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Posted to commits@superset.apache.org by ru...@apache.org on 2024/03/14 20:20:46 UTC
(superset) branch master updated: feat: Add Turkey's regions to country map visualization (#27455)
This is an automated email from the ASF dual-hosted git repository.
rusackas pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/superset.git
The following commit(s) were added to refs/heads/master by this push:
new 6b529a4b68 feat: Add Turkey's regions to country map visualization (#27455)
6b529a4b68 is described below
commit 6b529a4b68f26ec0f38926d78057473de3ed2648
Author: İSKENDER ÜLGEN OĞUL <is...@users.noreply.github.com>
AuthorDate: Thu Mar 14 23:20:39 2024 +0300
feat: Add Turkey's regions to country map visualization (#27455)
---
.../scripts/Country Map GeoJSON Generator.ipynb | 1415 +++-----------------
.../src/countries.ts | 5 +
.../src/countries/turkey_regions.geojson | 18 +
3 files changed, 210 insertions(+), 1228 deletions(-)
diff --git a/superset-frontend/plugins/legacy-plugin-chart-country-map/scripts/Country Map GeoJSON Generator.ipynb b/superset-frontend/plugins/legacy-plugin-chart-country-map/scripts/Country Map GeoJSON Generator.ipynb
index 6b8052274e..7006cb441a 100644
--- a/superset-frontend/plugins/legacy-plugin-chart-country-map/scripts/Country Map GeoJSON Generator.ipynb
+++ b/superset-frontend/plugins/legacy-plugin-chart-country-map/scripts/Country Map GeoJSON Generator.ipynb
@@ -42,7 +42,7 @@
},
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
@@ -50,18 +50,7 @@
"id": "VjGrqW4Kt1LS",
"outputId": "2e2accda-5ee4-4270-872e-ecb78d0d02a2"
},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Skip ne_10m_admin_0_countries.zip because it already exists\n",
- "Skip ne_10m_admin_1_states_provinces.zip because it already exists\n",
- "Skip ne_50m_admin_1_states_provinces.zip because it already exists\n",
- "Done. \n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"import os\n",
"import requests\n",
@@ -107,7 +96,7 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
@@ -115,15 +104,7 @@
"id": "EL0e9DEVt1LT",
"outputId": "16cd6450-d4a3-457a-b205-9797bbce33fc"
},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "GeoJSON file for India downloaded and loaded successfully.\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"import os\n",
"import geopandas as gpd\n",
@@ -147,56 +128,24 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": null,
"metadata": {
"id": "_PKEg8s1t1LT",
"outputId": "9937eacd-7a05-491f-f356-790ad75a819f"
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "Index(['featurecla', 'scalerank', 'adm1_code', 'diss_me', 'iso_3166_2',\n",
- " 'wikipedia', 'iso_a2', 'adm0_sr', 'name', 'name_alt',\n",
- " ...\n",
- " 'FCLASS_ID', 'FCLASS_PL', 'FCLASS_GR', 'FCLASS_IT', 'FCLASS_NL',\n",
- " 'FCLASS_SE', 'FCLASS_BD', 'FCLASS_UA', 'FCLASS_TLC', 'geometry'],\n",
- " dtype='object', length=122)"
- ]
- },
- "execution_count": 3,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"df_50m.columns"
]
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": null,
"metadata": {
"id": "w8OD4nq2t1LT",
"outputId": "b7164440-d6e0-4074-b357-47fd8a8d2884"
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "Index(['featurecla', 'scalerank', 'labelrank', 'sovereignt', 'sov_a3',\n",
- " 'adm0_dif', 'level', 'type', 'tlc', 'admin',\n",
- " ...\n",
- " 'fclass_tr', 'fclass_id', 'fclass_pl', 'fclass_gr', 'fclass_it',\n",
- " 'fclass_nl', 'fclass_se', 'fclass_bd', 'fclass_ua', 'geometry'],\n",
- " dtype='object', length=169)"
- ]
- },
- "execution_count": 4,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"df_admin0_10m.columns = df_admin0_10m.columns.str.lower()\n",
"df_admin0_10m.columns"
@@ -204,378 +153,19 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": null,
"metadata": {
"id": "DUrz04nYt1LT",
"outputId": "18d7cdb0-8ab6-4238-e50c-925c5dc117b0"
},
- "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>adm1_code</th>\n",
- " <th>diss_me</th>\n",
- " <th>iso_3166_2</th>\n",
- " <th>wikipedia</th>\n",
- " <th>iso_a2</th>\n",
- " <th>adm0_sr</th>\n",
- " <th>name</th>\n",
- " <th>name_alt</th>\n",
- " <th>...</th>\n",
- " <th>FCLASS_ID</th>\n",
- " <th>FCLASS_PL</th>\n",
- " <th>FCLASS_GR</th>\n",
- " <th>FCLASS_IT</th>\n",
- " <th>FCLASS_NL</th>\n",
- " <th>FCLASS_SE</th>\n",
- " <th>FCLASS_BD</th>\n",
- " <th>FCLASS_UA</th>\n",
- " <th>FCLASS_TLC</th>\n",
- " <th>geometry</th>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>admin</th>\n",
- " <th></th>\n",
- " <th></th>\n",
- " <th></th>\n",
- " <th></th>\n",
- " <th></th>\n",
- " <th></th>\n",
- " <th></th>\n",
- " <th></th>\n",
- " <th></th>\n",
- " <th></th>\n",
- " <th></th>\n",
- " <th></th>\n",
- " <th></th>\n",
- " <th></th>\n",
- " <th></th>\n",
- " <th></th>\n",
- " <th></th>\n",
- " <th></th>\n",
- " <th></th>\n",
- " <th></th>\n",
- " <th></th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>Australia</th>\n",
- " <td>9</td>\n",
- " <td>9</td>\n",
- " <td>9</td>\n",
- " <td>9</td>\n",
- " <td>9</td>\n",
- " <td>0</td>\n",
- " <td>9</td>\n",
- " <td>9</td>\n",
- " <td>9</td>\n",
- " <td>0</td>\n",
- " <td>...</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>9</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>Brazil</th>\n",
- " <td>27</td>\n",
- " <td>27</td>\n",
- " <td>27</td>\n",
- " <td>27</td>\n",
- " <td>27</td>\n",
- " <td>0</td>\n",
- " <td>27</td>\n",
- " <td>27</td>\n",
- " <td>27</td>\n",
- " <td>13</td>\n",
- " <td>...</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>27</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>Canada</th>\n",
- " <td>13</td>\n",
- " <td>13</td>\n",
- " <td>13</td>\n",
- " <td>13</td>\n",
- " <td>13</td>\n",
- " <td>13</td>\n",
- " <td>13</td>\n",
- " <td>13</td>\n",
- " <td>13</td>\n",
- " <td>9</td>\n",
- " <td>...</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>13</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>China</th>\n",
- " <td>31</td>\n",
- " <td>31</td>\n",
- " <td>31</td>\n",
- " <td>31</td>\n",
- " <td>31</td>\n",
- " <td>0</td>\n",
- " <td>31</td>\n",
- " <td>31</td>\n",
- " <td>31</td>\n",
- " <td>30</td>\n",
- " <td>...</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>31</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>India</th>\n",
- " <td>36</td>\n",
- " <td>36</td>\n",
- " <td>36</td>\n",
- " <td>36</td>\n",
- " <td>36</td>\n",
- " <td>0</td>\n",
- " <td>36</td>\n",
- " <td>36</td>\n",
- " <td>36</td>\n",
- " <td>13</td>\n",
- " <td>...</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>36</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>Indonesia</th>\n",
- " <td>33</td>\n",
- " <td>33</td>\n",
- " <td>33</td>\n",
- " <td>33</td>\n",
- " <td>33</td>\n",
- " <td>0</td>\n",
- " <td>33</td>\n",
- " <td>33</td>\n",
- " <td>33</td>\n",
- " <td>30</td>\n",
- " <td>...</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>33</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>Russia</th>\n",
- " <td>85</td>\n",
- " <td>85</td>\n",
- " <td>85</td>\n",
- " <td>85</td>\n",
- " <td>85</td>\n",
- " <td>1</td>\n",
- " <td>85</td>\n",
- " <td>85</td>\n",
- " <td>85</td>\n",
