From c6542f083cb9f1ff0ab8c45e6e9f5606e59bc7b0 Mon Sep 17 00:00:00 2001 From: ryanbaumann Date: Wed, 28 Mar 2018 22:12:40 -0700 Subject: [PATCH] updated examples and organization of examples --- examples/choropleth-viz-example.ipynb | 191 - .../data/2010_us_population_by_postcode.csv | 33093 ++++++++++++++++ examples/{ => data}/cdec.csv | 0 examples/{ => data}/cdec.geojson | 0 examples/{ => data}/mosaic.png | Bin examples/{ => data}/points.csv | 0 examples/data/points1.geojson | 3175 ++ examples/{ => data}/us-states.geojson | 0 .../notebooks/choropleth-viz-example.ipynb | 1812 + .../image-vis-type-example.ipynb | 87 +- .../point-viz-categorical-example.ipynb | 157 +- .../point-viz-types-example.ipynb | 77 +- .../rastertile-viz-type-example.ipynb | 39 +- .../{ => notebooks}/usgs-earthquakes.ipynb | 0 examples/points1.geojson | 3175 -- examples/{ => screenshots}/screenshot.png | Bin ...tion_choropleth_mapbox-gl-js-v0.44.1.ipynb | 451 + 17 files changed, 38738 insertions(+), 3519 deletions(-) delete mode 100644 examples/choropleth-viz-example.ipynb create mode 100644 examples/data/2010_us_population_by_postcode.csv rename examples/{ => data}/cdec.csv (100%) rename examples/{ => data}/cdec.geojson (100%) rename examples/{ => data}/mosaic.png (100%) rename examples/{ => data}/points.csv (100%) create mode 100644 examples/data/points1.geojson rename examples/{ => data}/us-states.geojson (100%) create mode 100644 examples/notebooks/choropleth-viz-example.ipynb rename examples/{ => notebooks}/image-vis-type-example.ipynb (55%) rename examples/{ => notebooks}/point-viz-categorical-example.ipynb (99%) rename examples/{ => notebooks}/point-viz-types-example.ipynb (97%) rename examples/{ => notebooks}/rastertile-viz-type-example.ipynb (93%) rename examples/{ => notebooks}/usgs-earthquakes.ipynb (100%) delete mode 100644 examples/points1.geojson rename examples/{ => screenshots}/screenshot.png (100%) create mode 100644 examples/us_population_choropleth_mapbox-gl-js-v0.44.1.ipynb diff --git a/examples/choropleth-viz-example.ipynb b/examples/choropleth-viz-example.ipynb deleted file mode 100644 index 898c8fb..0000000 --- a/examples/choropleth-viz-example.ipynb +++ /dev/null @@ -1,191 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Mapboxgl Python Library\n", - "\n", - "https://github.com/mapbox/mapboxgl-jupyter" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import os\n", - "from mapboxgl.viz import *\n", - "from mapboxgl.utils import *\n", - "\n", - "# Must be a public token, starting with `pk`\n", - "token = os.getenv('MAPBOX_ACCESS_TOKEN')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Choropleths with interpolated color assignment from GeoJSON source" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "# create choropleth from polygon features stored as GeoJSON\n", - "viz = ChoroplethViz('us-states.geojson', \n", - " color_property='density',\n", - " color_stops=create_color_stops([0, 50, 100, 500, 1500], colors='YlOrRd'),\n", - " color_function_type='interpolate',\n", - " line_stroke='--',\n", - " line_color='rgb(128,0,38)',\n", - " line_width=1,\n", - " opacity=0.8,\n", - " center=(-96, 37.8),\n", - " zoom=3,\n", - " below_layer='waterway-label'\n", - " )\n", - "viz.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Choropleths with match-type color scheme from GeoJSON source" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "match_color_stops = [\n", - " ['Massachusetts', 'rgb(46,204,113)'],\n", - " ['Utah', 'rgb(231,76,60)'],\n", - " ['California', 'rgb(142,68,173)'],\n", - "]\n", - "\n", - "viz = ChoroplethViz('us-states.geojson', \n", - " color_property='name', \n", - " color_stops = match_color_stops, \n", - " color_function_type = 'match', \n", - " color_default = 'rgba(52,73,94,0.5)', \n", - " opacity=0.8, \n", - " center = (-96, 37.8), \n", - " zoom = 3, \n", - " below_layer = 'waterway-label'\n", - " )\n", - "viz.