PMTOQVFEBLSwsVbG1R\nr359tGnTBl27doWFhWrOuFi8igRQ5pefUVJfG+l/afbRtuLCpucfSHmahaioKNFRSMFkMhlycnLe\nHClOSUnB7du3cffuXSQnJ+PRo0d4+vQppFIpdHR0ULVqVTRq1AjffvutypcLQPF/Q5V2mmPs2LHo\n2rUrDA0N0bdvX0ydOhV5eXkYOnQoAMDX1xfJycnYtGkTAGDx4sWwt7dHjRo1kJiYiC1btuDGjRtY\nunSpsiIqhUwmw/79++Hv74/joaHIzslBCW1tVLYog561a6NNtWpoXbUaSunpfdZ2JRIJSunpoZSe\nHsqbmaGWjQ3aVq/+n31fuH8fB65cRsTtOwgJDsaOHTvg5eWFWl9/jd4eHhg2bBhMTEwU+ZS/WHEr\nEgCgpaWFQhkH7GmKQqkMWlo81KSJJBIJDA0NYWj4ak6YGjVq4Jtvvnlrnfz8fERFReHUqVO4ePEi\nNmzYgDVr1kBPTw+NGzfGoEGD4O7uDh0dHRFPoUgprUx07NgRmzdvxm+//YYdO3bA2dkZ4eHhbw6/\np6amIikp6c36BQUFGD9+PO7fvw87Ozt0794d586d+88VIarq7NmzWLlyJQ4eOIC0J09gZGCA1lWq\noGut2mhXvfpnl4cvIZFI4GprC1dbWwCvykVMUhL2xsXhwNUrmDBhAqZOmYJGjRtjwIAB6Nu3r7Bf\n8uJYJABAoqUFGcuExiiUsUwUZ7q6umjSpAmaNGkC4FW5OHv2LI4ePYrIyEiEhobC29sbbdu2xbBh\nw/5TRjSJ0k5zKJuqnObYuXMnZs+ejYsXL0K3RAk0tLNH37p10b12beiUUJnxrQCAC/fvY21EBA5d\nv4a0589R2twcPwwdikmTJr1p30WhuBYJALCa6AvpSynyDk8WHYUUwKTTfGTnFeLMmTOio5CKkclk\nCA8PR1BQEM6fP4+8vDxUrlwZP//8MwYPHix8DiVF/w3ldU1fQCaTYc2aNahSuTLc3d3x6G4iJrt9\ni9vTZyB42DD0cnVVuSIBAM7lymFFr16InzIVAQMHoZKRMebPnw9rKyt4e3t/dHZSRSjORQJ4dWRC\nyiMTGkMqfckjE/ROEokELVq0wKJFi3D06FGMGzcOubm5GDp0KGxtbbFgwQIUFGjOAF6Wic/k7+8P\nW1tbeHkXRi/xAAAgAElEQVR5oTAjAwu7dcfVSZMwvnVrGKv4gJvXJBIJ2js64u8ff0ToyJ9Qx9oa\nfn5+sLW1xaBBg5CZmamU/Rb3IgEAJSQSFEplyHuhOW8ixdmLgkKWCfooPT099OrVC3v27MGsWbOg\nr6+Pn3/+GVZWVpg/f75GXF7MMvGJYmNj4erqiqFDh6JUQQHW9e2HC79MwJDGjd+66kLduNraYt9Q\nL5wZNw6tK1fG5k2bYG9nh1WrVin0F5xF4hXdf45Yxd1+KDgJyetpZi4KpTK1fv1T0ZJIJHBzc0Ng\nYCCWLFmCsmXLwtfXF9WrV0dYWJjoeHJhmfiIrKwsDB48GHXr1MGta9cwp1NnnB03Ht85Ows/56VI\nVct+hW2eA3FkhA8s9fTh7e0NFxcXREdHy71tFon/97pMxN5OFZyE5HX+ZjIAaNT7ABWdRo0aYfPm\nzZg2bRrS0tLQsmVLdO/evUhONysDXwUfsHv3btjb2WHjhg3oXPNrxE3whU/z5hr95lGnQgVEjBmD\nX7t0RWJ8POrXr4+hQ4d+8bk9Fom36WhrQ0tLC1fuqucbBv2/i/8cXeKRCZJHx44dsXfvXnTr1g1/\n/fUXKlWqhFWrVomO9dk096+iHKRSKYYOHYqePXvCWEsLId4jsKF/f5iXKiU6WpGQSCQY1rQpYif4\nokvNr+Hv7w+n2rVx+/btz9oOi8R/aWlpQVdHB/H3n4qOQnK6du8xtP8ph0TyKFmyJHx9fbF161ZY\nW1vD29sb3bt3R25uruhon4xl4n/cuXMHtWvXhr+/P3o6O+Ps2HFoYG8vOpYQZiVLYkP//vDz8MC9\nhAQ41a6NLVu2fNJjWSTeT09fH7eS00XHIDndSHqCkgYGomOQBqlUqRI2b94MDw8PBAUFoVq1arhw\n4YLoWJ+EZeJftm3bhtq1aiHx9m2s7u0B/z59oVsMZi77mN6udXBq9GiUNzLC999/jz59+nzwtAeL\nxIeZmJggISUdmdl5oqPQF5LJZLiU8Bhm5uaio5CGkUgkGDNmDP744w9kZmaiYcOG+OOPP0TH+iiW\niX/MnDkT/fv3RzkjI5waPRoedeqIjqRS7EtbIGL0GAxs0ACBgYFo3KgRsrKy/rMei8THlS5dGlKZ\nDPtP3xQdhb7Q+RspyMzOg5WVlegopKEaN26MwMBAVK1aFWPHjsXw4cNV+hLSYl8mZDIZvL29MW3a\nNLSq4oCTP42CfWnVvCmWaNra2lj8XU/80b0HLly4ABdnZ6Sm/v9VCSwSn8bU1BQlSxrg8LnPG4NC\nqiMo8jokWlqfdRdkos9VunRp+Pv7o3379li9ejV69OgBqVQqOtY7FesyIZVK0aNHD6xatQq9XF2x\na8gQntb4BIMaNsTGfv1w/949uLq44ObNmywSn0FLSws1HWvizPVk0VHoC4XHJcK2gq3K3xmS1J9E\nIsGMGTPQv39/7Nu3D82bN1fJgZnFtkzk5+ejRYsW2LdvH35q0QJrPPpo9CWfitbp61rYO+QHZGdk\noGrVqiwSn6lJ06a4/eApx02oIZlMhosJj1GvXn3RUagYGTlyJEaPHo0zZ86gbt26SE9XrUHcxfKv\np0wmQ/v27REZEYE5nTpjZsdOoiOppYYVK2LfD69uKW9qYMAi8Rnc3d0hlcmwPiRWdBT6TPtPxyMz\nOw+dO3cWHYWKmT59+mD69Om4efMmWrZsibw81fkwUizLRL9+/XDs2DFMbucGn+bNRcdRay62trg9\nfQYSZ80WHUWt1K9fHxVsbfHnscuio9Bn8j8QA2NjI7i7u4uOQsWQm5sbJk6ciEuXLqF9+/YqMyiz\n2JWJMWPGICAgAF6Nm2Bs69ai42gEiyK8fbkm6da9O2LiU/AgTTk3ViPFy3tRgOOxd9G2bTvocHwV\nCdKxY0d4e3vj+PHj6NOnj+g4AIpZmfj999+xaNEidK1VC7916yY6DhVzPj4+kL18iZVB50RHoU+0\n+chFZOflw8vLS3QUKuYGDBgADw8PbN++HT/99JPoOMWnTBw9ehQTJkxAk0qVsL5vP9FxiFCpUiXU\nrOmIXeHXRUehT7Tl74uwsrREq1atREchwpgxY9CmTRssXboUGzduFJqlWJSJtLQ09PHwgJWxMXYM\nGswb85DK8PDog5tJaYi4fE90FPqIhJR0nLl2H527dOGVX6QyZs2ahcqVK8PHxwfx8fHCcmj8K0Im\nk6Fbt254lpGBzf2/Ryk9PdGRiN4YNWoUTIyNMWXDcdFR6CMmrw+FRFsbU6ZMER2F6A1tbW0sXLgQ\nANClS5cvvsOzvDS+TMyYMQOnTp3CxLbt4GprKzoO0VsMDAwwwNMTYXGJuJzwSHQceo/H6dnYc/IG\nOnXqDBsbG9FxiN5ibW2NCRMm4Nq1axg2bJiQDBpdJiIiIjBv7ly0dHDAaJ7jJBU1bdo06OvpY9La\nY6Kj0HtM3XgcBVIp5s6dKzoK0Tu5ubmhQ4cO2LBhA3bu3Fnk+9fYMiGTyTBk8GAY6+tjU//vRcch\nei9zc3P06t0bIedu425qhug49D8ys/Ow9dhlfPNNazg4OIiOQ/RekyZNgo2NDX788ccin9BKY8vE\nggULcP3GDUxv3x4mBgai4xB90KxZs6AlkWDsqsOio9D/mLz+OLJz8zFnzhzRUYg+SEdHBxMmTMCj\nR48wbty4It23RpaJtLQ0zJ0zB662tvie8+eTGrCxscGAAZ7YF3ED4XGJouPQP+LvP8Ga/TH41s0N\nderUER2H6KPq16+PJk2awN/fH9evF91l5xpZJoYNG4acnBws78npbkl9LFq0CKXNS8Nr0X6VmSK3\nuBvyezBK6Ohijb+/6ChEn2zixIkoUaIEBg8eXGT71LgycebMGezduxd969RBDSsr0XGIPlmpUqUw\n/9dfcf1eGhbuOC06TrG34/gVhF+8hzFjx/IKDlIrFhYW6NevHyIjI7Fjx44i2afGlYmJvr4w0tPD\nvM5dREch+myDBg1C3bp1MXvbKaRlZIuOU2zlvSjA6JVHYG9vh2nTpomOQ/TZBg0ahK+++gozZswo\nkv1pVJm4ePEiwsLD0adOHU5ORWpr7dq1yH1RiL5z94iOUmwNX3wAKU+fY+XKVZwxl9SStrY2PDw8\ncPXqVRw4cEDp+9OoMjFp0iTolyiBX9q0FR2F6IvVqlULv0yYgCPn72BBYIToOMVOYOhlbDpyEQMG\nDICbm5voOERfzN3dHebm5kVydEJjykRCQgIOhYSgW+3aMCtZUnQcIrnMmDEDTRo3xpQNJ3D+RrLo\nOMXG3dQMeC06gKoODlizZo3oOERy0dHRQbdu3XDu3DlERCj3g4nGlIkpU6ZAoqWFyW7fio5CJDeJ\nRII9e/fCyMQEPabvRHZuvuhIGk8qlaHrlO2QQoKg4GDo6OiIjkQkN09PTxgaGir9njIaUSYKCgoQ\nHBSEVg4OsDYxER2HSCHKlCmDrVu34UFaJnrP2iU6jsYbseQg4m6nYtmy5ZzpkjSGvr4+2rZti5Mn\nT+Lx48dK249GlInAwEA8z8rCoIYNRUchUqh27drh559/wf4z8fBZclB0HI01b9tJ+O2PRr++fTFw\n4EDRcYgUqnfv3igsLMSqVauUtg+NKBMbNmyAhZER2lStJjoKkcLNnTsXfTw8sCLoHOZsDRcdR+Ns\nPBSLyRuOo2WLFti0ebPoOEQKZ29vDzs7O2zfvl1p+1D7MvH8+XNEnDqFdtWqQSJR+6dD9E5btm5F\n69atMXXjCaw9ECM6jsY4cPomvP7Yj1q1auFgSAjfQ0hjffPNN7h69arSpthW+1fO3r17kV9QgB8a\nNxEdhUhpJBIJDhw4AGcnZ3gvOYjgiBuiI6m9M1fvo9es3ShX3hYnToRBX19fdCQipfnuu++gra2N\nFStWKGX7al8mjh07hgrmpeFcrpzoKERKpauri9Djx2Fvb4+eM3dhy5E40ZHU1qGoW2g9fguMTM1w\nIiwMJhy4TRrOwsIC1apVU9oEVmpfJm7duoUG9naiYxAVCWNjY5w5G4Xq1Wtg4G9B+H17pOhIamfL\nkTh0mbIdZS2tcfZsFMqXLy86ElGRqFu3Lu7evYu0tDSFb1vty0ReXh6+cagqOgZRkTEzM8OZs2fR\npElTjPf7G2NXHRYdSW38vj0SA38LQvXqNRAdHQNbW1vRkYiKTLNmzfDy5UsEBwcrfNtqXyYkWlpw\nq1FDdAyiIqWvr49joaHo2bMn/th5Br1m7kRBgVR0LJUlk8kwclkIxvv9jSZNmuLM2bMwMzMTHYuo\nSDk6OqJUqVI4cuSIwret9mXC2sQEJgYGomMQFTltbW3s2LEDI0eOxM6wa/h6yGpcv6f4w5fqLjkt\nEw181mPZ3ii49+yJY6GhHGxJxZJEIkGVKlUQFRWl+G0rfItFrLqVlegIREItWbIEgYGBSHn2AnWG\n+fPS0X8JjriBmoNX49LdNCxbtgzbd+zgXUCpWHN2dsbdu3eRnp6u0O2qfZn42pJlgsjd3R1xcRdR\n2aEaflj4F9xn7ETeiwLRsYSRSmUYseQAuk3bDvMyVjh7Ngo+Pj6iYxEJ5+rqipcvX+LSpUsK3a7a\nl4kqZcuKjkCkEuzs7BAdE4MRI0Zg98nrqNhvGQJDL4uOVeQOn7sFhwHLsTLoPHr2dMflK1dQq1Yt\n0bGIVEK1aq9mio6Pj1fodtW+TFQuU0Z0BCKVoa2tjeXLlyMkJAQlTcrAY/ZuNB25ATeTNH8sRXJa\nJjr6/gm3X7YhV6aHgIAABAYGcnwE0b+YmJjA0NAQCQkJCt2u2pcJ3RIlREcgUjlt27bFjZs3MWPG\nDFxISMPXQ/zw49KDGnkr84ICKaZtPA6H71fg6IVEjBw5EncSEtC7d2/R0YhUkoWFBe7fv6/Qbap9\nmSCid9PW1sbUqVNx82Y82rZzw4qg87BxX4SfloXgaWau6Hhyy87Nx5T1x2HTaxFmbg6Ha936uHT5\nMpYsWcKjEUQfYGlpiYcPHyp0mywTRBrO2toaf/31FyIiIuBaryGWB51H+V6LMPDXfXiQlik63md7\nmpmLkctCYO2+CLO3hsO+Sg0cPHgQYeHhqFKliuh4RCqvfPnyePr0qUK3qdQysW3bNjg5OcHU1BQt\nW7bExYsXP7h+bGwsmjdvDlNTU7i4uCAwMFCZ8YiKlYYNG+JYaCji4uLQuq0bth27gop9lsLt563Y\neeIKpFKZ6IjvJZPJEHI2Ht2mbEf5XouwIug86tRriMjISJyNisK3334rOiKR2jA1NUVhYaFCt6m0\nMvHXX39hwIABcHV1RVBQEAoLC9GsWTM8fvz4neunpKSgadOmAIDg4GA4OTmhX79+CAkJUVZEomKp\nZs2aCAoOxo2bN9G7T19E3X4C95m7UKb77+gzezfC4xJFR3zjQnwKhiwIhlXPRWjv+yeOxiXBrUMn\nxMXF4VhoKBo2bCg6IpHaKVWqlMK3qbTRiwsXLoS7uzvWrVsHADh58iSsrKzg5+eHyZMn/2d9Pz8/\nGBsbIywsDMCrOcRzcnKwcOFCfuogUgJ7e3ts2rQJUqkU+/btw7q1a7HvxAkEhF6GVWkj1HWwwjcu\n9ujapDpsvyqau2o+TM9C0Kkb+Dv6NqJupODewwzo6uigYcOG+HXgQPTp0we6urpFkoVIUxkaGip8\nm0orE1FRUZgxY8Zby5ycnBAZ+e67HJ45cwZOTk7/WX/mzJnKikhEeDVQs0ePHujRowdyc3Oxfv16\n7Nu3D5EXYhB8+iZ+WnEY1hbGcKlsCecqlvjavixcHaxhZ2kCieTLD24mPXqG6JvJuHjnES7efojz\n8a/Kw8uXgImxMWo7OcF7dHsMHTqU99EgUiC1KRNPnjxBXl7ef8pB7dq133vaIjk5GZ06dXprmZOT\nE/Ly8pCRkQFTU1NlRCUVcfDKFVx88EB0DKV7lqvaV1EYGBhgxIgRGDFiBADgypUrCAoKwvHjx3Em\n9gL2n7n5Zl093RKwNDeEtbkhjErqopS+LowMdGFUUg9GJXUhkWghM/sFnufkIyv3n6+8fKQ8zUbq\nkyzkvPj/y1TNTE3wda3a+P6H5ujSpQucnZ3lKipFKT8/H/7+/qJjKFVKSgru3buHtWvXio5CCmBk\nZKTwbar9JA2+Qfv+c6Ov75yd8Z2zi6BE9CWGbQ/Es5wc0TGKRIUKFURH+GSOjo5wdHTExIkTAQBZ\nWVmIiYlBXFwcrl69ivj4eCQ/eICUxznIzX2OvBcv8CLvBV7kvyoKuro60NPVg76+PvT19VGypAFs\nHSqhVeXKqF69OmrXrg0XFxe1PfJQsWJF5OXlYc2aNaKjFImCggLo6OiIjkGf6fDhwzh8+PCbf2dm\nKv4qLqWUidKlS0NfXx+xsbFo06bNm+WxsbEoV67cOx9jY2ODCxcuvLUsNjYW+vr6HzwqMa9LVzi9\nZ5ukPnLz8+Hj44OFCxeKjqJ06nzO39DQEM2aNUOzZs0+uJ5M9urKEHU5uvClZs6c+c4xYJrmjz/+\ngK+vLzIzM1G6dGnRcegztWvXDu3atXvz74iICIwaNUqh+1DakYn69ev/pxzExcW992Y7DRo0gJ+f\n31vLYmNj0bhxY2VFJBUhlUqRX1gIU1NTtf5DS/9P00vEvxWH39nXBYJlQjNkZWUpfJtKe8WPHTsW\nO3bswNChQxEWFobmzZsjLy8PQ4cOBQD4+vpiwIABb9b38vJCVlYWWrRogbCwMAwZMgS7du3C2LFj\nlRWRVERGXh4AwNjYWHASInqX10eHnz9/LjgJKYIyfo5KKxMdO3bE5s2bERUVhS5dukAikSA8PBxl\n/rkxV2pqKpKSkt6sb2lpifDwcABAly5dEBMTg23btsHNzU1ZEUlFpOdkA3h1AxoiUj2vx7Qo41w7\nFb3s7GyFb1OpAzD79OmDPn36vPN7GzZs+M8yJycnnDhxQpmRSAVl5Ly6woFHJohUE49MaBZllIni\nc2KTVNbdf+aIV6erHIiKEzs7OwCvjiiT+nv06BEM/ucqSHmxTJBwV1NToKWl9Z95SYhINVhYWMDI\nyAh3794VHYUU4MGDB2+GHCgKywQJF//oMUqbmyu8KROR4lhbW+P+/fuiY5ACPHz4EFZWVgrdptqX\nideD90h9JT59AhvOFUKk0ipUqIBHjx6JjkFykslkePLkCWxtbRW6XbUvEzce8pdb3SU/fw57e3vR\nMYjoA6pUqYInT568mZCM1NODBw+Qn5+PihUrKnS7al8mbrIpq7XsFy/wJCsLDg4OoqMQ0Qc4Ojqi\noKCA4ybU3JUrVwC8KoeKpPZlojjcHEqTHbl2DTKZDN98843oKET0Aa/n/Dl58qTgJCSPqKgo6Ovr\n4+uvv1bodtW+TMSnPRYdgeRw9MYN6Ovpo2XLlqKjENEH2Nvbw9LSEufPnxcdheRw+fJl1KhRAyVK\nKHaaKbUvExk5OYjnqQ61FXUvETUca/BOhERqwNXVFTdv3vz4iqSScnJycO/ePTRp0kTh21b7MgEA\n+y9fFh2BvkBWXh7upKUp5RebiBSvVatWePr0KRITE0VHoS8QEREBqVSKDh06KHzbal8mSpubI/xW\nvOgY9AWOXL+OQiX9YhOR4nXr1g0AeNsDNXX69Gno6yvntLLal4maX3+Nc0lJKCgsFB2FPtPeuDiU\nKlmS4yWI1IS9vT1sbGw4CFNNnT9/HrVq1VLKaWW1LxNdu3bF89xc7I6LFR2FPkNBYSGOx99Eq2++\n4XgJIjXSuXNnXLlyBenp6aKj0Ge4ePEiUlJS0LdvX6VsX+3LRJMmTWBRujT+PMcRxupkd1wsnufl\n4YcffhAdhYg+w4gRI1BYWIg9e/aIjkKfYdeuXdDT08OgQYOUsn21LxMSiQQdO3XC6bsJyMzLEx2H\nPtG2c+dgUbo0x0sQqRlHR0dUrVoVf//9t+go9IlkMhkiIyPRrFkzGBoaKmUfal8mgFdNOb+wEJvO\nnBEdhT5BZl4ezty9i46dOkEi0YhfQaJixd3dHXfu3MG9e/dER6FPcOLECTx79kxpRyUADSkTderU\nQUV7e/zJyVTUwupTJ5FfWIjhw4eLjkJEX8Db2xsSiQRbt24VHYU+wa5du2BiYoKePXsqbR8aUSYA\nYKiXF66mpuDYjRuio9AHSKVSrI2MhFPt2qhXr57oOET0BSwtLdG6dWscPnwYWVlZouPQByQkJCA6\nOhr9+vWDtra20vajMWVi9OjRKG1ujnlHDouOQh+w/sxpPMzMxOQpU0RHISI5zJkzB7m5uVi/fr3o\nKPQBK1asgJ6eHqZPn67U/WhMmdDV1cVQLy+cS0zEec7OppJkMhmWh4ejSuXK6NGjh+g4RCQHV1dX\nNGzYEMHBwcjPzxcdh94hNTUVERER+O6772BhYaHUfWlMmQCAiRMnwsjQELMPhYiOQu+wK/YC7j55\ngp9/+UV0FCJSgJkzZ+LZs2fYtm2b6Cj0DqtWrYKWlhZmz56t9H1pVJkwNDTE9wMGIOz2bcTdvy86\nDv2LTCbDb0ePopyNjVJHFBNR0fnmm2/g5OSE7du348WLF6Lj0L88evQIx44dQ/v27WFra6v0/WlU\nmQCAWbNmwdjICD/u3Ck6Cv3L8rAwxD96hGnTp/NyUCINsmDBAjx9+hRLly4VHYX+Zc6cOQCAhQsX\nFsn+NO5d3czMDFOnTUPcg/tYf/q06DgE4El2Nn4LPYY6rq4YMmSI6DhEpECtW7dG+/btsW/fPt5N\nVEVERkYiMjISw4cPR6VKlYpknxpXJgDgp59+gqOjI2YdCkEWZ8UUbszuXcjNz8c6jvom0khr1qyB\njo5OkZybpw+TSqX47bffYG1tjV9//bXI9quRZUIikWDt2rXIyM3Fz0H7RMcp1s4kJCD40iUM8PRE\nrVq1RMchIiWwtrbGuHHjEBsbiyNHjoiOU6z5+/vjwYMHWLx4MXR1dYtsvxpZJgCgQYMG6NmzJwKj\noxFx+5boOMVSfkEBhm8PhLm5ORYvXiw6DhEp0ZQpU1CxYkUsXLgQmZmZouMUSwkJCdi2bRuaNWum\n1Nku30VjywTw6tBb2bJlMXDbNqTn5IiOU+yM2LEDCU+eYLWfn9JuLkNEqkFbWxtbt27F8+fP8Qsv\n/y5y+fn5GDduHHR1dbFly5Yi379GlwljY2Ps2LkTT3Ny4Llls+g4xcqf585hx4UY/PDDD5ygiqiY\naNiwIaZOnYrz589j3bp1ouMUK3PmzEFSUhLWrl1bJJeC/i+NLhMA0KRJE0yeMgUn4uOx8Ngx0XGK\nhTtpaRi3by8cHR2xcuVK0XGIqAhNnjwZLVu2xLp163Dp0iXRcYqFgwcP4uDBgxg8eHCRn954TePL\nBPDql7t5s2aY//cRnEu8KzqORssvKIDHhg2Q6OggODhYqTeWISLVtGvXLpiZmWHChAm8EZiSJSUl\n4bfffkONGjWEfngrFmVCIpFgz969MC9dGu7r1+PW40eiI2kkmUwG9w3rcePRQ6xavRoVK1YUHYmI\nBDA3N8f27duRnp6OYcOG8d4dSpKeno7hw4dDIpEgODgYOjo6wrIUizIBvPrl/vvoUUi1tdHJzw+P\nnj8XHUnjeAUG4PjNm5g5cyb69u0rOg4RCdSiRQusXr0a8fHxGDVqFGQymehIGiUnJwdeXl7IyMhA\nUFBQkU1O9T7FpkwAQM2aNREUHIyneXnosGolJ7RSoMl//YUdMTHw9vbG5MmTRcchIhUwaNAgzJ49\nG+fOncOUKVNEx9EYBQUF8PHxwb1797B582a0bNlSdKTiVSYAoHnz5ti6dSvuPHmCLmv8UFBYKDqS\n2lt24gSWhZ1A9+7dsWzZMtFxiEiF+Pr6YuTIkThy5Aj++OMP0XHUnkwmwy+//ILLly9j8eLFcHd3\nFx0JQDEsEwDQo0cPLF22DNFJSXBbuYJHKOTw29G/MfXAfjRt2hQ7duzgTbyI6D+WLFmCnj17IiAg\nAL/99pvoOGqroKAAY8aMwcmTJ+Hr6wsfHx/Rkd4oITqAKMOHDwcAjPzxR7RcuhQHhg9HWSMjwanU\ny7g9u+EfGYk2rVtj/4EDvHKDiN4rMDAQurq62LZtG548eYK5c+fyPeMzZGdnw8fHB1euXMGUKVMw\nc+ZM0ZHeUqw/Rg4fPhyB27fjXuYzNF+ymFd5fCKpVIr+mzbBPzISffv2xaHDh4t0DngiUj8SiQRb\nt27FuHHjEBoaCm9vb7x48UJ0LLXw5MkTeHp64vr161ixYoXKFQmgmJcJ4NUpj8OHDyNbJkPr5csR\ndTdBdCSVlpWXh05+qxF86SLGjBmDrVu38tQGEX2yBQsW4Pfff0dsbCw8PT2Rnp4uOpJKS0hIwPff\nf4/U1FQEBga+OaquavhXAECzZs1wKiICeoaGaL96NWfKfI/oe/dQf+HvOJuYiAULFmDhwoWiIxGR\nGho