- " <td>84</td>\n",
- " <td>...</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>85</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>South Africa</th>\n",
- " <td>9</td>\n",
- " <td>9</td>\n",
- " <td>9</td>\n",
- " <td>9</td>\n",
- " <td>9</td>\n",
- " <td>0</td>\n",
- " <td>9</td>\n",
- " <td>9</td>\n",
- " <td>9</td>\n",
- " <td>9</td>\n",
- " <td>...</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>9</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>United States of America</th>\n",
- " <td>51</td>\n",
- " <td>51</td>\n",
- " <td>51</td>\n",
- " <td>51</td>\n",
- " <td>51</td>\n",
- " <td>51</td>\n",
- " <td>51</td>\n",
- " <td>51</td>\n",
- " <td>51</td>\n",
- " <td>51</td>\n",
- " <td>...</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>51</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "<p>9 rows × 121 columns</p>\n",
- "</div>"
- ],
- "text/plain": [
- " featurecla scalerank adm1_code diss_me \\\n",
- "admin \n",
- "Australia 9 9 9 9 \n",
- "Brazil 27 27 27 27 \n",
- "Canada 13 13 13 13 \n",
- "China 31 31 31 31 \n",
- "India 36 36 36 36 \n",
- "Indonesia 33 33 33 33 \n",
- "Russia 85 85 85 85 \n",
- "South Africa 9 9 9 9 \n",
- "United States of America 51 51 51 51 \n",
- "\n",
- " iso_3166_2 wikipedia iso_a2 adm0_sr name \\\n",
- "admin \n",
- "Australia 9 0 9 9 9 \n",
- "Brazil 27 0 27 27 27 \n",
- "Canada 13 13 13 13 13 \n",
- "China 31 0 31 31 31 \n",
- "India 36 0 36 36 36 \n",
- "Indonesia 33 0 33 33 33 \n",
- "Russia 85 1 85 85 85 \n",
- "South Africa 9 0 9 9 9 \n",
- "United States of America 51 51 51 51 51 \n",
- "\n",
- " name_alt ... FCLASS_ID FCLASS_PL FCLASS_GR \\\n",
- "admin ... \n",
- "Australia 0 ... 0 0 0 \n",
- "Brazil 13 ... 0 0 0 \n",
- "Canada 9 ... 0 0 0 \n",
- "China 30 ... 0 0 0 \n",
- "India 13 ... 0 0 0 \n",
- "Indonesia 30 ... 0 0 0 \n",
- "Russia 84 ... 0 0 0 \n",
- "South Africa 9 ... 0 0 0 \n",
- "United States of America 51 ... 0 0 0 \n",
- "\n",
- " FCLASS_IT FCLASS_NL FCLASS_SE FCLASS_BD \\\n",
- "admin \n",
- "Australia 0 0 0 0 \n",
- "Brazil 0 0 0 0 \n",
- "Canada 0 0 0 0 \n",
- "China 0 0 0 0 \n",
- "India 0 0 0 0 \n",
- "Indonesia 0 0 0 0 \n",
- "Russia 0 0 0 0 \n",
- "South Africa 0 0 0 0 \n",
- "United States of America 0 0 0 0 \n",
- "\n",
- " FCLASS_UA FCLASS_TLC geometry \n",
- "admin \n",
- "Australia 0 0 9 \n",
- "Brazil 0 0 27 \n",
- "Canada 0 0 13 \n",
- "China 0 0 31 \n",
- "India 0 0 36 \n",
- "Indonesia 0 0 33 \n",
- "Russia 0 0 85 \n",
- "South Africa 0 0 9 \n",
- "United States of America 0 0 51 \n",
- "\n",
- "[9 rows x 121 columns]"
- ]
- },
- "execution_count": 5,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"df_50m.groupby('admin').count()"
]
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -584,38 +174,7 @@
"id": "eUlJjdRkt1LT",
"outputId": "60df2dc3-800e-40ac-f151-696a7f91cff4"
},
- "outputs": [
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAABK4AAAMtCAYAAAC2GTmHAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/P9b71AAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzdd3ib1f338Y+m997xiu3svXcII0DYe7aMMktbRqGl5dfytNBB6QBK2S2bUvbeJIQQkkD2dIYz7HhvS56SLOn5w2Bi4iS2I1uy/X5dVy7iW0fn/grHTvTxOd9j8Hq9XgEAAAAAAAABxujvAgAAAAAAAIDOEFwBAAAAAAAgIBFcAQAAAAAAICARXAEAAAAAACAgEVwBAAAAAAAgIBFcAQAAAAAAICARXAEAAAAAACAgmf1dwPd5PB6VlJQoIiJCBoPB3+UAAAAAAADAh7xer+rr6zVkyBAZjYdfUxVw [...]
- "text/plain": [
- "<Figure size 2000x1000 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "text/plain": [
- "<AxesSubplot: >"
- ]
- },
- "execution_count": 6,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAAt8AAAMtCAYAAABHJx1iAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/P9b71AAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzdd3hc5ZU/8O+903tR7yNb7rZcZMuYTqgJIRBgQzYhkCykkmxC2CRLym+XbNqmVwhJYAktlAAhlEAoptuWJcuWbLlIsnqXpve55ffHSLJltZnRzNyZ0fk8D08iaXTvkayZOfe95z2HEUVRBCGEEEIIISTlWKkDIIQQQgghZLmg5JsQQgghhJA0oeSbEEIIIYSQNKHkmxBCCCGEkDSh5JsQQgghhJA0oeSbEEIIIYSQNKHkmxBCCCGEkDSRSx3AmQRBwODgIAwGAxiGkTocQgghhBBCFiWKIjweD0pL [...]
- "text/plain": [
- "<Figure size 2000x1000 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"df_50m[df_50m.adm0_a3 == 'USA'].plot(figsize=(20,10))\n",
"plt.show()\n",
@@ -633,32 +192,19 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": null,
"metadata": {
"id": "pr1jqM3kt1LU",
"outputId": "7211a182-b64a-469b-fadb-af2148ec6852"
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "array(['Australia', 'Brazil', 'Canada', 'United States of America',\n",
- " 'China', 'India', 'Indonesia', 'Russia', 'South Africa'],\n",
- " dtype=object)"
- ]
- },
- "execution_count": 7,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"df_50m['admin'].unique()"
]
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": null,
"metadata": {
"id": "k-KuZ8L4t1LU"
},
@@ -682,19 +228,11 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": null,
"metadata": {
"id": "-4uH5XaEt1LU"
},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Following country names are not valid: ['france_regions']\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"# Country names used in file names\n",
"countries = [\n",
@@ -782,6 +320,7 @@
" 'thailand',\n",
" 'timorleste',\n",
" 'turkey',\n",
+ " 'turkey_regions', # this one derived from turkey - see below\n",
" 'turkmenistan',\n",
" 'uganda',\n",
" 'uk',\n",
@@ -827,31 +366,12 @@
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": null,
"metadata": {
"id": "tJ_WNQl8t1LU",
"outputId": "4f601ce0-26e4-4a40-c36c-8449420e9406"
},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "/var/folders/lc/0hq8dvlj5c7_g_fzpmgclh540000gn/T/ipykernel_60888/1621097802.py:21: UserWarning: The GeoDataFrame you are attempting to plot is empty. Nothing has been displayed.\n",
- " get_gdf(country).plot(ax=ax)\n"
- ]
- },
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAB8oAAAagCAYAAAAH4dMtAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/P9b71AAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzdd3hTZfsH8O/Jbpom6R50D1poKaMMi7KRgvwQRQEVX0ERFAEBUQEHgoigoL5OQF5FVBBBBRWRoSzRAqVQ9ip00b139vP7ozQ2NN0jSXt/rivXRZ6cnNznkN4559zPeR6OMcZACCGEEEIIIYQQQgghhBBCCCGEdBI8SwdACCGEEEIIIYQQQgghhBBCCCGEtCcqlBNCCCGEEEIIIYQQQgghhBBCCOlUqFBOCCGEEEIIIYQQQgghhBBCCCGkU6FCOSGEEEIIIYQQQgghhBBCCCGEkE6FCuWEEEIIIYQQ [...]
- "text/plain": [
- "<Figure size 2000x2000 with 95 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"import geopandas as gpd\n",
"\n",
@@ -905,33 +425,12 @@
},
{
"cell_type": "code",
- "execution_count": 11,
+ "execution_count": null,
"metadata": {
"id": "xx8IbBKtt1LU",
"outputId": "025139d2-ba0b-43a9-e2ec-f4608e6ecad2"
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot: >"
- ]
- },
- "execution_count": 11,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAAh8AAAF3CAYAAAAFEil7AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/P9b71AAAACXBIWXMAAA9hAAAPYQGoP6dpAABq+klEQVR4nO3dd3hc1bU28PdM7029FxdJlns3xhRjEGASCKZDQk3DkIAJCYaEclPghlxKvmACCYEQ4pAAAUIzAdvY4I7cm9xkS7J6maIy/Xx/yJItq81IU6X39zx6QHPOnNmzJeus2XvttQVRFEUQERERRYgk2g0gIiKi0YXBBxEREUUUgw8iIiKKKAYfREREFFEMPoiIiCiiGHwQERFRRDH4ICIiooiSRbsBZ/P7/aiuroZer4cgCNFuDhEREQVAFEU4HA6kp6dDIhl4bCPmgo/q6mpkZWVFuxlEREQ0BJWVlcjM [...]