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Vector polygon source with data-join technique\n", - "\n", - "In this configuration, properties in JSON data are used to calculate colors to style polygons from the vector source." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# must be JSON object (need to extend to use referenced JSON file)\n", - "data = [{\"id\": \"01\", \"name\": \"Alabama\", \"density\": 94.65}, {\"id\": \"02\", \"name\": \"Alaska\", \"density\": 1.264}, {\"id\": \"04\", \"name\": \"Arizona\", \"density\": 57.05}, {\"id\": \"05\", \"name\": \"Arkansas\", \"density\": 56.43}, {\"id\": \"06\", \"name\": \"California\", \"density\": 241.7}, {\"id\": \"08\", \"name\": \"Colorado\", \"density\": 49.33}, {\"id\": \"09\", \"name\": \"Connecticut\", \"density\": 739.1}, {\"id\": \"10\", \"name\": \"Delaware\", \"density\": 464.3}, {\"id\": \"11\", \"name\": \"District of Columbia\", \"density\": 10065}, {\"id\": \"12\", \"name\": \"Florida\", \"density\": 353.4}, {\"id\": \"13\", \"name\": \"Georgia\", \"density\": 169.5}, {\"id\": \"15\", \"name\": \"Hawaii\", \"density\": 214.1}, {\"id\": \"16\", \"name\": \"Idaho\", \"density\": 19.15}, {\"id\": \"17\", \"name\": \"Illinois\", \"density\": 231.5}, {\"id\": \"18\", \"name\": \"Indiana\", \"density\": 181.7}, {\"id\": \"19\", \"name\": \"Iowa\", \"density\": 54.81}, {\"id\": \"20\", \"name\": \"Kansas\", \"density\": 35.09}, {\"id\": \"21\", \"name\": \"Kentucky\", \"density\": 110}, {\"id\": \"22\", \"name\": \"Louisiana\", \"density\": 105}, {\"id\": \"23\", \"name\": \"Maine\", \"density\": 43.04}, {\"id\": \"24\", \"name\": \"Maryland\", \"density\": 596.3}, {\"id\": \"25\", \"name\": \"Massachusetts\", \"density\": 840.2}, {\"id\": \"26\", \"name\": \"Michigan\", \"density\": 173.9}, {\"id\": \"27\", \"name\": \"Minnesota\", \"density\": 67.14}, {\"id\": \"28\", \"name\": \"Mississippi\", \"density\": 63.5}, {\"id\": \"29\", \"name\": \"Missouri\", \"density\": 87.26}, {\"id\": \"30\", \"name\": \"Montana\", \"density\": 6.858}, {\"id\": \"31\", \"name\": \"Nebraska\", \"density\": 23.97}, {\"id\": \"32\", \"name\": \"Nevada\", \"density\": 24.8}, {\"id\": \"33\", \"name\": \"New Hampshire\", \"density\": 147}, {\"id\": \"34\", \"name\": \"New Jersey\", \"density\": 1189}, {\"id\": \"35\", \"name\": \"New Mexico\", \"density\": 17.16}, {\"id\": \"36\", \"name\": \"New York\", \"density\": 412.3}, {\"id\": \"37\", \"name\": \"North Carolina\", \"density\": 198.2}, {\"id\": \"38\", \"name\": \"North Dakota\", \"density\": 9.916}, {\"id\": \"39\", \"name\": \"Ohio\", \"density\": 281.9}, {\"id\": \"40\", \"name\": \"Oklahoma\", \"density\": 55.22}, {\"id\": \"41\", \"name\": \"Oregon\", \"density\": 40.33}, {\"id\": \"42\", \"name\": \"Pennsylvania\", \"density\": 284.3}, {\"id\": \"44\", \"name\": \"Rhode Island\", \"density\": 1006}, {\"id\": \"45\", \"name\": \"South Carolina\", \"density\": 155.4}, {\"id\": \"46\", \"name\": \"South Dakota\", \"density\": 98.07}, {\"id\": \"47\", \"name\": \"Tennessee\", \"density\": 88.08}, {\"id\": \"48\", \"name\": \"Texas\", \"density\": 98.07}, {\"id\": \"49\", \"name\": \"Utah\", \"density\": 34.3}, {\"id\": \"50\", \"name\": \"Vermont\", \"density\": 67.73}, {\"id\": \"51\", \"name\": \"Virginia\", \"density\": 204.5}, {\"id\": \"53\", \"name\": \"Washington\", \"density\": 102.6}, {\"id\": \"54\", \"name\": \"West Virginia\", \"density\": 77.06}, {\"id\": \"55\", \"name\": \"Wisconsin\", \"density\": 105.2}, {\"id\": \"56\", \"name\": \"Wyoming\", \"density\": 5.851}, {\"id\": \"72\", \"name\": \"Puerto Rico\", \"density\": 1082}]\n", - "\n", - "# create choropleth map with vector source styling use data in JSON object\n", - "viz = ChoroplethViz(data, \n", - " vector_url='mapbox://mapbox.us_census_states_2015',\n", - " vector_layer_name='states',\n", - " vector_join_property='STATEFP',\n", - " data_join_property='id',\n", - " color_property='density',\n", - " color_stops=create_color_stops([0, 50, 100, 500, 1500], colors='YlOrRd'),\n", - " line_stroke='dashed',\n", - " line_color='rgb(128,0,38)',\n", - " opacity=0.8,\n", - " center=(-96, 37.8),\n", - " zoom=3,\n", - " below_layer='waterway-label'\n", - " )\n", - "viz.