Added notebook for mortality rate BC

.gitignore

@@ -2,4 +2,9 @@
 *.DS_Store
 *.idea/
 *.vs/
-*__pycache__/
+*__pycache__/
+*venv/
+*.html
+*.log
+*.png
+*.pdf

README.md

@@ -9,11 +9,17 @@ A python package without useful utility tools was developed to aid extraction
 and visualization. The package is compatible with `Python >= 3.8` and has the
 following dependencies:
 
-* pandas
-
 * numpy
 
-* matplotlib
+* folium
+
+* pycountry
+
+* geopandas
+
+* Pillow
+
+Note that these dependencies will be installed directly when launching the Jypyter Notebooks.
 
 ## Installation
 
@@ -31,8 +37,14 @@ Example application notebooks are available in the [apps/](https://github.com/an
 
 ## Troubleshoot
 
+1) Virtual environment activation
+
 To activate the virtual environment on Windows, instead of `source venv/bin/activate` run `./venv/Scripts/activate`.
 
+2) `ImportError: No module named selenium`
+
+To export the generated map as a PNG image, the [Firefox](https://www.mozilla.org/en-US/firefox/new/) explorer is required.
+
 ## License
 
 This repository has [MIT license](https://github.com/andreped/breast-cancer-stats/blob/main/LICENSE).

apps/breast_cancer_mortality_rate.ipynb

@@ -0,0 +1,94 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.1.2\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.2.1\u001b[0m\n",
+      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Install dependencies\n",
+    "!pip install -q geopandas folium pycountry Pillow selenium"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import folium\n",
+    "import pandas as pd\n",
+    "import pycountry\n",
+    "import io\n",
+    "from PIL import Image\n",
+    "\n",
+    "cancer_data = pd.read_csv(\"../data/SA_0000001439.csv\")\n",
+    "political_countries_url = (\n",
+    "    \"http://geojson.xyz/naturalearth-3.3.0/ne_50m_admin_0_countries.geojson\"\n",
+    ")\n",
+    "\n",
+    "# convert country code to full name\n",
+    "tmp = []\n",
+    "for x in cancer_data[\"COUNTRY\"]:\n",
+    "    try:\n",
+    "        tmp.append(pycountry.countries.get(alpha_3=x).name)\n",
+    "    except AttributeError:\n",
+    "        tmp.append(x)\n",
+    "cancer_data[\"COUNTRY\"] = tmp\n",
+    "\n",
+    "m = folium.Map(location=(30, 10), zoom_start=2, tiles=\"cartodb positron\")\n",
+    "folium.Choropleth(\n",
+    "    geo_data=political_countries_url,\n",
+    "    data=cancer_data,\n",
+    "    columns=[\"COUNTRY\", \"Numeric\"],\n",
+    "    key_on=\"feature.properties.name\",\n",
+    "    fill_color=\"Reds\",\n",
+    "    nan_fill_color=\"Grey\",\n",
+    "    fill_opacity=0.7,\n",
+    "    line_opacity=0.2,\n",
+    "    legend_name=\"Breast cancer mortality rate.\"\n",
+    ").add_to(m)\n",
+    "\n",
+    "# to export snapshot of map as PNG\n",
+    "img_data = m._to_png(5)\n",
+    "img = Image.open(io.BytesIO(img_data))\n",
+    "img.save('mortality_rate_breast_cancer.png')\n",
+    "\n",
+    "# to export as interactive viewer in HTML\n",
+    "m.save(\"mortality_rate_breast_cancer.html\")\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "venv",
+   "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": "3.8.16"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

assets/requirements.txt

@@ -1,4 +1,5 @@
-pandas
-numpy
-matplotlib
-setuptools
+geopandas
+folium
+pycountry
+Pillow
+selenium