- "text/plain": [
- "<Figure size 640x480 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"usa = df[df['adm0_a3'] == 'USA']\n",
"usa.plot()"
@@ -939,33 +438,12 @@
},
{
"cell_type": "code",
- "execution_count": 12,
+ "execution_count": null,
"metadata": {
"id": "ixC6KENXt1LU",
"outputId": "8e63cb2d-d733-4a9f-caf6-ccc843f15b5d"
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot: >"
- ]
- },
- "execution_count": 12,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAApsAAAFvCAYAAAAFeQD2AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/P9b71AAAACXBIWXMAAA9hAAAPYQGoP6dpAACfgElEQVR4nOzdd1hb59k/8O/R3ou9p20MeGCMdxyPLGcnzptmtM1ezWiTjjRv+7ZNOpImv7YZbdK0TZM2sxlN0+xtxyM2GOOFDQbM3iC0t3R+f8hgY8AgkHSOxP25Li4bjaMHIaT7PM9z3zfDsiwLQgghhBBCIkDA9QAIIYQQQkj8omCTEEIIIYREDAWbhBBCCCEkYijYJIQQQgghEUPBJiGEEEIIiRgKNgkhhBBCSMRQsEkIIYQQQiKGgk1CCCGEEBIxIq4HcKpAIICuri6o1WowDMP1cAghhBBCyClYloXVakV6 [...]
- "text/plain": [
- "<Figure size 800x800 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"def reposition(df, idx, xoff=None, yoff=None, xscale=None, yscale=None, simplify=None):\n",
"\n",
@@ -1003,168 +481,12 @@
},
{
"cell_type": "code",
- "execution_count": 13,
+ "execution_count": null,
"metadata": {
"id": "vN4Ngpe7t1LU",
"outputId": "3bcdc612-cc01-49be-fe19-f6e08e833fca"
},
- "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>labelrank</th>\n",
- " <th>sov_a3</th>\n",
- " <th>type</th>\n",
- " <th>admin</th>\n",
- " <th>adm0_a3</th>\n",
- " <th>gu_a3</th>\n",
- " <th>name</th>\n",
- " <th>abbrev</th>\n",
- " <th>...</th>\n",
- " <th>name_sv</th>\n",
- " <th>name_tr</th>\n",
- " <th>name_uk</th>\n",
- " <th>name_ur</th>\n",
- " <th>name_vi</th>\n",
- " <th>name_zh_x</th>\n",
- " <th>name_zht</th>\n",
- " <th>geometry</th>\n",
- " <th>name_zh_y</th>\n",
- " <th>iso_3166_2</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>0</th>\n",
- " <td>Admin-0 country</td>\n",
- " <td>0</td>\n",
- " <td>4</td>\n",
- " <td>CH1</td>\n",
- " <td>Country</td>\n",
- " <td>Hong Kong S.A.R.</td>\n",
- " <td>HKG</td>\n",
- " <td>HKG</td>\n",
- " <td>Hong Kong</td>\n",
- " <td>H.K.</td>\n",
- " <td>...</td>\n",
- " <td>Hongkong</td>\n",
- " <td>Hong Kong</td>\n",
- " <td>Гонконг</td>\n",
- " <td>ہانگ کانگ</td>\n",
- " <td>Hồng Kông</td>\n",
- " <td>香港</td>\n",
- " <td>香港</td>\n",
- " <td>MULTIPOLYGON (((114.22983 22.55581, 114.23471 ...</td>\n",
- " <td>香港特别行政区</td>\n",
- " <td>CN-91</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1</th>\n",
- " <td>Admin-0 country</td>\n",
- " <td>0</td>\n",
- " <td>3</td>\n",
- " <td>TWN</td>\n",
- " <td>Sovereign country</td>\n",
- " <td>Taiwan</td>\n",
- " <td>TWN</td>\n",
- " <td>TWN</td>\n",
- " <td>Taiwan</td>\n",
- " <td>Taiwan</td>\n",
- " <td>...</td>\n",
- " <td>Taiwan</td>\n",
- " <td>Çin Cumhuriyeti</td>\n",
- " <td>Республіка Китай</td>\n",
- " <td>تائیوان</td>\n",
- " <td>Đài Loan</td>\n",
- " <td>中华民国</td>\n",
- " <td>中華民國</td>\n",
- " <td>MULTIPOLYGON (((121.90577 24.95010, 121.83473 ...</td>\n",
- " <td>中国台湾</td>\n",
- " <td>CN-71</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2</th>\n",
- " <td>Admin-0 country</td>\n",
- " <td>0</td>\n",
- " <td>4</td>\n",
- " <td>CH1</td>\n",
- " <td>Country</td>\n",
- " <td>Macao S.A.R</td>\n",
- " <td>MAC</td>\n",
- " <td>MAC</td>\n",
- " <td>Macao</td>\n",
- " <td>Mac.</td>\n",
- " <td>...</td>\n",
- " <td>Macao</td>\n",
- " <td>Makao</td>\n",
- " <td>Аоминь</td>\n",
- " <td>مکاؤ</td>\n",
- " <td>Ma Cao</td>\n",
- " <td>澳门</td>\n",
- " <td>澳門</td>\n",
- " <td>MULTIPOLYGON (((113.55860 22.16303, 113.56943 ...</td>\n",
- " <td>澳门特别行政区</td>\n",
- " <td>CN-92</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "<p>3 rows × 51 columns</p>\n",
- "</div>"
- ],
- "text/plain": [
- " featurecla scalerank labelrank sov_a3 type \\\n",
- "0 Admin-0 country 0 4 CH1 Country \n",
- "1 Admin-0 country 0 3 TWN Sovereign country \n",
- "2 Admin-0 country 0 4 CH1 Country \n",
- "\n",
- " admin adm0_a3 gu_a3 name abbrev ... name_sv \\\n",
- "0 Hong Kong S.A.R. HKG HKG Hong Kong H.K. ... Hongkong \n",
- "1 Taiwan TWN TWN Taiwan Taiwan ... Taiwan \n",
- "2 Macao S.A.R MAC MAC Macao Mac. ... Macao \n",
- "\n",
- " name_tr name_uk name_ur name_vi name_zh_x \\\n",
- "0 Hong Kong Гонконг ہانگ کانگ Hồng Kông 香港 \n",
- "1 Çin Cumhuriyeti Республіка Китай تائیوان Đài Loan 中华民国 \n",
- "2 Makao Аоминь مکاؤ Ma Cao 澳门 \n",
- "\n",
- " name_zht geometry name_zh_y \\\n",
- "0 香港 MULTIPOLYGON (((114.22983 22.55581, 114.23471 ... 香港特别行政区 \n",
- "1 中華民國 MULTIPOLYGON (((121.90577 24.95010, 121.83473 ... 中国台湾 \n",
- "2 澳門 MULTIPOLYGON (((113.55860 22.16303, 113.56943 ... 澳门特别行政区 \n",
- "\n",
- " iso_3166_2 \n",
- "0 CN-91 \n",
- "1 CN-71 \n",
- "2 CN-92 \n",
- "\n",
- "[3 rows x 51 columns]"
- ]
- },
- "execution_count": 13,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"# Chinese Special Administrative Regions\n",
"china_sars = df_admin0_10m.loc[\n",
@@ -1183,34 +505,13 @@
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": null,
"metadata": {
"id": "PP6E24eEt1LV",
"outputId": "2621d5f1-1edc-42fc-e8df-8afd6a525cc6",
"scrolled": true
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot: >"
- ]
- },
- "execution_count": 14,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAA9EAAALDCAYAAAASWYNXAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/P9b71AAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzdd5hkZZU/8O+tnFPn3D0550AWBERRDKCygDnHVdTVZdVV0FV3/a24RtR1xQCCKCAZyWlCT+7pyd3TOXdXzun+/uiZZno6Vb4Vvp/n4WGmq+reMzPdVffc97znCKIoiiAiIiIiIiKiBcmkDoCIiIiIiIioUDCJJiIiIiIiIkoQk2giIiIiIiKiBDGJJiIiIiIiIkoQk2giIiIiIiKiBDGJJiIiIiIiIkoQk2giIiIiIiKiBDGJJiIiIiIiIkqQQuoAzhePxzE4OAij0QhBEKQOh4iIiIiIiIqcKIrw [...]
- "text/plain": [
- "<Figure size 1200x1200 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"import pandas as pd\n",
"\n",
@@ -1246,7 +547,7 @@
},
{
"cell_type": "code",
- "execution_count": 15,
+ "execution_count": null,
"metadata": {
"id": "LuNGgwiQt1LV"
},
@@ -1267,33 +568,12 @@
},
{
"cell_type": "code",
- "execution_count": 16,
+ "execution_count": null,
"metadata": {
"id": "v8ig_jQDt1LV",
"outputId": "3f10b14d-dde2-46d9-f4f6-6f4311fb3e73"
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot: >"
- ]
- },
- "execution_count": 16,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAAf0AAAPHCAYAAAAispBqAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/P9b71AAAACXBIWXMAAA9hAAAPYQGoP6dpAADyEklEQVR4nOzdd3ib5dk28FPbsq3pve3sOHuzR6GFMgstpYPR0vGW0tJC27fQ9bZfB92DbsrooNDJKpQ9AyFx9o7jJN7b1t7r+f5wMBl2LNmS7ueRzt9x5DgSW5auJJJOPfe4bpUkSRKIiIgo56lFF0BERETZwdAnIiLKEwx9IiKiPMHQJyIiyhMMfSIiojzB0CciIsoTDH0iIqI8oRVdwIkSiQT6+vpgMpmgUqlEl0NERCRLkiTB6/WiuroaanVy1/CyC/2+vj7U1dWJLoOIiEgRuru7UVtbm9RtZRf6JpMJwNhf [...]