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Vector polygon source with data-join technique, categorical color scheme" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# must be JSON object (need to extend to use referenced JSON file)\n", - "data = [{\"id\": \"01\", \"name\": \"Alabama\", \"density\": 94.65}, {\"id\": \"02\", \"name\": \"Alaska\", \"density\": 1.264}, {\"id\": \"04\", \"name\": \"Arizona\", \"density\": 57.05}, {\"id\": \"05\", \"name\": \"Arkansas\", \"density\": 56.43}, {\"id\": \"06\", \"name\": \"California\", \"density\": 241.7}, {\"id\": \"08\", \"name\": \"Colorado\", \"density\": 49.33}, {\"id\": \"09\", \"name\": \"Connecticut\", \"density\": 739.1}, {\"id\": \"10\", \"name\": \"Delaware\", \"density\": 464.3}, {\"id\": \"11\", \"name\": \"District of Columbia\", \"density\": 10065}, {\"id\": \"12\", \"name\": \"Florida\", \"density\": 353.4}, {\"id\": \"13\", \"name\": \"Georgia\", \"density\": 169.5}, {\"id\": \"15\", \"name\": \"Hawaii\", \"density\": 214.1}, {\"id\": \"16\", \"name\": \"Idaho\", \"density\": 19.15}, {\"id\": \"17\", \"name\": \"Illinois\", \"density\": 231.5}, {\"id\": \"18\", \"name\": \"Indiana\", \"density\": 181.7}, {\"id\": \"19\", \"name\": \"Iowa\", \"density\": 54.81}, {\"id\": \"20\", \"name\": \"Kansas\", \"density\": 35.09}, {\"id\": \"21\", \"name\": \"Kentucky\", \"density\": 110}, {\"id\": \"22\", \"name\": \"Louisiana\", \"density\": 105}, {\"id\": \"23\", \"name\": \"Maine\", \"density\": 43.04}, {\"id\": \"24\", \"name\": \"Maryland\", \"density\": 596.3}, {\"id\": \"25\", \"name\": \"Massachusetts\", \"density\": 840.2}, {\"id\": \"26\", \"name\": \"Michigan\", \"density\": 173.9}, {\"id\": \"27\", \"name\": \"Minnesota\", \"density\": 67.14}, {\"id\": \"28\", \"name\": \"Mississippi\", \"density\": 63.5}, {\"id\": \"29\", \"name\": \"Missouri\", \"density\": 87.26}, {\"id\": \"30\", \"name\": \"Montana\", \"density\": 6.858}, {\"id\": \"31\", \"name\": \"Nebraska\", \"density\": 23.97}, {\"id\": \"32\", \"name\": \"Nevada\", \"density\": 24.8}, {\"id\": \"33\", \"name\": \"New Hampshire\", \"density\": 147}, {\"id\": \"34\", \"name\": \"New Jersey\", \"density\": 1189}, {\"id\": \"35\", \"name\": \"New Mexico\", \"density\": 17.16}, {\"id\": \"36\", \"name\": \"New York\", \"density\": 412.3}, {\"id\": \"37\", \"name\": \"North Carolina\", \"density\": 198.2}, {\"id\": \"38\", \"name\": \"North Dakota\", \"density\": 9.916}, {\"id\": \"39\", \"name\": \"Ohio\", \"density\": 281.9}, {\"id\": \"40\", \"name\": \"Oklahoma\", \"density\": 55.22}, {\"id\": \"41\", \"name\": \"Oregon\", \"density\": 40.33}, {\"id\": \"42\", \"name\": \"Pennsylvania\", \"density\": 284.3}, {\"id\": \"44\", \"name\": \"Rhode Island\", \"density\": 1006}, {\"id\": \"45\", \"name\": \"South Carolina\", \"density\": 155.4}, {\"id\": \"46\", \"name\": \"South Dakota\", \"density\": 98.07}, {\"id\": \"47\", \"name\": \"Tennessee\", \"density\": 88.08}, {\"id\": \"48\", \"name\": \"Texas\", \"density\": 98.07}, {\"id\": \"49\", \"name\": \"Utah\", \"density\": 34.3}, {\"id\": \"50\", \"name\": \"Vermont\", \"density\": 67.73}, {\"id\": \"51\", \"name\": \"Virginia\", \"density\": 204.5}, {\"id\": \"53\", \"name\": \"Washington\", \"density\": 102.6}, {\"id\": \"54\", \"name\": \"West Virginia\", \"density\": 77.06}, {\"id\": \"55\", \"name\": \"Wisconsin\", \"density\": 105.2}, {\"id\": \"56\", \"name\": \"Wyoming\", \"density\": 5.851}, {\"id\": \"72\", \"name\": \"Puerto Rico\", \"density\": 1082}]\n", - "\n", - "match_color_stops = [\n", - " ['Massachusetts', 