From 9ff2110dfe09ddb08e530ba9494b67ccfbf7a591 Mon Sep 17 00:00:00 2001
From: Ou Ku <o.ku@esciencecenter.nl>
Date: Thu, 28 Sep 2023 17:49:12 +0200
Subject: [PATCH] initial update

---
 notebooks/07-vector-data-in-python.ipynb | 446 ++++++++++++++++++++++-
 1 file changed, 445 insertions(+), 1 deletion(-)

diff --git a/notebooks/07-vector-data-in-python.ipynb b/notebooks/07-vector-data-in-python.ipynb
index 8352274c..bf4b377e 100644
--- a/notebooks/07-vector-data-in-python.ipynb
+++ b/notebooks/07-vector-data-in-python.ipynb
@@ -39,7 +39,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "id": "19beffdb",
    "metadata": {},
    "outputs": [],
@@ -47,6 +47,433 @@
     "import geopandas as gpd"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "bb46415e",
+   "metadata": {},
+   "source": [
+    "Administration data retrieved from GADM. Download [link](https://geodata.ucdavis.edu/gadm/gadm4.1/shp/gadm41_GRC_shp.zip)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "78328ad1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# p_buildings = './greece-latest-free/gis_osm_buildings_a_free_1.shp'\n",
+    "# p_landuse = './greece-latest-free/gis_osm_landuse_a_free_1.shp'\n",
+    "p_nature = './greece-latest-free/gis_osm_pofw_a_free_1.shp'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "bad09c74",
+   "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>GID_3</th>\n",
+       "      <th>GID_0</th>\n",
+       "      <th>COUNTRY</th>\n",
+       "      <th>GID_1</th>\n",
+       "      <th>NAME_1</th>\n",
+       "      <th>NL_NAME_1</th>\n",
+       "      <th>GID_2</th>\n",
+       "      <th>NAME_2</th>\n",
+       "      <th>NL_NAME_2</th>\n",
+       "      <th>NAME_3</th>\n",
+       "      <th>VARNAME_3</th>\n",
+       "      <th>NL_NAME_3</th>\n",
+       "      <th>TYPE_3</th>\n",
+       "      <th>ENGTYPE_3</th>\n",
+       "      <th>CC_3</th>\n",
+       "      <th>HASC_3</th>\n",
+       "      <th>geometry</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>GRC.1.2.26_1</td>\n",
+       "      <td>GRC</td>\n",
+       "      <td>Greece</td>\n",
+       "      <td>GRC.1_1</td>\n",
+       "      <td>Aegean</td>\n",
+       "      <td>Αιγαίο</td>\n",
+       "      <td>GRC.1.2_1</td>\n",
+       "      <td>South Aegean</td>\n",
+       "      <td>Νότιο Αιγαίο</td>\n",
+       "      <td>Rhodos</td>\n",
+       "      <td>Rhodes</td>\n",
+       "      <td>Ρόδου</td>\n",
+       "      <td>Dímos</td>\n",
+       "      <td>Municipality</td>\n",
+       "      <td>NA</td>\n",
+       "      <td>GR.AI.RH</td>\n",
+       "      <td>MULTIPOLYGON (((27.75792 35.88792, 27.75903 35...</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           GID_3 GID_0 COUNTRY    GID_1  NAME_1 NL_NAME_1      GID_2   \n",
+       "34  GRC.1.2.26_1   GRC  Greece  GRC.1_1  Aegean    Αιγαίο  GRC.1.2_1  \\\n",
+       "\n",
+       "          NAME_2     NL_NAME_2  NAME_3 VARNAME_3 NL_NAME_3 TYPE_3   \n",
+       "34  South Aegean  Νότιο Αιγαίο  Rhodos    Rhodes     Ρόδου  Dímos  \\\n",
+       "\n",
+       "       ENGTYPE_3 CC_3    HASC_3   \n",
+       "34  Municipality   NA  GR.AI.RH  \\\n",
+       "\n",
+       "                                             geometry  \n",
+       "34  MULTIPOLYGON (((27.75792 35.88792, 27.75903 35...  "
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data = gpd.read_file('./greece-latest-free/gadm41_GRC_3.shp')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "767e30d7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df_rhodes = data.loc[data['NAME_3']=='Rhodos']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "ca861c00",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: >"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "df_rhodes.plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "26338222",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0      False\n",
+       "1      False\n",
+       "2      False\n",
+       "3      False\n",
+       "4      False\n",
+       "       ...  \n",
+       "321    False\n",
+       "322    False\n",
+       "323    False\n",
+       "324    False\n",
+       "325    False\n",
+       "Name: NAME_3, Length: 326, dtype: bool"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data['NAME_3']=='Rhodos'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "b83e4b17",
+   "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>featurecla</th>\n",
+       "      <th>scalerank</th>\n",
+       "      <th>min_zoom</th>\n",
