%s
Total FB pop: %d\" % (row[\"name\"], row[\"both_18-_AllDevices\"])\n", " popup = folium.Popup(html, max_width=450, min_width=450)\n", "\n", " folium.Marker([row[\"lat\"], row[\"lng\"]], popup=popup, tooltip=tooltip).add_to(m)\n", "m" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "When any of the locations is clicked, a pop up showing the city name and the total Facebook audience is shown.\n", "This number is based on the column **both_18-_AllDevices**, and as [explaned before](content:post_process_collection), it represents both male and female audience aged at least 18 years old and using any network to connect to Facebook. \n", "\n", "```{warning}\n", "Note that the correct column name will depend on the criteria used in the collection!\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Improving the Basic Map" ] }, { "cell_type": "markdown", "metadata": { "ExecuteTime": { "end_time": "2020-09-01T03:01:11.277294Z", "start_time": "2020-09-01T03:01:11.271663Z" } }, "source": [ "Next we will define a few functions to be able to plot a much more interesting map.\n", "The functions ``getPie`` and ``getPyramid`` can be used in other contexts as well.\n", "The parameter `get_encoded` is decide if these functions should return an image HTML encoded or not. For the maps, we will use `get_encoded=True`." ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "ExecuteTime": { "end_time": "2021-02-24T11:36:23.242631Z", "start_time": "2021-02-24T11:36:23.236069Z" } }, "outputs": [], "source": [ "def getPie(labels, sizes, explode=None, title=None, get_encoded=True):\n", " \n", " # Pie chart, where the slices will be ordered and plotted counter-clockwise:\n", " # Examples:\n", " # labels = 'Frogs', 'Hogs', 'Dogs', 'Logs'\n", " # sizes = [15, 30, 45, 10]\n", " # explode = (0, 0.1, 0, 0) # only \"explode\" the 2nd slice (i.e. 'Hogs')\n", "\n", " \n", " def label_formant(pct, allvals):\n", " absolute = int(pct/100.*np.sum(allvals))\n", " return \"{:.1f}%\\n({:,d})\".format(pct, absolute)\n", " \n", " # TODO: make it like a doughout\n", " # https://matplotlib.org/3.1.1/gallery/pie_and_polar_charts/pie_and_donut_labels.html\n", " \n", " fig1, ax1 = plt.subplots(figsize=(2,2))\n", " ax1.pie(sizes, explode=explode, labels=labels,\n", " autopct=lambda pct: label_formant(pct, sizes),\n", " shadow=True, startangle=90, counterclock=False, \n", " wedgeprops = {'linewidth' : 2, 'edgecolor': \"black\", }\n", " )\n", " \n", " if title:\n", " ax1.set_title(title)\n", " ax1.axis('equal') # Equal aspect ratio ensures that pie is drawn as a circle.\n", "\n", " if get_encoded:\n", " img_buffer = io.BytesIO()\n", " plt.savefig(img_buffer, format='png', transparent=True, bbox_inches=\"tight\")\n", " img_buffer.seek(0)\n", " plt.close()\n", " \n", " return base64.b64encode(img_buffer.getvalue()).decode('UTF-8')\n", " \n", " else:\n", " return plt\n", " " ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "ExecuteTime": { "end_time": "2021-02-24T11:36:24.008666Z", "start_time": "2021-02-24T11:36:23.907173Z" } }, "outputs": [ { "data": { "text/plain": [ "Location: {name} ({lat:.1f}, {lng:.1f})
\n", "Total Population: {total_pop:,}
\n", " \n", " \n", "Gender Distribution:
\n", "
Age Distribution
\n", "
Age Distribution per Gender
\n", "
\n",
" 
\n",
" Connectivity <\\h5>\n",
" 
Connectivity per Gender <\\h5>\n",
" 
"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# There are many options for tile. Here we are using the first one, openstreetmaps\n",
"tile_options = ['openstreetmap', 'cartodbpositron', 'Mapbox Bright', \n",
" 'Stamen Terrain', 'Stamen Toner', 'Stamen Watercolor',\n",
" 'Mapbox Control Room', 'CartoDB dark_matter', ]\n",
"\n",
"tiles = tile_options[0]\n",
"\n",
"m = folium.Map(location=[0, 0], zoom_start=2, tiles=tiles, control_scale = True)\n",
"\n",
"\n",
"for idx, row in df.iterrows():\n",
" html = getHTML(row)\n",
" popup = folium.Popup(html, max_width=450, min_width=450)\n",
"\n",
" tooltip = '%s!' % (row[\"name\"])\n",
"\n",
" folium.Marker([row[\"lat\"], row[\"lng\"]], popup=popup, tooltip=tooltip).add_to(m)\n",
"\n",
"m"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"ExecuteTime": {
"end_time": "2020-09-23T04:22:14.183755Z",
"start_time": "2020-09-23T04:22:13.483670Z"
}
},
"outputs": [],
"source": [
"# It is much easier to see the outcome of this notebook as a HTML file.\n",
"m.save('connetivity_top5_cities.html')"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.8.3"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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