'rgb(46,204,113)'],\n", - " ['Utah', 'rgb(231,76,60)'],\n", - " ['California', 'rgb(142,68,173)'],\n", - "]\n", - "\n", - "# create choropleth map with vector source styling use data in JSON object\n", - "viz = ChoroplethViz(data, \n", - " vector_url='mapbox://mapbox.us_census_states_2015',\n", - " vector_layer_name='states',\n", - " vector_join_property='STATEFP',\n", - " data_join_property='id',\n", - " color_property='name',\n", - " color_stops=match_color_stops,\n", - " color_default = 'rgba(52,73,94,0.5)', \n", - " opacity=0.8,\n", - " center=(-96, 37.8),\n", - " zoom=3,\n", - " below_layer='waterway-label'\n", - " )\n", - "viz.show()" - ] - } - ], - "metadata": { - "anaconda-cloud": { - "attach-environment": true, - "environment": "Root", - "summary": "Mapboxgl Python Data Visualization example" - }, - "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": "3.6.1" - } - }, - "nbformat": 4, - "nbformat_minor": 1 -} diff --git a/examples/data/2010_us_population_by_postcode.csv b/examples/data/2010_us_population_by_postcode.csv new file mode 100644 index 0000000..2ba44b2 --- /dev/null +++ b/examples/data/2010_us_population_by_postcode.csv @@ -0,0 +1,33093 @@ +Zip Code ZCTA,2010 Census Population +01001,16769 +01002,29049 +01003,10372 +01005,5079 +01007,14649 +01008,1263 +01009,741 +01010,3609 +01011,1370 +01012,661 +01013,23188 +01020,29668 +01022,2451 +01026,946 +01027,17660 +01028,15720 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{"type": "Point", "coordinates": [-97.412, 32.645]}, "properties": {"Avg Medicare Payments": 12847.445, "Avg Covered Charges": 76782.92, "date": "8/19/22 12:00 AM"}} +,{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-106.265, 31.79]}, "properties": {"Avg Medicare Payments": 7230.524, "Avg Covered Charges": 61648.217, "date": "8/20/22 12:00 AM"}} +,{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-96.771, 32.875]}, "properties": {"Avg Medicare Payments": 11771.823, "Avg Covered Charges": 37821.13, "date": "8/21/22 12:00 AM"}} +,{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-101.903, 33.617]}, "properties": {"Avg Medicare Payments": 5176.948, "Avg Covered Charges": 10102.53, "date": "8/22/22 12:00 AM"}} +,{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-97.762, 33.22]}, "properties": {"Avg Medicare Payments": 4435.164, "Avg Covered Charges": 17513.027, "date": "8/23/22 12:00 AM"}} +,{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-95.62, 29.605]}, "properties": {"Avg Medicare Payments": 9660.143, "Avg Covered Charges": 48044.354, "date": "8/24/22 12:00 AM"}} +,{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-98.59, 29.53]}, "properties": {"Avg Medicare Payments": 18004.7, "Avg Covered Charges": 78096.005, "date": "8/25/22 12:00 AM"}} +,{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-98.475, 29.616]}, "properties": {"Avg Medicare Payments": 6957.479, "Avg Covered Charges": 40209.005, "date": "8/26/22 12:00 AM"}} +,{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-97.854, 30.008]}, "properties": {"Avg Medicare Payments": 7775.728, "Avg Covered Charges": 50232.53, "date": "8/27/22 12:00 AM"}} +,{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-95.459, 30.203]}, "properties": {"Avg Medicare Payments": 22846.092, "Avg Covered Charges": 72005.962, "date": "8/28/22 12:00 AM"}} +,{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-96.569, 32.779]}, "properties": {"Avg Medicare Payments": 10129.047, "Avg Covered Charges": 41962.343, "date": "8/29/22 12:00 AM"}} +,{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-97.375, 27.686]}, "properties": {"Avg Medicare Payments": 9346.575, "Avg Covered Charges": 53932.705, "date": "8/30/22 12:00 AM"}} +,{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-97.117, 32.683]}, "properties": {"Avg Medicare Payments": 12467.915, "Avg Covered Charges": 66848.12, "date": "8/31/22 12:00 