- "text/plain": [
- "<Figure size 1200x1200 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"import pandas as pd\n",
"\n",
@@ -1323,33 +603,12 @@
},
{
"cell_type": "code",
- "execution_count": 17,
+ "execution_count": null,
"metadata": {
"id": "8zBzSIqQt1LV",
"outputId": "cc8b6fbf-accb-44ba-b80a-a837df398c96"
},
- "outputs": [
- {
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- "text/plain": [
- "<AxesSubplot: >"
- ]
- },
- "execution_count": 17,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAAKwAAAGdCAYAAACPYJhkAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/P9b71AAAACXBIWXMAAA9hAAAPYQGoP6dpAAAkJUlEQVR4nO3de1xUdf7H8fdcDzM4M9xkBnBAvOKtMEwizbL4yZbbZrq13W+ubi62mT5a5VFq7Wa41raVj0zdfeS2ZavrttVqbeVS0baLmndRQQ0UBGYAgXMGmBsz398f1KnJS4NyGL7weT4e5/FgzhwO3/G8PJwZzsxRMcYYCOGEOtIDIKQrKFjCFQqWcIWCJVyhYAlXKFjCFQqWcIWCJVzRRnoAlyoYDKK2thYmkwkqlSrSwyEXiTEGl8uF5ORkqNXn349yH2xtbS3sdnukh0G6SXV1NQYNGnTe+7kP1mQyAeh8 [...]
- "text/plain": [
- "<Figure size 640x480 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"norway = df[df['adm0_a3'] == 'NOR']\n",
"norway.plot()"
@@ -1357,33 +616,12 @@
},
{
"cell_type": "code",
- "execution_count": 18,
+ "execution_count": null,
"metadata": {
"id": "-LXcKKOjt1LV",
"outputId": "546a286e-9682-4f9a-c57e-b19250d88a34"
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot: >"
- ]
- },
- "execution_count": 18,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAAhIAAAGdCAYAAABHM5ovAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/P9b71AAAACXBIWXMAAA9hAAAPYQGoP6dpAACtAUlEQVR4nOzdd3iUVfbA8e/0TNqk9x4ILfTQpYpixd57byuKrgXddVfX1dXV1d+6a++rYkexgkhReq+B9N77JJlMn98fgYGQQhLSgPN5Hp41M+/c951skvfMveeeo3C5XC6EEEIIIbpB2d8XIIQQQogTlwQSQgghhOg2CSSEEEII0W0SSAghhBCi2ySQEEIIIUS3SSAhhBBCiG6TQEIIIYQQ3SaBhBBCCCG6Td3fF3A0p9NJcXExPj4+KBSK/r4cIYQQ4pTkcrmor68nIiICpbL9eYcBF0gUFxcTHR3d35chhBBC [...]
- "text/plain": [
- "<Figure size 640x480 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"norway_copy = norway.copy()\n",
"norway_copy = norway_copy[norway_copy[\"iso_3166_2\"] != \"NO-X01~\"]\n",
@@ -1404,33 +642,12 @@
},
{
"cell_type": "code",
- "execution_count": 19,
+ "execution_count": null,
"metadata": {
"id": "mznw0XOgt1LV",
"outputId": "7e8085bc-abd9-4592-f047-62fa1a45eb01"
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot: >"
- ]
- },
- "execution_count": 19,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAAigAAAFUCAYAAAAOBceiAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/P9b71AAAACXBIWXMAAA9hAAAPYQGoP6dpAAA5GUlEQVR4nO3deXxU5b0/8M/sk8yWTPZlskAgIUDYlyBaQVap4i1W788F21IVS/EqbUXaWq9FhZ/aS71W0etWfrVcKlgUF0RcwKosIRAJIAgSSMhKmGRmMsns5/dHZCSSZSYzSc5MPu/XK69XZs45z3znODifPOc5zyMRBEEAERERkYhIB7oAIiIiou9jQCEiIiLRYUAhIiIi0WFAISIiItFhQCEiIiLRYUAhIiIi0WFAISIiItFhQCEiIiLRkQ90Ad/n8/lQU1MDnU4HiUQy0OUQERFRAARBgM1mQ3p6OqTS0Ps/ [...]
- "text/plain": [
- "<Figure size 640x480 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"portugal = df[df.admin == 'Portugal']\n",
"portugal.plot()"
@@ -1438,33 +655,12 @@
},
{
"cell_type": "code",
- "execution_count": 20,
+ "execution_count": null,
"metadata": {
"id": "yfAO1qFrt1LV",
"outputId": "9151ce8f-2412-415b-da73-eeec613276d8"
},
- "outputs": [
- {
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- "text/plain": [
- "<AxesSubplot: >"
- ]
- },
- "execution_count": 20,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAApsAAAHRCAYAAAAluXLzAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/P9b71AAAACXBIWXMAAA9hAAAPYQGoP6dpAABoAklEQVR4nO3deXhU5d0+8Hv2mcw+2fcEAmENq0BwRxYpVVx+2sWKtdZWS/u6dFFefau2tdDS19a+Vlyrtkq1arVaF1xxQYQQtgAStoSELGSdJZPZ5/z+CARCttnOzCTcn+vKVXLmzHO+c4rJzXOeRSIIggAiIiIiIhFIE10AEREREY1eDJtEREREJBqGTSIiIiISDcMmEREREYmGYZOIiIiIRMOwSURERESiYdgkIiIiItHIE13AmYLBIBobG6HX6yGRSBJdDhERERGdQRAEOBwO5OTkQCoduu8y6cJmY2Mj8vPz [...]
- "text/plain": [
- "<Figure size 800x800 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"portugal_copy = portugal.copy()\n",
"reposition(portugal_copy, portugal.name == 'Azores', 11, 0)\n",
@@ -1483,33 +679,12 @@
},
{
"cell_type": "code",
- "execution_count": 21,
+ "execution_count": null,
"metadata": {
"id": "bbyDCO0Qt1LV",
"outputId": "f2a0594d-999b-4573-d008-5158f898a1c6"
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot: >"
- ]
- },
- "execution_count": 21,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAAdEAAAGdCAYAAABNWUmMAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/P9b71AAAACXBIWXMAAA9hAAAPYQGoP6dpAABrWklEQVR4nO3deXicZbk/8O87+75l35M2bdK0TfeUFFmEQqmIoCgcRSgczlE4BYSKS8/RI6hYfqKCCwJHEXHhsHmKqCACWhAoXdKFdF+z78ssmX15f39MMzTNJJl5Z7J/P9eV6yKTd573mWnIPc9234IoiiKIiIgoabLJ7gAREdF0xSBKREQkEYMoERGRRAyiREREEjGIEhERScQgSkREJBGDKBERkUQMokRERBIpJrsD54pEImhra4PRaIQgCJPdHSIimmVEUYTL5UJ+fj5kstHHmlMuiLa1taGoqGiyu0FERLNc [...]
- "text/plain": [
- "<Figure size 640x480 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"spain = df[df.admin == 'Spain']\n",
"spain.plot()"
@@ -1517,33 +692,12 @@
},
{
"cell_type": "code",
- "execution_count": 22,
+ "execution_count": null,
"metadata": {
"id": "yJ_Ueh7Rt1LV",
"outputId": "16fe59db-4be4-4e02-d37b-3098bdfa945a"
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot: >"
- ]
- },
- "execution_count": 22,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAAp0AAAGjCAYAAABuTa5+AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/P9b71AAAACXBIWXMAAA9hAAAPYQGoP6dpAACvZklEQVR4nOzdd3hkZ3k34N/p08409T7a1e5qtStt02q9tgE3MMaYbiCAIZSEEDohEPIRAqEHEgiBAKEFEhwCBoztEIwpNja2V9t7X/UuTe8zZ873x0iz6ppypknPfV1ciUcz57wqKz3zvk9hVFVVQQghhBBCSB6xxV4AIYQQQghZ/yjoJIQQQggheUdBJyGEEEIIyTsKOgkhhBBCSN5R0EkIIYQQQvKOgk5CCCGEEJJ3FHQSQgghhJC8o6CTEEIIIYTkHV/sBSyWSCQwOjoKWZbBMEyxl0MIIYQQQhZRVRU+nw/1 [...]
