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Merge pull request jupyter-widgets#422 from martinRenou/add_wealth_of…
…_nations_notebook Add wealth of nations notebook
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{ | ||
"cells": [ | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"import os\n", | ||
"import json\n", | ||
"\n", | ||
"import numpy as np\n", | ||
"import pandas as pd\n", | ||
"\n", | ||
"from ipywidgets import Dropdown\n", | ||
"\n", | ||
"from bqplot import Lines, Figure, LinearScale, DateScale, Axis\n", | ||
"\n", | ||
"from ipyleaflet import Map, GeoJSON, WidgetControl" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"data = pd.read_json(os.path.abspath('nations.json'))" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"def clean_data(data):\n", | ||
" for column in ['income', 'lifeExpectancy', 'population']:\n", | ||
" data = data.drop(data[data[column].apply(len) <= 4].index)\n", | ||
" return data\n", | ||
"\n", | ||
"def extrap_interp(data):\n", | ||
" data = np.array(data)\n", | ||
" x_range = np.arange(1800, 2009, 1.)\n", | ||
" y_range = np.interp(x_range, data[:, 0], data[:, 1])\n", | ||
" return y_range\n", | ||
"\n", | ||
"def extrap_data(data):\n", | ||
" for column in ['income', 'lifeExpectancy', 'population']:\n", | ||
" data[column] = data[column].apply(extrap_interp)\n", | ||
" return data" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"data = clean_data(data)\n", | ||
"data = extrap_data(data)" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"data" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"date_start = pd.datetime(1800, 12, 31)\n", | ||
"date_end = pd.datetime(2009, 12, 31)\n", | ||
"\n", | ||
"date_scale = DateScale(min=date_start, max=date_end)" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"date_data = pd.date_range(start=date_start, end=date_end, freq='A', normalize=True)" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"country_name = 'Angola'\n", | ||
"data_name = 'income'\n", | ||
"\n", | ||
"x_data = data[data.name == country_name][data_name].values[0]" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"x_scale = LinearScale()\n", | ||
"\n", | ||
"lines = Lines(x=date_data, y=x_data, scales={'x': date_scale, 'y': x_scale})\n", | ||
"\n", | ||
"ax_x = Axis(label='Year', scale=date_scale, num_ticks=10, tick_format='%Y')\n", | ||
"ax_y = Axis(label=data_name.capitalize(), scale=x_scale, orientation='vertical', side='left')\n", | ||
"\n", | ||
"figure = Figure(axes=[ax_x, ax_y], title=country_name, marks=[lines], animation_duration=500,\n", | ||
" layout={'max_height': '250px', 'max_width': '400px'})\n", | ||
"figure" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"def update_figure(country_name, data_name):\n", | ||
" lines.y = data[data.name == country_name][data_name].values[0]\n", | ||
" ax_y.label = data_name.capitalize()\n", | ||
" figure.title = country_name" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"country_name = 'Benin'\n", | ||
"data_name = 'income'\n", | ||
"\n", | ||
"update_figure(country_name, data_name)" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"country_name = 'Angola'\n", | ||
"data_name = 'population'\n", | ||
"\n", | ||
"update_figure(country_name, data_name)" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"with open('./countries.geo.json') as f:\n", | ||
" countries = json.load(f)" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"m = Map(zoom=3)\n", | ||
"\n", | ||
"geo = GeoJSON(data=countries, style={'fillColor': 'white', 'weight': 0.5}, hover_style={'fillColor': '#1f77b4'}, name='Countries')\n", | ||
"m.add_layer(geo)\n", | ||
"\n", | ||
"m" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"widget_control1 = WidgetControl(widget=figure, position='bottomright')\n", | ||
"\n", | ||
"m.add_control(widget_control1)\n", | ||
"\n", | ||
"def on_hover(event, feature, **kwargs):\n", | ||
" global country_name\n", | ||
"\n", | ||
" country_name = feature['properties']['name']\n", | ||
" update_figure(country_name, data_name)\n", | ||
"\n", | ||
"geo.on_hover(on_hover)" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"dropdown = Dropdown(\n", | ||
" options=['income', 'population', 'lifeExpectancy'],\n", | ||
" value=data_name,\n", | ||
" description='Plotting:'\n", | ||
")\n", | ||
"\n", | ||
"def on_click(change):\n", | ||
" global data_name\n", | ||
"\n", | ||
" data_name = change['new']\n", | ||
" update_figure(country_name, data_name)\n", | ||
"\n", | ||
"dropdown.observe(on_click, 'value')\n", | ||
"\n", | ||
"widget_control2 = WidgetControl(widget=dropdown, position='bottomleft')\n", | ||
"\n", | ||
"m.add_control(widget_control2)" | ||
] | ||
} | ||
], | ||
"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": "3.7.3" | ||
} | ||
}, | ||
"nbformat": 4, | ||
"nbformat_minor": 4 | ||
} |
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