AM"}} +,{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-97.068, 33.046]}, "properties": {"Avg Medicare Payments": 5686.26, "Avg Covered Charges": 30620.551, "date": "9/1/22 12:00 AM"}} +,{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-96.723, 33.177]}, "properties": {"Avg Medicare Payments": 8709.45, "Avg Covered Charges": 32115.5, "date": "9/2/22 12:00 AM"}} +,{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-97.116, 32.748]}, "properties": {"Avg Medicare Payments": 3945.66, "Avg Covered Charges": 26435.207, "date": "9/3/22 12:00 AM"}} +,{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-95.478, 29.651]}, "properties": {"Avg Medicare Payments": 3894.55, "Avg Covered Charges": 9132.27, "date": "9/4/22 12:00 AM"}} +,{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-96.829, 32.985]}, "properties": {"Avg Medicare Payments": 9176.108, "Avg Covered Charges": 26091.035, "date": "9/5/22 12:00 AM"}} +,{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-95.568, 29.989]}, "properties": {"Avg Medicare Payments": 4116.482, "Avg Covered Charges": 33840.385, "date": "9/6/22 12:00 AM"}} +,{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-96.603, 33.677]}, "properties": {"Avg Medicare Payments": 8491.44, "Avg Covered Charges": 33310.61, "date": "9/7/22 12:00 AM"}} +,{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-95.697, 29.787]}, "properties": {"Avg Medicare Payments": 2743.57, "Avg Covered Charges": 22316.35, "date": "9/8/22 12:00 AM"}} +]} \ No newline at end of file diff --git a/examples/us-states.geojson b/examples/data/us-states.geojson similarity index 100% rename from examples/us-states.geojson rename to examples/data/us-states.geojson diff --git a/examples/notebooks/choropleth-viz-example.ipynb b/examples/notebooks/choropleth-viz-example.ipynb new file mode 100644 index 0000000..757c636 --- /dev/null +++ b/examples/notebooks/choropleth-viz-example.ipynb @@ -0,0 +1,1812 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Mapboxgl Python Library\n", + "\n", + "https://github.com/mapbox/mapboxgl-jupyter" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "from mapboxgl.viz import *\n", + "from mapboxgl.utils import *\n", + "\n", + "# Must be a public token, starting with `pk`\n", + "token = os.getenv('MAPBOX_ACCESS_TOKEN')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Choropleths with interpolated color assignment from GeoJSON source" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# create choropleth from polygon features stored as GeoJSON\n", + "viz = ChoroplethViz('../data/us-states.geojson', \n", + " color_property='density',\n", + " color_stops=create_color_stops([0, 50, 100, 500, 1500], colors='YlOrRd'),\n", + " color_function_type='interpolate',\n", + " line_stroke='--',\n", + " line_color='rgb(128,0,38)',\n", + " line_width=1,\n", + " opacity=0.8,\n", + " center=(-96, 37.8),\n", + " zoom=3,\n", + " below_layer='waterway-label'\n", + " )\n", + "viz.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Choropleths with match-type color scheme from GeoJSON source" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "match_color_stops = [\n", + " ['Massachusetts', 'rgb(46,204,113)'],\n", + " ['Utah', 'rgb(231,76,60)'],\n", + " ['California', 'rgb(142,68,173)'],\n", + "]\n", + "\n", + "viz = ChoroplethViz('../data/us-states.geojson', \n", + " color_property='name', \n", + " color_stops = match_color_stops, \n", + " color_function_type = 'match', \n", + " color_default = 'rgba(52,73,94,0.5)', \n", + " opacity=0.8, \n", + " center = (-96, 37.8), \n", + " zoom = 3, \n", + " below_layer = 'waterway-label'\n", + " )\n", + "viz.