- "text/plain": [
- "<Figure size 800x800 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"spain_copy = spain.copy()\n",
"reposition(spain_copy, spain.name.isin(['Las Palmas', 'Santa Cruz de Tenerife']), 3, 7, 1, 1)\n",
@@ -1561,33 +715,12 @@
},
{
"cell_type": "code",
- "execution_count": 23,
+ "execution_count": null,
"metadata": {
"id": "60UpJMNwt1LV",
"outputId": "1c9ff3fa-83e6-411e-9dc3-0c718ee97d39"
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot: >"
- ]
- },
- "execution_count": 23,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAAh8AAAChCAYAAABnAt39AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/P9b71AAAACXBIWXMAAA9hAAAPYQGoP6dpAABT8klEQVR4nO3dd3ykVbnA8d87vbf0XrZle+8sdWVB4IIgIKIUERRQRBAE76VaQFDwqhRBL0UUBBUEpQjLLggs23sv6XVTJjOZTJ/3/jHJbCYzyaZnsznfz4cPu++88845k+y8z5zznOdIsizLCIIgCIIgjBDFaDdAEARBEITxRQQfgiAIgiCMKBF8CIIgCIIwokTwIQiCIAjCiBLBhyAIgiAII0oEH4IgCIIgjCgRfAiCIAiCMKJE8CEIgiAIwohSjXYDuotEItTU1GA2m5EkabSbIwiCIAhCH8iyjNvtJjs7G4Wi [...]
- "text/plain": [
- "<Figure size 640x480 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"russia = df[df.admin == 'Russia']\n",
"russia.plot()"
@@ -1604,34 +737,13 @@
},
{
"cell_type": "code",
- "execution_count": 24,
+ "execution_count": null,
"metadata": {
"id": "rfBkQf78t1LW",
"outputId": "8342e4b8-2483-4aac-8a79-e88d455297e2",
"scrolled": true
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot: >"
- ]
- },
- "execution_count": 24,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAABj0AAAMyCAYAAAA2aQPiAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/P9b71AAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzddXhk5fUH8O+4zySZuMsmm9WsuwKLu7v9sBZaKC0tFCm0SCkUt0JxpzgLLLDCuls2nmzcfTTj9/dHlkDYZGMzmcj38zw82czc+94z7CaT3POec0SCIAggIiIiIiIiIiIiIiIa5cTBDoCIiIiIiIiIiIiIiMgfmPQgIiIiIiIiIiIiIqIxgUkPIiIiIiIiIiIiIiIaE5j0ICIiIiIiIiIiIiKiMYFJDyIiIiIiIiIiIiIiGhOY9CAiIiIiIiIiIiIiojGBSQ8iIiIiIiIiIiIiIhoTmPQgIiIiIiIi [...]
- "text/plain": [
- "<Figure size 2000x2000 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"import shapely.geometry\n",
"import shapely.ops\n",
@@ -1673,6 +785,111 @@
"russia_copy.plot(figsize=(20, 20))\n"
]
},
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Turkey"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "#### Turkey Regions"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "turkey = df[df.admin == 'Turkey'][['iso_3166_2','geometry']]\n",
+ "turkey.plot()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from shapely.geometry import Polygon, MultiPolygon\n",
+ "\n",
+ "# NUTS - 1 Codes for Turkey and correspong region - city names\n",
+ "\n",
+ "region_dict = {\n",
+ " 'TR1': ['TR-34'],\n",
+ " 'TR2': ['TR-59', 'TR-22', 'TR-39', 'TR-10', 'TR-17'],\n",
+ " 'TR3': ['TR-35', 'TR-09', 'TR-20', 'TR-48', 'TR-45', 'TR-03', 'TR-43', 'TR-64'],\n",
+ " 'TR4': ['TR-16', 'TR-26', 'TR-11', 'TR-41', 'TR-54', 'TR-81', 'TR-14', 'TR-77'],\n",
+ " 'TR5': ['TR-06', 'TR-42', 'TR-70'],\n",
+ " 'TR6': ['TR-07', 'TR-32', 'TR-15', 'TR-01', 'TR-33', 'TR-31', 'TR-46', 'TR-80'],\n",
+ " 'TR7': ['TR-71', 'TR-68', 'TR-51', 'TR-50', 'TR-40', 'TR-38', 'TR-58', 'TR-66'],\n",
+ " 'TR8': ['TR-67', 'TR-78', 'TR-74', 'TR-37', 'TR-18', 'TR-57', 'TR-55', 'TR-60', 'TR-19', 'TR-05'],\n",
+ " 'TR9': ['TR-61', 'TR-52', 'TR-28', 'TR-53', 'TR-08', 'TR-29'],\n",
+ " 'TRA': ['TR-25', 'TR-24', 'TR-69', 'TR-04', 'TR-36', 'TR-76', 'TR-75'],\n",
+ " 'TRB': ['TR-44', 'TR-23', 'TR-12', 'TR-62', 'TR-65', 'TR-49', 'TR-13', 'TR-30'],\n",
+ " 'TRC': ['TR-27', 'TR-02', 'TR-79', 'TR-63', 'TR-21', 'TR-47', 'TR-72', 'TR-73', 'TR-56']}\n",
+ "\n",
+ "# Region names corresponding to NUTS-1\n",
+ "\n",
+ "region_name_dict = {'TR1':'İstanbul',\n",
+ " 'TR2':'Batı Marmara',\n",
+ " 'TR3':'Ege',\n",
+ " 'TR4':'Doğu Marmara',\n",
+ " 'TR5':'Batı Anadolu',\n",
+ " 'TR6':'Akdeniz',\n",
+ " 'TR7':'Orta Anadolu',\n",
+ " 'TR8':'Batı Karadeniz',\n",
+ " 'TR9':'Doğu Karadeniz',\n",
+ " 'TRA':'Kuzeydoğu Anadolu',\n",
+ " 'TRC':'Güneydoğu Anadolu',\n",
+ " 'TRB':'Ortadoğu Anadolu'\n",
+ " }\n",
+ "\n",
+ "\n",
+ "def create_region_polygons(region_dict, turkey_gdf):\n",
+ " # Create a reverse dictionary where city codes map to region codes\n",
+ " city_to_region = {city_code: region_code for region_code, city_codes in region_dict.items() for city_code in city_codes}\n",
+ "\n",
+ " # Create a new column 'REGION' in the GeoDataFrame that maps each city to its region\n",
+ " turkey_gdf['REGION'] = turkey_gdf['iso_3166_2'].map(city_to_region)\n",
+ "\n",
+ " # Dissolve the GeoDataFrame on the 'REGION' column to combine city polygons into region polygons\n",
+ " region_gdf = turkey_gdf.dissolve(by='REGION')\n",
+ "\n",
+ " # Reset the index of the new GeoDataFrame\n",
+ " region_gdf.reset_index(inplace=True)\n",
+ " \n",
+ " return region_gdf.drop(columns=['iso_3166_2'])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "turkey_regions = create_region_polygons(region_dict, turkey)\n",
+ "\n",
+ "# Rename 'REGION' column to 'ISO'\n",
+ "turkey_regions = turkey_regions.rename(columns={'REGION': 'iso_3166_2'})\n",
+ "\n",
+ "# Map the region_name_dict to a new 'NAME_1' column\n",
+ "turkey_regions['name'] = turkey_regions['iso_3166_2'].map(region_name_dict)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "turkey_regions.plot(figsize=(10, 7), edgecolor='black', column='name', legend=False, cmap='tab20')"
+ ]
+ },
{
"cell_type": "markdown",
"metadata": {
@@ -1684,33 +901,12 @@
},
{
"cell_type": "code",
- "execution_count": 25,
+ "execution_count": null,
"metadata": {
"id": "AcT31Diyt1LW",
"outputId": "cd6cc6ef-43ba-478e-b183-84eb7e003e17"
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot: >"
- ]
- },
- "execution_count": 25,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAAi0AAAFnCAYAAABqwnnlAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/P9b71AAAACXBIWXMAAA9hAAAPYQGoP6dpAAAxQUlEQVR4nO3de3RU9b3//9fcc53J/UYSCIICIogoGG/1kkqpbbWi39baViw/rDZaEdqjHK3W3zoWlvXUVlsvbS3aUxWL56cercrxYIvt1yAQ5RIUBLkkIZkESDKTC5nJzHx+f0RHcwBLkMlkm+djrb0W89l79n7PR2Rea8/n89k2Y4wRAADAMGdPdgEAAABHg9ACAAAsgdACAAAsgdACAAAsgdACAAAsgdACAAAsgdACAAAswZnsAj6rWCympqYmZWZmymazJbscAABwFIwx6uzsVElJiez2o7uHYvnQ0tTUpLKy [...]