7diw2btyIpKQkuLu7IzIyUnQklbRv3z4MGDAAL168wKFDh1T61gQsE/+oWbMmrly9ikaNGmFm\nyEF09lvNm4P9y6LQULitXIF8bW2EHDqEcePGiY5ERGqsf//+OH36NIyNjTF69GgsWrSIc1H848WL\nF/D19cWcOXPg4OCAixcvonnz5qJjfRDLxL+Ym5vjRFgYZsyYgciEBNT7fUGxv335s9xcdPXzw/SD\nB1C/YUNcuXYNrVu3Fh2LiDSAs7Mzrl69is6dO+PPP/+Ep6cnHj0q3mPX4uPj0atXL4SGhsLHxwfR\n0dFCbtz1uVgm3mHq1Kk4fuIEtEuWRCc/PwwPDEBmMbx8dHPUWTj/Oh+nEu5g2rRpOHHiBCwsLETH\nIiINUqpUKezduxcrV67E3bt34e7ujk2bNhW7oxT5+flYtGgRPD09kZOTg3379mHZsmVqc8ULy8R7\nNG7cGNdv3MB3PXsiMCYGtefNxfrTp0XHKhKXkpPRYsli/LhjB8qUK4ew8HBMnz6dAy2JSGmGDx+O\nc+fOoUaNGli+fDl69eqFmJgY0bGKxNGjR9GtWzf8+eefaNWqFS5fvoxOnTqJjvVZ+NfhA4yNjREY\nGLBuDA8AAA6vSURBVIiIiAhY2dlh9O5daLroD8Tdvy86mlJkv3iBH3dsR4sli3E7IwMLFizAlStX\n0LBhQ9HRiKgYcHR0RFRUFNavX4/s7GwMHz4cP//8s8Ze8ZGUlAQvLy/4+vqiZMmSOHjwIEJCQmBt\nbS062mdjmfgEDRo0wMWLF7Fo0SLcy8pCi6VL0MVvNc4nJoqOphBPs7Pxy769qDZ7FraeP49u3bvj\n9p07GDduHI9GEFGRGzhwIBISEjBkyBCcPHkSnTt3xsyZMzVmPMWdf95f3d3dcf36dUyZMgW3bt3C\nt99+KzraF+Nfik8kkUgwatQo3ElIgLe3N6JTU/HNsqVovWwpQm/cUOq+d11QzqG+5GfPMDwwADXm\nzMaayEi4NmiAiIgI7NixQ8jYiICAgCLfpwh8npqFz1M5SpUqBT8/P8TGxqJNmzYICQlB165d8csv\nvyBRiR/kDh8+rLRtX7p0Cd7e3vDw8EBUVBT69OmDm//caVldxka8j1LKRG5uLry8vFC+fHmUL18e\nw4cP/+hMZ56enpBIJG99NWrUSBnx5GJmZoZly5YhOTkZEydOREJWFrr5r0HD33/H0uPHlTJQc9eF\nCwrblkwmw6GrV9Fr/TrUmjcXO2Nj0bpdO8TFxSE0NBQNGjRQ2L4+F9+UNQufp2YR9TwdHR0RHByM\nmzdvwt3dHREREejVqxe8vb1x+PBhSKVShe5P0WUiLy8Pu3btgqenJwYNGoTr16/D29sb9+7dw6ZN\nm2BjY6PQ/YmilHtz9O/fH+Hh4Zg3bx5evnwJX19fZGRkfPCXUUtLC99++y02bNjwZpkqT9FsaGiI\nOXPmYNq0aViyZAlWr1qFKQf2Y9bhQ2hgZ4c+deriOycn6JRQjdufxCQlwT/iFI5cv4G0rOcwMjKC\ne69emD17Nuzs7ETHIyL6IHt7e2zduhWLFi3C1KlTsWPHDkyePBm//vorGjRogO7du6NOnTqiYwJ4\n9aEtLCwMQUFBiI6ORl5eHqytrTFx4kRMnDgRpUqVEh1R4RT+l+7OnTvYt28fDh48iLZt2wIAypUr\nh44dO2L+/PmoUKHCOx/38uVL6OrqomzZsoqOpFS6uroYP348xo8fj/Pnz2PlypXY/9dfGBYYgPH7\n9qKurS2aVa6C9jUdUbXsV0WW61luLkKuXsGxGzf+r737j2nqXOMA/m17wcJgrQNcf2jYuA4652y7\niU6NFLJM5xI3MIP9cMKMw7AMsiVbcjXLAtni2JYlZFkMmaJREw3ZL+kMsA3CGrIAFqSF3W3VydQ5\nKQO9A0Va3dLn/mHayKWU/jgUTu/zSd7E9Lwt79NvbZ80PefFyfMXcOE/V7AgPh5r163D9u3b8eyz\nzyIuLi5q62GMMSGkpaWhtrYWe/fuhdlsRl1dHSwWC1paWpCWlga9Xo9Vq1YhNzcXCxcujNq6nE4n\nLBYLuru70d/fj7GxMSgUCjz11FMoKytDbm5u1NYyFwRvJqxWKzweD4xGo+82g8EAj8cDq9U6bTMh\nkUhgsVigUqmg1+uxdetWbNmyBUlJSUIvcdasXLkSBw8ehMfjQXNzM+rq6nCysxNtTY2oampEanIy\nVqjVWJORAb1WC+PiJYLsVOq6eRP/dg6i/9Igus6fw6mLF3HuyhV4PB7ckZiI5Q8+iIrC3SgtLcWd\nd94pQKWMMTa3pFIpCgoKUFBQAJfLhSNHjuDYsWOwWq1obW1FdXU11Go1li1bBr1ej8zMTGRlZQny\nrcDY2BgcDgdOnz4Nu90Oh8OBkZERAEBqairWrFmDkpISFBYWiv63EMESvJm4dOkSVCoV0tLSfLep\nVCrcfffduHTp0rT327RpE4qKiqDVatHS0oI9e/agvr4eTU1NAf/ezz//LNjahaRWq/HWW28BuPWc\nWCwWWK1W9P30E9rOnPHNS4iPR0piIlTJyViYlITEf8QhMT4eSfHxSJQvwB1x8Tg9PIx/NTRg4uYN\nXL95ExM3b+Ka+waGro5h5Pp1jLlcvseTL1iAfy5diq2PP46cnBwYDAbfGRlnz87vq3mOjo7+X5xX\nznXGFq5zfsjOzkZ2djY8Hg8cDgcsFgtOnTqFzs5OtLa2+uYlJSVBqVQiNTUVycnJkMvlkMvlSEhI\nQEJCAi5cuICPP/4YLpcLLpcLbrcbLpcLV69exeXLlzE6OgrXbe+5CoUCWVlZKCoqQl5eHu69917f\nsb6+vqg+B6EQ/LOTglRZWUkSiSTg6OnpoQ8//JDUavWU+6tUKqqpqQn2z1FHRwfJZDK6ePGi3+OD\ng4Ok0WgIAA8ePHjw4MEjxKHRaGhwcDDoz+VAgv5moqKiAs8//3zAOenp6fjll18wNDSEy5cv+04v\nHBoawh9//BHSr1bXrFmD1NRUmM1mvPLKK1OOq9Vq9PT0wOl0Bv2YjDHGGLtFrVZDrVYL8lhBNxMp\nKSlISUmZcd6qVasglUrR29vr+wGm3W6HVCrF6tWrg15Yd3c3hoeHAxYq5BPBGGOMsfAIfp2JjIwM\nFBQUYNu2bTh48CAOHDiA4uJiFBUVTdr5TKfToaGhAQBw/fp1vPHGG+jq6sLAwAD279+Pl156CVlZ\nWXjiiSeEXiJjjDHGBCQhIhL6Qd1uN1599VU0NjYCADZv3oyPPvpo0nUjpFIpDh06hOLiYrjdbuTn\n58Nms2F8fBwmkwn5+fnYsmUL71LJGGOMzXOz0kwwxhhj7P8H783BGGOMsYiIppmI5f0+jh49CoPB\nAKVSiby8PPT39wecb7fbYTKZoFQq8dBDD6G+vj5KK41MKHVaLJYp2UmlUpy57Rod8017ezs2b94M\nrVYLqVQKs9k8433EmGWodYoxSwCorq5GdnY2FAoFjEYjqqqqgtpgSmyZhlOnGDOtra2FXq+HQqFA\neno6SktL8f333we8j9iy9Aq1ViHyFE0zsW3bNhw/fhxVVVWorKz0bZwSiHe/j6GhId+Y6SJY0Xbi\nxAmUlJTg4Ycfhtlsxt9//42cnBzf1dT+l9PpxPr16wEAX331FQwGA1544QU0NzdHc9khC7VOL++p\nxt6xdOnSKK04dBMTEzAajdi7dy+AW6+/QMSaZah1eokpS+BW01RRUYGuri689957sFgsKCsrC3gf\nMWYaTp1eYsp0yZIleP/999Hb24tPP/0UUqkUhYWFky5AdTsxZukVaq1eEeUpyNUqZtnAwADJZDL6\n5ptvfLc1NzeTTCaj8+fPT3u/kpISys/Pj8YSw2Yymei5556bdJtKpaJ33nnH7/zKykrSaDSTbnvm\nmWfo0UcfnbU1CiHUOr/77juSSCQ0OjoajeUJTiKRkNlsDjhHrFneLpg6xZ6l148//kgSiYQcDse0\nc2Ih02DqjIVMJyYmSC6X0+eff+73eCxk6TVTrULkKYpvJmba72M6t+/3sXHjRhw5cgTj4+PRWHLQ\nrFbrpLqAW7V1dHT4nd/V1QWDwRD0/Pki1Dq9jEYjdDodqqqq5vVXqOEQa5bhEnuWHo8HAAJueR0L\nmQZTp5dYM/3zzz9RW1uLuLg4mEwmv3NiIUsguFq9IslTFM1EJPt9HDt2DN9++y02bNiAPXv2oKio\nKBpLDsqVK1fgdrunvGD1ev20dQ0ODvp9gbvdboyOjs7aWiMRTp0ajQb79+/Hl19+ierqavT19eGB\nBx6IqSueijHLcMRClh6PB6+99ho2bNiAZcuWTTtP7JkGW6dYM/3hhx+QlJSE1NRUvPvuu+jp6Zn2\n8gNizzKUWoXIU/CNvkJRVVWFt99+O+Cc7u7usB//9sZhxYoVWLt2LdavX4/ff/8dixcvDvtx2ezL\nzMxEZmYmgFv/gQsKCqDT6XDo0CHs3r17jlfHQhELWZaXl+PcuXMz/mBP7IKtU6yZ6nQ69Pf3Y2Bg\nAJ999hlycnLQ3t7uqyWWhFKrEHnO6TcTFRUVcDgcAcfy5cuh1Wp9+314Rbrfx3yQkpICuVwOu90+\n6Xa73T5ts6PVamGz2abMl8vlUCqVs7bWSIRTpz9PPvkkvvjiC6GXN2fEmKVQxJRleXk5mpqa0NbW\nNuPl+8WcaSh1+iOGTOPi4pCRkYHHHnsM+/btw1133YXDhw/7nSvmLIHQavUn1DzntJlISUnxdUTT\njQULFkza78Nrtvb7iLbVq1dPecH29fVNewrrI4884vdDed26dbO2RiGEWqc/jY2N0Gg0Qi9tzog1\nSyGIJcvy8nKYzWa0tbUhPT19xvlizTTUOv0RS6ZeHo8Hf/31F65du+b3uFiz9GemWv0JOc+wf7oZ\nZU8//TQtWrSIDhw4QHV1dZSWljbl7ICsrCw6fvw4ERGNj4/T66+/Tp2dnXT27Fnat28frVixgnQ6\nHblcrrkowa8TJ06QTCaj0tJSslgslJOTQ0qlkoaHh4mIaNeuXVRcXOyb73Q6KTk5mUwmE1ksFtqx\nYwfJZDJqbm6eqxKCEmqdNTU11NDQQGfOnKGWlhYqLi4mmUxGra2tc1XCjMbHx8lms5HNZiOJREI1\nNTVks9not99+I6LYyTLUOsWYJRHRyy+/TEqlktrb28npdPrG7e8fsZBpOHWKMdNdu3ZRe3s7/frr\nr/T111/Tzp07KT4+njo6OnzHxZ6lV6i1CpGnaJoJl8tFO3fuJK1WS1qtlsrKyujGjRuT5kgkEjp8\n+LBv/saNG2nRokWUmJhImzZtok8++YRGRkbmYvkBHT16lPR6PSkUCsrNzaX+/n7fsRdffJHy8vIm\nzbfZbGQymUihUJDRaKT6+vpoLzksodT5wQcf0H333UcJCQl0//3305tvvkm9vb1zseygeU+vkkgk\nJJVKff/evn07EcVOlqHWKcYsiWhKfd7hfY8hio1Mw6lTjJnu2LGD7rnnHkpISKCVK1fS7t276eTJ\nk77jsZClV6i1CpEn783BGGOMsYiI4tRQxhhjjM1f3EwwxhhjLCLcTDDGGGMsItxMMMYYYywi3Eww\nxhhjLCLcTDDGGGMsItxMMMYYYywi3EwwxhhjLCLcTDDGGGMsItxMMMYYYywi3EwwxhhjLCLcTDDG\nGGMsIv8FQPebIuovctAAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x10bf67310>"
]
}
],
"prompt_number": 9
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"g.intersection(c).plot()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 10,
"text": [
"<matplotlib.axes.AxesSubplot at 0x10bcf1390>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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IaPPnz0fPnj1RUFCAn376SSs+TqiO0q5iKCsrw9ChQzFnzhzY29vLtW9wcDDE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\n3DgUFBTA3d0diYmJGDNmDLZ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"text": [
"<matplotlib.figure.Figure at 0x10bfda5d0>"
]
}
],
"prompt_number": 10
}
],
"metadata": {}
}
]
}
@lsxinh
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lsxinh commented Aug 2, 2015

I am very interested in your talks in geospatial data with python/ipython. But one thing that pulls be back is I could not follow the ipython notebook on your github because I could not install the related packages. I did tried and it took me hours but it still does not work.
I use Windows 7 and anaconda 64 bit, python 3.4. Please show me a step by step how to install Geoseries and other packages after install Anaconda in Windows.

Thanks very much!
Xinh

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