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Vector polygon source with data-join technique\n", + "\n", + "In this configuration, properties in JSON data are used to calculate colors to style polygons from the vector source." + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# must be JSON object (need to extend to use referenced JSON file)\n", + "data = [{\"id\": \"01\", \"name\": \"Alabama\", \"density\": 94.65}, {\"id\": \"02\", \"name\": \"Alaska\", \"density\": 1.264}, {\"id\": \"04\", \"name\": \"Arizona\", \"density\": 57.05}, {\"id\": \"05\", \"name\": \"Arkansas\", \"density\": 56.43}, {\"id\": \"06\", \"name\": \"California\", \"density\": 241.7}, {\"id\": \"08\", \"name\": \"Colorado\", \"density\": 49.33}, {\"id\": \"09\", \"name\": \"Connecticut\", \"density\": 739.1}, {\"id\": \"10\", \"name\": \"Delaware\", \"density\": 464.3}, {\"id\": \"11\", \"name\": \"District of Columbia\", \"density\": 10065}, {\"id\": \"12\", \"name\": \"Florida\", \"density\": 353.4}, {\"id\": \"13\", \"name\": \"Georgia\", \"density\": 169.5}, {\"id\": \"15\", \"name\": \"Hawaii\", \"density\": 214.1}, {\"id\": \"16\", \"name\": \"Idaho\", \"density\": 19.15}, {\"id\": \"17\", \"name\": \"Illinois\", \"density\": 231.5}, {\"id\": \"18\", \"name\": \"Indiana\", \"density\": 181.7}, {\"id\": \"19\", \"name\": \"Iowa\", \"density\": 54.81}, {\"id\": \"20\", \"name\": \"Kansas\", \"density\": 35.09}, {\"id\": \"21\", \"name\": \"Kentucky\", \"density\": 110}, {\"id\": \"22\", \"name\": \"Louisiana\", \"density\": 105}, {\"id\": \"23\", \"name\": \"Maine\", \"density\": 43.04}, {\"id\": \"24\", \"name\": \"Maryland\", \"density\": 596.3}, {\"id\": \"25\", \"name\": \"Massachusetts\", \"density\": 840.2}, {\"id\": \"26\", \"name\": \"Michigan\", \"density\": 173.9}, {\"id\": \"27\", \"name\": \"Minnesota\", \"density\": 67.14}, {\"id\": \"28\", \"name\": \"Mississippi\", \"density\": 63.5}, {\"id\": \"29\", \"name\": \"Missouri\", \"density\": 87.26}, {\"id\": \"30\", \"name\": \"Montana\", \"density\": 6.858}, {\"id\": \"31\", \"name\": \"Nebraska\", \"density\": 23.97}, {\"id\": \"32\", \"name\": \"Nevada\", \"density\": 24.8}, {\"id\": \"33\", \"name\": \"New Hampshire\", \"density\": 147}, {\"id\": \"34\", \"name\": \"New Jersey\", \"density\": 1189}, {\"id\": \"35\", \"name\": \"New Mexico\", \"density\": 17.16}, {\"id\": \"36\", \"name\": \"New York\", \"density\": 412.3}, {\"id\": \"37\", \"name\": \"North Carolina\", \"density\": 198.2}, {\"id\": \"38\", \"name\": \"North Dakota\", \"density\": 9.916}, {\"id\": \"39\", \"name\": \"Ohio\", \"density\": 281.9}, {\"id\": \"40\", \"name\": \"Oklahoma\", \"density\": 55.22}, {\"id\": \"41\", \"name\": \"Oregon\", \"density\": 40.33}, {\"id\": \"42\", \"name\": \"Pennsylvania\", \"density\": 284.3}, {\"id\": \"44\", \"name\": \"Rhode Island\", \"density\": 1006}, {\"id\": \"45\", \"name\": \"South Carolina\", \"density\": 155.4}, {\"id\": \"46\", \"name\": \"South Dakota\", \"density\": 98.07}, {\"id\": \"47\", \"name\": \"Tennessee\", \"density\": 88.08}, {\"id\": \"48\", \"name\": \"Texas\", \"density\": 98.07}, {\"id\": \"49\", \"name\": \"Utah\", \"density\": 34.3}, {\"id\": \"50\", \"name\": \"Vermont\", \"density\": 67.73}, {\"id\": \"51\", \"name\": \"Virginia\", \"density\": 204.5}, {\"id\": \"53\", \"name\": \"Washington\", \"density\": 102.6}, {\"id\": \"54\", \"name\": \"West Virginia\", \"density\": 77.06}, {\"id\": \"55\", \"name\": \"Wisconsin\", \"density\": 105.2}, {\"id\": \"56\", \"name\": \"Wyoming\", \"density\": 5.851}, {\"id\": \"72\", \"name\": \"Puerto Rico\", \"density\": 1082}]\n", + "\n", + "# create choropleth map with vector source styling use data in JSON object\n", + "viz = ChoroplethViz(data, \n", + " vector_url='mapbox://mapbox.us_census_states_2015',\n", + " vector_layer_name='states',\n", + " vector_join_property='STATEFP',\n", + " data_join_property='id',\n", + " color_property='density',\n", + " color_stops=create_color_stops([0, 50, 100, 500, 1500], colors='YlOrRd'),\n", + " line_stroke='dashed',\n", + " line_color='rgb(128,0,38)',\n", + " opacity=0.8,\n", + " center=(-96, 37.8),\n", + " zoom=3,\n", + " below_layer='waterway-label'\n", + " )\n", + "viz.