- "text/plain": [
- "<Figure size 640x480 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"france = df[df.admin == 'France']\n",
"france.plot()"
@@ -1737,7 +933,7 @@
},
{
"cell_type": "code",
- "execution_count": 26,
+ "execution_count": null,
"metadata": {},
"outputs": [],
"source": [
@@ -1752,33 +948,12 @@
},
{
"cell_type": "code",
- "execution_count": 27,
+ "execution_count": null,
"metadata": {
"id": "yjKX9Pbbt1LW",
"outputId": "14caae01-b1b0-4775-a00e-a9e4f30fdf73"
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot: >"
- ]
- },
- "execution_count": 27,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAApsAAAKRCAYAAAAbCWICAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/P9b71AAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzdd3xb93kv/s9Z2JvgXqBIbWpLlO3YmXb2aOzWWXVGkzQ3bdOMtunNbdKMpk1+vW3S5Gbv0Syn2bEzbCfelqhJbUqiuDeJvYFzzu8PiBApgiTGOcAB+bxfr7xikcDBIQgCz/l+n8HIsiyDEEIIIYQQFbCVPgFCCCGEELJ+UbBJCCGEEEJUQ8EmIYQQQghRDQWbhBBCCCFENRRsEkIIIYQQ1VCwSQghhBBCVEPBJiGEEEIIUQ0Fm4QQQgghRDV8pU/gZpIkYWJiAlarFQzDVPp0CCGEEELITWRZRigU [...]
- "text/plain": [
- "<Figure size 800x800 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"france_copy = france.copy()\n",
"reposition(france_copy, france.name=='Guadeloupe', 57.4, 25.4, 1.5, 1.5)\n",
@@ -1799,30 +974,9 @@
},
{
"cell_type": "code",
- "execution_count": 49,
+ "execution_count": null,
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot: >"
- ]
- },
- "execution_count": 49,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAAa0AAAGdCAYAAAChLCyaAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/P9b71AAAACXBIWXMAAA9hAAAPYQGoP6dpAAB+I0lEQVR4nO3dd3xV9f0/8Ne5e+TO7L0YAZIAARJBcYGKUupqtUq1jrqKA+3Pqq2t2iW1tvar1Uqtq3WPuq2KqCgzEAgQIIGE7J3c3L3vPb8/AhdC1t333Jv38/HI40HuPffcz+Xmnvf9rPebYVmWBSGEEBIHeLFuACGEEOIvClqEEELiBgUtQgghcYOCFiGEkLhBQYsQQkjcoKBFCCEkblDQIoQQEjcoaBFCCIkbglg34FRerxddXV1QKBRgGCbWzSGEEBIilmVhMpmQlZUFHi+0vhLnglZXVxdyc3Nj3QxCCCFh [...]
- "text/plain": [
- "<Figure size 640x480 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"france_regions = france_copy.copy()\n",
"# Define the mapping from the departments to their parent division\n",
@@ -1954,7 +1108,7 @@
},
{
"cell_type": "code",
- "execution_count": 50,
+ "execution_count": null,
"metadata": {},
"outputs": [],
"source": [
@@ -1968,33 +1122,12 @@
},
{
"cell_type": "code",
- "execution_count": 51,
+ "execution_count": null,
"metadata": {
"id": "IS5Gcxgct1LW",
"outputId": "b8dbb05f-4ca9-4884-83ac-a7c169a9830a"
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot: >"
- ]
- },
- "execution_count": 51,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiMAAAFmCAYAAAC/V5rzAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/P9b71AAAACXBIWXMAAA9hAAAPYQGoP6dpAAAlV0lEQVR4nO3df3RU9Z3/8dfk15CQzOT3L5kExApomq+KNYw/WJRUFlyqa9zTo1TFL8uKJ2IF2mXzlVbhuzZ89RRc2YW6tYuelUhLD5T1J0XQeKyJ0pgYwJIKBRIMCVXMTAhkEsjn+4dlykhQJgl8yOT5OOeew3w+937m/Zlo7uvc+dwbhzHGCAAAwJIo2wUAAIChjTACAACsIowAAACrCCMAAMAqwggAALCKMAIAAKwijAAAAKsIIwAAwCrCCAAAsIowAgAArIoJZ+fHHntMixcvDmkbM2aMdu3aJUmaNGmSKisr [...]
- "text/plain": [
- "<Figure size 640x480 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"netherlands = df[df.admin == 'Netherlands']\n",
"netherlands.plot()"
@@ -2002,33 +1135,12 @@
},
{
"cell_type": "code",
- "execution_count": 52,
+ "execution_count": null,
"metadata": {
"id": "nwUGucQ1t1LW",
"outputId": "26c5aede-c587-4d88-cfe0-30ecaec9ede3"
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot: >"
- ]
- },
- "execution_count": 52,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAAkIAAAKTCAYAAAD1xWeKAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/P9b71AAAACXBIWXMAAA9hAAAPYQGoP6dpAAC1YklEQVR4nOzdd3hc1bU34N+Z3pt6by5yL7IlG0zHYJMChOoACQk3kEZCCCH1Jibhfk5yCZc0ShqENCAEU0INxcbgIhfZli1LVhv1Or3X8/0hW1i2yvRzZma9z6PH9mh0ZsmWZ9bsvfZaDMuyLAghhBBCspCA6wAIIYQQQrhCiRAhhBBCshYlQoQQQgjJWpQIEUIIISRrUSJECCGEkKxFiRAhhBBCshYlQoQQQgjJWiKuA0iEcDiMwcFBqNVqMAzDdTiEEEII4RDLsnA4HCguLoZAMPuaT0YkQoODgygrK+M6DEII [...]
- "text/plain": [
- "<Figure size 800x800 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"netherlands_copy = apply_bounds(netherlands, (-20, 60), (20, 20))\n",
"netherlands_copy.plot(figsize=(8, 8))"
@@ -2045,33 +1157,12 @@
},
{
"cell_type": "code",
- "execution_count": 53,
+ "execution_count": null,
"metadata": {
"id": "xfMx6gJmt1LW",
"outputId": "5278dfc3-3f51-4c21-84cc-922251b1d0cb"
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot: >"
- ]
- },
- "execution_count": 53,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWIAAAGdCAYAAAAomHm2AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/P9b71AAAACXBIWXMAAA9hAAAPYQGoP6dpAACafElEQVR4nOzddXxkZ7348c8Zd4t7spvdZN1361SoAYUWb6G4S6HIvXB/cKEXKRcpXNylQCmlLaVQL3VZ981K3H3c7fz+mGQ2k0ySiW2y2+f9eu2LzciZM6H7nWee8xVJlmUZQRAEYdEoFvsEBEEQXulEIBYEQVhkIhALgiAsMhGIBUEQFpkIxIIgCItMBGJBEIRFJgKxIAjCIhOBWBAEYZGpFvsExksmk/T09GA2m5EkabFPRxAEIYMsy/h8PkpLS1Eo5mctu+QCcU9PDxUVFYt9GoIgCFPq7OykvLx8Xo615AKx [...]
- "text/plain": [
- "<Figure size 640x480 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"uk = df[df.admin == 'United Kingdom']\n",
"uk.plot()"
@@ -2079,33 +1170,12 @@
},
{
"cell_type": "code",
- "execution_count": 54,
+ "execution_count": null,
"metadata": {
"id": "28VU40f9t1LW",
"outputId": "45585067-de13-4e02-8147-053ef0115d2d"
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<AxesSubplot: >"
- ]
- },
- "execution_count": 54,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAAaYAAAKTCAYAAABSLqyAAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/P9b71AAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzdd3xb1dkH8N+92nt47x07HkkcJ86GEMLeu2GvAqWM0gKFtrxA4YX2LQXKKmWVUSCMsjdhZMdOnOmVeO+tvdd9/5CtWLYkS7Zsyfb5fj79fBrpSjoOzn10znnO81AMwzAgCIIgiChBR3oABEEQBDEaCUwEQRBEVCGBiSAIgogqJDARBEEQUYUEJoIgCCKqkMBEEARBRBUSmAiCIIiowo70AMZyuVzo7u6GRCIBRVGRHg5BEAQRBgzDQK/XIzk5GTQdeE4UdYGpu7sbaWlpkR4GQRAEMQ06OjqQmpoa [...]
- "text/plain": [
- "<Figure size 800x800 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"uk_copy = apply_bounds(uk, (-10, 60), (20, 20))\n",
"uk_copy.plot(figsize=(8, 8))"
@@ -2122,7 +1192,7 @@
},
{
"cell_type": "code",
- "execution_count": 55,
+ "execution_count": null,
"metadata": {
"id": "5xOVyzXCt1LW"
},
@@ -2134,6 +1204,7 @@
" \"usa\": usa_copy,\n",
" \"france\": france_copy,\n",
" \"france_regions\": france_regions,\n",
+ " \"turkey_regions\": turkey_regions,\n",
" \"netherlands\": netherlands_copy,\n",
" \"norway\": norway_copy,\n",
" \"uk\": uk_copy,\n",
@@ -2145,138 +1216,25 @@
},
{
"cell_type": "code",
- "execution_count": 56,
+ "execution_count": null,
"metadata": {
"id": "tM1F5d0Vt1LW",
"outputId": "75abad9b-9442-4279-d66d-a0cd5fb97198"
},
- "outputs": [
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAB8oAAAagCAYAAAAH4dMtAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/P9b71AAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzdd3hTZfsH8O/Jbpom6R50D1poKaMMi7KRgvwQRQEVX0ERFAEBUQEHgoigoL5OQF5FVBBBBRWRoSzRAqVQ9ip00b139vP7ozQ2NN0jSXt/rivXRZ6cnNznkN4559zPeR6OMcZACCGEEEIIIYQQQgghhBBCCCGEdBI8SwdACCGEEEIIIYQQQgghhBBCCCGEtCcqlBNCCCGEEEIIIYQQQgghhBBCCOlUqFBOCCGEEEIIIYQQQgghhBBCCCGkU6FCOSGEEEIIIYQQQgghhBBCCCGEkE6FCuWEEEIIIYQQ [...]