+       "      <th>geometry</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Land</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>POLYGON ((-59.57209 -80.04018, -59.86585 -80.5...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Land</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>POLYGON ((-159.20818 -79.49706, -161.12760 -79...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Land</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>POLYGON ((-45.15476 -78.04707, -43.92083 -78.4...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Land</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>POLYGON ((-121.21151 -73.50099, -119.91885 -73...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Land</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>POLYGON ((-125.55957 -73.48135, -124.03188 -73...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>122</th>\n",
+       "      <td>Land</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>POLYGON ((51.13619 80.54728, 49.79368 80.41543...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>123</th>\n",
+       "      <td>Land</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>POLYGON ((99.93976 78.88094, 97.75794 78.75620...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>124</th>\n",
+       "      <td>Land</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>POLYGON ((-87.02000 79.66000, -85.81435 79.336...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>125</th>\n",
+       "      <td>Land</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>POLYGON ((-68.50000 83.10632, -65.82735 83.028...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>126</th>\n",
+       "      <td>Land</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>POLYGON ((-27.10046 83.51966, -20.84539 82.726...</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>127 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    featurecla  scalerank  min_zoom   \n",
+       "0         Land          1       1.0  \\\n",
+       "1         Land          1       1.0   \n",
+       "2         Land          1       0.0   \n",
+       "3         Land          1       1.0   \n",
+       "4         Land          1       1.0   \n",
+       "..         ...        ...       ...   \n",
+       "122       Land          1       1.0   \n",
+       "123       Land          0       0.0   \n",
+       "124       Land          0       0.0   \n",
+       "125       Land          0       0.0   \n",
+       "126       Land          0       0.0   \n",
+       "\n",
+       "                                              geometry  \n",
+       "0    POLYGON ((-59.57209 -80.04018, -59.86585 -80.5...  \n",
+       "1    POLYGON ((-159.20818 -79.49706, -161.12760 -79...  \n",
+       "2    POLYGON ((-45.15476 -78.04707, -43.92083 -78.4...  \n",
+       "3    POLYGON ((-121.21151 -73.50099, -119.91885 -73...  \n",
+       "4    POLYGON ((-125.55957 -73.48135, -124.03188 -73...  \n",
+       "..                                                 ...  \n",
+       "122  POLYGON ((51.13619 80.54728, 49.79368 80.41543...  \n",
+       "123  POLYGON ((99.93976 78.88094, 97.75794 78.75620...  \n",
+       "124  POLYGON ((-87.02000 79.66000, -85.81435 79.336...  \n",
+       "125  POLYGON ((-68.50000 83.10632, -65.82735 83.028...  \n",
+       "126  POLYGON ((-27.10046 83.51966, -20.84539 82.726...  \n",
+       "\n",
+       "[127 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data = gpd.read_file(geodatasets.get_url('naturalearth.land'))\n",
+    "data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "e9419b1a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: >"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data.plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1c5995bc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "gdf = gpd.read_file(p_nature)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f27095ed",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "gdf_rhodes = gdf.cx[27.5:28.4, 35.8:36.5]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b8248340",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "gdf_rhodes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "22930909",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from matplotlib import pyplot as plt\n",
+    "# fig, ax = plt.subplots()\n",
+    "gdf_rhodes.plot(column='fclass', legend=True, legend_kwds={'loc': 'right'})\n",
+    "# plt.colorbar(ax)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "922f8f34",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "landuse_rhodes"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "da625680",
@@ -721,6 +1148,23 @@
  "metadata": {
   "jupytext": {
    "main_language": "python"
+  },
+  "kernelspec": {
+   "display_name": "geospatial",
+   "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": "3.10.10"
   }
  },
  "nbformat": 4,