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Vector polygon source with data-join technique, categorical color scheme" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# must be JSON object (need to extend to use referenced JSON file)\n", + "data = [{\"id\": \"01\", \"name\": \"Alabama\", \"density\": 94.65}, {\"id\": \"02\", \"name\": \"Alaska\", \"density\": 1.264}, {\"id\": \"04\", \"name\": \"Arizona\", \"density\": 57.05}, {\"id\": \"05\", \"name\": \"Arkansas\", \"density\": 56.43}, {\"id\": \"06\", \"name\": \"California\", \"density\": 241.7}, {\"id\": \"08\", \"name\": \"Colorado\", \"density\": 49.33}, {\"id\": \"09\", \"name\": \"Connecticut\", \"density\": 739.1}, {\"id\": \"10\", \"name\": \"Delaware\", \"density\": 464.3}, {\"id\": \"11\", \"name\": \"District of Columbia\", \"density\": 10065}, {\"id\": \"12\", \"name\": \"Florida\", \"density\": 353.4}, {\"id\": \"13\", \"name\": \"Georgia\", \"density\": 169.5}, {\"id\": \"15\", \"name\": \"Hawaii\", \"density\": 214.1}, {\"id\": \"16\", \"name\": \"Idaho\", \"density\": 19.15}, {\"id\": \"17\", \"name\": \"Illinois\", \"density\": 231.5}, {\"id\": \"18\", \"name\": \"Indiana\", \"density\": 181.7}, {\"id\": \"19\", \"name\": \"Iowa\", \"density\": 54.81}, {\"id\": \"20\", \"name\": \"Kansas\", \"density\": 35.09}, {\"id\": \"21\", \"name\": \"Kentucky\", \"density\": 110}, {\"id\": \"22\", \"name\": \"Louisiana\", \"density\": 105}, {\"id\": \"23\", \"name\": \"Maine\", \"density\": 43.04}, {\"id\": \"24\", \"name\": \"Maryland\", \"density\": 596.3}, {\"id\": \"25\", \"name\": \"Massachusetts\", \"density\": 840.2}, {\"id\": \"26\", \"name\": \"Michigan\", \"density\": 173.9}, {\"id\": \"27\", \"name\": \"Minnesota\", \"density\": 67.14}, {\"id\": \"28\", \"name\": \"Mississippi\", \"density\": 63.5}, {\"id\": \"29\", \"name\": \"Missouri\", \"density\": 87.26}, {\"id\": \"30\", \"name\": \"Montana\", \"density\": 6.858}, {\"id\": \"31\", \"name\": \"Nebraska\", \"density\": 23.97}, {\"id\": \"32\", \"name\": \"Nevada\", \"density\": 24.8}, {\"id\": \"33\", \"name\": \"New Hampshire\", \"density\": 147}, {\"id\": \"34\", \"name\": \"New Jersey\", \"density\": 1189}, {\"id\": \"35\", \"name\": \"New Mexico\", \"density\": 17.16}, {\"id\": \"36\", \"name\": \"New York\", \"density\": 412.3}, {\"id\": \"37\", \"name\": \"North Carolina\", \"density\": 198.2}, {\"id\": \"38\", \"name\": \"North Dakota\", \"density\": 9.916}, {\"id\": \"39\", \"name\": \"Ohio\", \"density\": 281.9}, {\"id\": \"40\", \"name\": \"Oklahoma\", \"density\": 55.22}, {\"id\": \"41\", \"name\": \"Oregon\", \"density\": 40.33}, {\"id\": \"42\", \"name\": \"Pennsylvania\", \"density\": 284.3}, {\"id\": \"44\", \"name\": \"Rhode Island\", \"density\": 1006}, {\"id\": \"45\", \"name\": \"South Carolina\", \"density\": 155.4}, {\"id\": \"46\", \"name\": \"South Dakota\", \"density\": 98.07}, {\"id\": \"47\", \"name\": \"Tennessee\", \"density\": 88.08}, {\"id\": \"48\", \"name\": \"Texas\", \"density\": 98.07}, {\"id\": \"49\", \"name\": \"Utah\", \"density\": 34.3}, {\"id\": \"50\", \"name\": \"Vermont\", \"density\": 67.73}, {\"id\": \"51\", \"name\": \"Virginia\", \"density\": 204.5}, {\"id\": \"53\", \"name\": \"Washington\", \"density\": 102.6}, {\"id\": \"54\", \"name\": \"West Virginia\", \"density\": 77.06}, {\"id\": \"55\", \"name\": \"Wisconsin\", \"density\": 105.2}, {\"id\": \"56\", \"name\": \"Wyoming\", \"density\": 5.851}, {\"id\": \"72\", \"name\": \"Puerto Rico\", \"density\": 1082}]\n", + "\n", + "match_color_stops = [\n", + " ['Massachusetts', 'rgb(46,204,113)'],\n", + " ['Utah', 'rgb(231,76,60)'],\n", + " ['California', 'rgb(142,68,173)'],\n", + "]\n", + "\n", + "# create choropleth map with vector source styling use data in JSON object\n", + "viz = ChoroplethViz(data, \n", + " vector_url='mapbox://mapbox.us_census_states_2015',\n", + " vector_layer_name='states',\n", + " vector_join_property='STATEFP',\n", + " data_join_property='id',\n", + " color_property='name',\n", + " color_stops=match_color_stops,\n", + " color_default = 'rgba(52,73,94,0.5)', \n", + " opacity=0.8,\n", + " center=(-96, 37.8),\n", + " zoom=3,\n", + " below_layer='waterway-label'\n", + " )\n", + "viz.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Vector polygon source joined to data in a local Pandas dataframe" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