- "text/plain": [
- "<Figure size 2000x2000 with 95 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"plot_all_countries()"
]
},
{
"cell_type": "code",
- "execution_count": 57,
+ "execution_count": null,
"metadata": {
"id": "8U3S1PUbt1LW",
"outputId": "cfb8d229-ffdf-473f-d516-6aa136e41a60",
"scrolled": true
},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "afghanistan\tSize 130.904\tSaving geojson for afghanistan...\n",
- "albania\tSize 5.325\tSaving geojson for albania...\n",
- "algeria\tSize 374.167\tSaving geojson for algeria...\n",
- "argentina\tSize 662.347\tSaving geojson for argentina...\n",
- "australia\tSaving geojson for australia...\n",
- "austria\tSize 20.068\tSaving geojson for austria...\n",
- "belgium\tSize 7.709\tSaving geojson for belgium...\n",
- "bolivia\tSize 161.264\tSaving geojson for bolivia...\n",
- "brazil\tSaving geojson for brazil...\n",
- "bulgaria\tSize 18.715\tSaving geojson for bulgaria...\n",
- "burundi\tSize 3.99\tSaving geojson for burundi...\n",
- "canada\tSaving geojson for canada...\n",
- "chile\tSize 1652.977\tSaving geojson for chile...\n",
- "china\tSaving geojson for china...\n",
- "colombia\tSize 264.526\tSaving geojson for colombia...\n",
- "costa rica\tSize 25.939\tSaving geojson for costa rica...\n",
- "cuba\tSize 37.185\tSaving geojson for cuba...\n",
- "cyprus\tSize 1.05\tSaving geojson for cyprus...\n",
- "denmark\tSize 22.461\tSaving geojson for denmark...\n",
- "dominican republic\tSize 8.806\tSaving geojson for dominican republic...\n",
- "ecuador\tSize 112.048\tSaving geojson for ecuador...\n",
- "egypt\tSize 117.982\tSaving geojson for egypt...\n",
- "el salvador\tSize 3.116\tSaving geojson for el salvador...\n",
- "estonia\tSize 13.694\tSaving geojson for estonia...\n",
- "ethiopia\tSize 172.021\tSaving geojson for ethiopia...\n",
- "france\tSize 148.331\tSaving geojson for france...\n",
- "france_regions\tSize 148.331\tSaving geojson for france_regions...\n",
- "finland\tSize 123.747\tSaving geojson for finland...\n",
- "germany\tSize 71.47\tSaving geojson for germany...\n",
- "guatemala\tSize 16.442\tSaving geojson for guatemala...\n",
- "haiti\tSize 5.882\tSaving geojson for haiti...\n",
- "honduras\tSize 27.669\tSaving geojson for honduras...\n",
- "iceland\tSize 34.959\tSaving geojson for iceland...\n",
- "india\tSaving geojson for india...\n",
- "indonesia\tSaving geojson for indonesia...\n",
- "iran\tSize 284.014\tSaving geojson for iran...\n",
- "italy\tSize 138.162\tSaving geojson for italy...\n",
- "japan\tSize 661.569\tSaving geojson for japan...\n",
- "jordan\tSize 18.16\tSaving geojson for jordan...\n",
- "kazakhstan\tSize 606.552\tSaving geojson for kazakhstan...\n",
- "kenya\tSize 77.61\tSaving geojson for kenya...\n",
- "korea\tSize 34.227\tSaving geojson for korea...\n",
- "kuwait\tSize 2.973\tSaving geojson for kuwait...\n",
- "kyrgyzstan\tSize 44.924\tSaving geojson for kyrgyzstan...\n",
- "latvia\tSize 17.456\tSaving geojson for latvia...\n",
- "liechtenstein\tSize 0.029\tSaving geojson for liechtenstein...\n",
- "lithuania\tSize 15.018\tSaving geojson for lithuania...\n",
- "malaysia\tSize 127.7\tSaving geojson for malaysia...\n",
- "mexico\tSize 575.302\tSaving geojson for mexico...\n",
- "morocco\tSize 231.84\tSaving geojson for morocco...\n",
- "myanmar\tSize 168.709\tSaving geojson for myanmar...\n",
- "netherlands\tSize 10.818\tSaving geojson for netherlands...\n",
- "nicaragua\tSize 21.415\tSaving geojson for nicaragua...\n",
- "nigeria\tSize 115.287\tSaving geojson for nigeria...\n",
- "norway\tSize 530.052\tSaving geojson for norway...\n",
- "oman\tSize 76.643\tSaving geojson for oman...\n",
- "pakistan\tSize 216.493\tSaving geojson for pakistan...\n",
- "panama\tSize 14.275\tSaving geojson for panama...\n",
- "papua new guinea\tSize 155.567\tSaving geojson for papua new guinea...\n",
- "paraguay\tSize 69.763\tSaving geojson for paraguay...\n",
- "peru\tSize 231.665\tSaving geojson for peru...\n",
- "philippines\tSize 159.114\tSaving geojson for philippines...\n",
- "portugal\tSize 105.727\tSaving geojson for portugal...\n",
- "poland\tSize 58.556\tSaving geojson for poland...\n",
- "puerto rico\tSize 1.616\tSaving geojson for puerto rico...\n",
- "qatar\tSize 1.385\tSaving geojson for qatar...\n",
- "russia\tSaving geojson for russia...\n",
- "rwanda\tSize 3.59\tSaving geojson for rwanda...\n",
- "saint barthelemy\tSize 0.004\tSaving geojson for saint barthelemy...\n",
- "saint martin\tSize 0.012\tSaving geojson for saint martin...\n",
- "saudi arabia\tSize 331.779\tSaving geojson for saudi arabia...\n",
- "singapore\tSize 0.067\tSaving geojson for singapore...\n",
- "slovenia\tSize 4.537\tSaving geojson for slovenia...\n",
- "spain\tSize 178.488\tSaving geojson for spain...\n",
- "sri lanka\tSize 8.728\tSaving geojson for sri lanka...\n",
- "sweden\tSize 178.774\tSaving geojson for sweden...\n",
- "switzerland\tSize 8.935\tSaving geojson for switzerland...\n",
- "syria\tSize 33.348\tSaving geojson for syria...\n",
- "tajikistan\tSize 34.112\tSaving geojson for tajikistan...\n",
- "tanzania\tSize 119.579\tSaving geojson for tanzania...\n",
- "thailand\tSize 122.959\tSaving geojson for thailand...\n",
- "timorleste\tSize 4.486\tSaving geojson for timorleste...\n",
- "turkey\tSize 120.204\tSaving geojson for turkey...\n",
- "turkmenistan\tSize 108.7\tSaving geojson for turkmenistan...\n",
- "uganda\tSize 31.083\tSaving geojson for uganda...\n",
- "uk\tSaving geojson for uk...\n",
- "ukraine\tSize 128.988\tSaving geojson for ukraine...\n",
- "united arab emirates\tSize 16.628\tSaving geojson for united arab emirates...\n",
- "uruguay\tSize 25.985\tSaving geojson for uruguay...\n",
- "usa\tSaving geojson for usa...\n",
- "uzbekistan\tSize 143.798\tSaving geojson for uzbekistan...\n",
- "venezuela\tSize 204.361\tSaving geojson for venezuela...\n",
- "vietnam\tSize 108.841\tSaving geojson for vietnam...\n",
- "zambia\tSize 115.483\tSaving geojson for zambia...\n",
- "Done. \n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"import shutil\n",
"\n",
@@ -2339,17 +1297,9 @@
},
{
"cell_type": "code",
- "execution_count": 58,
+ "execution_count": null,
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "TypeScript code written to src/countries.ts\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"# Function to convert country name to a valid JavaScript identifier\n",
"def to_js_identifier(name):\n",
@@ -2394,7 +1344,16 @@
" if (x === 'france_regions') {\n",
" return [x, 'France (regions)'];\n",
" }\n",
- " return [x, x.split('_').map((e) => e[0].toUpperCase() + e.slice(1)).join(' ')];\n",
+ " if (x === 'turkey_regions') {\n",
+ " return [x, 'Turkey (regions)'];\n",
+ " }\n",
+ " return [\n",
+ " x,\n",
+ " x\n",
+ " .split('_')\n",
+ " .map(e => e[0].toUpperCase() + e.slice(1))\n",
+ " .join(' '),\n",
+ " ];\n",
"});\n",
"\n",
"export default countries;\n",
@@ -2437,7 +1396,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.11.7"
+ "version": "3.11.8"
},
"vscode": {
"interpreter": {
diff --git a/superset-frontend/plugins/legacy-plugin-chart-country-map/src/countries.ts b/superset-frontend/plugins/legacy-plugin-chart-country-map/src/countries.ts
index 73657dd97a..9957e291c0 100755
--- a/superset-frontend/plugins/legacy-plugin-chart-country-map/src/countries.ts
+++ b/superset-frontend/plugins/legacy-plugin-chart-country-map/src/countries.ts
@@ -101,6 +101,7 @@ import tanzania from './countries/tanzania.geojson';
import thailand from './countries/thailand.geojson';
import timorleste from './countries/timorleste.geojson';
import turkey from './countries/turkey.geojson';
+import turkey_regions from './countries/turkey_regions.geojson';
import turkmenistan from './countries/turkmenistan.geojson';
import uganda from './countries/uganda.geojson';
import uk from './countries/uk.geojson';
@@ -198,6 +199,7 @@ export const countries = {
thailand,
timorleste,
turkey,
+ turkey_regions,
turkmenistan,
uganda,
uk,
@@ -221,6 +223,9 @@ export const countryOptions = Object.keys(countries).map(x => {
if (x === 'france_regions') {
return [x, 'France (regions)'];
}
+ if (x === 'turkey_regions') {
+ return [x, 'Turkey (regions)'];
+ }
return [
x,
x
diff --git a/superset-frontend/plugins/legacy-plugin-chart-country-map/src/countries/turkey_regions.geojson b/superset-frontend/plugins/legacy-plugin-chart-country-map/src/countries/turkey_regions.geojson
new file mode 100644
index 0000000000..70bdbb9485
--- /dev/null
+++ b/superset-frontend/plugins/legacy-plugin-chart-country-map/src/countries/turkey_regions.geojson
@@ -0,0 +1,18 @@
+{
+"type": "FeatureCollection",
+"crs": { "type": "name", "properties": { "name": "urn:ogc:def:crs:OGC:1.3:CRS84" } },
+"features": [
+{ "type": "Feature", "properties": { "ISO": "TR1", "NAME_1": "İstanbul" }, "geometry": { "type": "MultiPolygon", "coordinates": [ [ [ [ 29.25367272200009, 40.875474351000037 ], [ 29.144786004000082, 40.914129950000074 ], [ 29.028086785000085, 40.982123114000046 ], [ 29.00757897200009, 41.030503648000035 ], [ 29.062347852000073, 41.076320705000057 ], [ 29.090586785000085, 41.14093659100007 ], [ 29.069102410000085, 41.152777411000045 ], [ 29.16968834700009, 41.233099677000041 ], [ 29.23178 [...]
+{ "type": "Feature", "properties": { "ISO": "TR2", "NAME_1": "Batı Marmara" }, "geometry": { "type": "MultiPolygon", "coordinates": [ [ [ [ 26.060557488000086, 39.837591864000046 ], [ 26.083018425000091, 39.834947007000039 ], [ 26.074961785000085, 39.784898179000038 ], [ 25.978037957000083, 39.834173895000049 ], [ 26.060557488000086, 39.837591864000046 ] ] ], [ [ [ 26.012217644000089, 40.166571356000077 ], [ 26.012217644000089, 40.146063544000071 ], [ 25.990244988000086, 40.1369082700000 [...]
+{ "type": "Feature", "properties": { "ISO": "TR3", "NAME_1": "Ege" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 29.261204804558076, 36.293578581086649 ], [ 29.234629754000082, 36.324286200000074 ], [ 29.158457879000082, 36.356756903000075 ], [ 29.144704623000052, 36.349310614000046 ], [ 29.144704623000052, 36.377183335000041 ], [ 29.096364780000044, 36.39093659100007 ], [ 29.130381707000083, 36.411363023000035 ], [ 29.124196811000047, 36.453599351000037 ], [ 29.09636478000004 [...]
+{ "type": "Feature", "properties": { "ISO": "TR4", "NAME_1": "Doğu Marmara" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 30.863573845856308, 40.142795519297749 ], [ 30.906671990619827, 40.100575872778279 ], [ 30.922071567648686, 40.020012315116219 ], [ 30.945739373972913, 40.014637966568898 ], [ 31.081648390260966, 40.048124294900276 ], [ 31.191099074063004, 40.02409475426947 ], [ 31.246909620682402, 40.057710272910754 ], [ 31.389123163303339, 40.056883449711393 ], [ 31.43077 [...]
+{ "type": "Feature", "properties": { "ISO": "TR5", "NAME_1": "Batı Anadolu" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 34.148954705595145, 37.155019232851316 ], [ 34.002710401563775, 37.128819281884319 ], [ 33.870625441111201, 37.057738349445231 ], [ 33.761174758208483, 37.031435044791465 ], [ 33.619374626737624, 37.031796779997364 ], [ 33.539999626581505, 37.006578680961354 ], [ 33.371947869998166, 36.98800100414303 ], [ 33.232731560912782, 36.918005276422321 ], [ 33.20069 [...]
+{ "type": "Feature", "properties": { "ISO": "TR6", "NAME_1": "Akdeniz" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 36.659562625000092, 36.827243022000104 ], [ 36.639861288000077, 36.828089091000024 ], [ 36.643271932000061, 36.803646139000065 ], [ 36.603274374000137, 36.746957093000063 ], [ 36.569271281000056, 36.62014312700002 ], [ 36.565343872000085, 36.532499899000115 ], [ 36.531237427000065, 36.479014791000068 ], [ 36.552734823000094, 36.408166403000038 ], [ 36.5933524980 [...]
+{ "type": "Feature", "properties": { "ISO": "TR7", "NAME_1": "Orta Anadolu" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 34.512240025256915, 37.351983953996239 ], [ 34.489088982870214, 37.394927070028245 ], [ 34.389146762712926, 37.486471868781678 ], [ 34.394107700110226, 37.561066798693787 ], [ 34.456842888888218, 37.660311387760316 ], [ 34.445474074169169, 37.717129624732365 ], [ 34.300470005386444, 37.87528534584203 ], [ 34.20631554492644, 37.909934394156949 ], [ 34.173139 [...]
+{ "type": "Feature", "properties": { "ISO": "TR8", "NAME_1": "Batı Karadeniz" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 36.705181105423662, 40.862493191507554 ], [ 36.687507765271107, 40.836009019700498 ], [ 36.698876580889475, 40.806811835198005 ], [ 36.946820103365042, 40.720253811364273 ], [ 37.013379347079194, 40.698937283428847 ], [ 37.21967166471552, 40.697697048180203 ], [ 37.448804966376088, 40.575947374571683 ], [ 37.584093865939167, 40.569384466719725 ], [ 37.634 [...]
+{ "type": "Feature", "properties": { "ISO": "TR9", "NAME_1": "Doğu Karadeniz" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 39.833982375186451, 40.561012885536229 ], [ 39.867365349831005, 40.413580023998861 ], [ 39.860027297421823, 40.266948147239191 ], [ 39.811451450424101, 40.14395823838197 ], [ 39.869122349017175, 40.014818833722188 ], [ 39.78788699688738, 39.934797879318637 ], [ 39.622005649740913, 39.893766791204428 ], [ 39.385430942883659, 39.893327542532063 ], [ 39.2664 [...]
+{ "type": "Feature", "properties": { "ISO": "TRA", "NAME_1": "Kuzeydoğu Anadolu" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 44.45825019369147, 39.642520089430548 ], [ 44.414012085000138, 39.560893860000036 ], [ 44.404813680000132, 39.434389954000082 ], [ 44.316963745000066, 39.385297343000033 ], [ 44.269524781000086, 39.382868551000072 ], [ 44.176507203000085, 39.411548971000073 ], [ 44.061372111000139, 39.400283508000101 ], [ 44.01486332200011, 39.374083557000077 ], [ 44.0 [...]
+{ "type": "Feature", "properties": { "ISO": "TRB", "NAME_1": "Ortadoğu Anadolu" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 38.147677036166272, 39.072576606125438 ], [ 38.361720819160439, 39.150272122360548 ], [ 38.440889112842285, 39.119524645146214 ], [ 38.580932245126974, 39.101954657781221 ], [ 38.687902459330985, 39.022967231252721 ], [ 38.745676710711621, 39.03777252907895 ], [ 38.720355258888048, 39.157868557188124 ], [ 38.755598586405597, 39.172596339749248 ], [ 38.7 [...]
+{ "type": "Feature", "properties": { "ISO": "TRC", "NAME_1": "Güneydoğu Anadolu" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 37.522143502026204, 36.67359952678661 ], [ 37.446116984000128, 36.634199117000051 ], [ 37.241891724000141, 36.658590393000068 ], [ 37.104432414000087, 36.650993957000097 ], [ 37.053066040000147, 36.619936422000066 ], [ 37.014515422000045, 36.642260641000021 ], [ 37.018442831000129, 36.70664947500002 ], [ 36.964699341000141, 36.753830058000048 ], [ 36.6 [...]
+]
+}