Zip Code ZCTA2010 Census Population
0100116769
1100229049
\n", + "
" + ], + "text/plain": [ + " Zip Code ZCTA 2010 Census Population\n", + "0 1001 16769\n", + "1 1002 29049" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Load data from sample csv\n", + "import pandas as pd\n", + "data_url = '../data/2010_us_population_by_postcode.csv'\n", + "df = pd.read_csv(data_url).round(3)\n", + "df = df.head(6000)\n", + "df.head(2)" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "# Group pandas dataframe by a value\n", + "measure = '2010 Census Population'\n", + "dimension = 'Zip Code ZCTA'\n", + "\n", + "data = df[[dimension, measure]].groupby(dimension, as_index=False).mean()\n", + "color_breaks = [round(data[measure].quantile(q=x*0.1), 2) for x in range(2,11)]\n", + "color_stops = create_color_stops(color_breaks, colors='PuRd')\n", + "data = json.loads(data.to_json(orient='records'))" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Create the viz\n", + "viz = ChoroplethViz(data, \n", + " vector_url='mapbox://rsbaumann.bv2k1pl2',\n", + " vector_layer_name='2016_us_census_postcode',\n", + " vector_join_property='postcode',\n", + " data_join_property=dimension,\n", + " color_property=measure,\n", + " color_stops=color_stops,\n", + " line_color = 'rgba(0,0,0,0.05)',\n", + " line_width = 0.5,\n", + " opacity=0.7,\n", + " center=(-75, 45),\n", + " zoom=4,\n", + " below_layer='waterway-label'\n", + " )\n", + "viz.show()" + ] + } + ], + "metadata": { + "anaconda-cloud": { + "attach-environment": true, + "environment": "Root", + "summary": "Mapboxgl Python Data Visualization example" + }, + "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": "3.6.3" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} diff --git a/examples/image-vis-type-example.ipynb b/examples/notebooks/image-vis-type-example.ipynb similarity index 55% rename from examples/image-vis-type-example.ipynb rename to examples/notebooks/image-vis-type-example.ipynb index be3e537..3ef4141 100644 --- a/examples/image-vis-type-example.ipynb +++ b/examples/notebooks/image-vis-type-example.ipynb @@ -23,7 +23,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -47,7 +47,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -64,7 +64,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 3, "metadata": { "scrolled": false }, @@ -102,8 +102,8 @@ " .legend h4 { margin: 0 0 10px; }\n", " .legend-title {\n", " margin: 6px;\n", - " padding: 6px:\n", - " font-weight: bold;\n", + " padding: 6px;\n", + " font-weight: bold !important;\n", " font-size: 14px;\n", " font: 12px/20px 'Helvetica Neue', Arial, Helvetica, sans-serif;\n", " }\n", @@ -115,6 +115,7 @@ " width: 10px;\n", " }\n", "\n", + "\n", "\n", "\n", "\n", @@ -122,6 +123,7 @@ "
\n", "\n", "\n", + "\n", + "\n", + "\n", + " \n", + "\n", + "\n", + "\n", + "\n", + "
\n", + "
\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\" style=\"width: 100%; height: 500px;\">" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Create the viz\n", + "viz = ChoroplethViz(data, \n", + " vector_url='mapbox://rsbaumann.bv2k1pl2',\n", + " vector_layer_name='2016_us_census_postcode',\n", + " vector_join_property='postcode',\n", + " data_join_property=dimension,\n", + " color_property=measure,\n", + " color_stops=color_stops,\n", + " line_color = 'rgba(0,0,0,0.05)',\n", + " line_width = 0.5,\n", + " opacity=0.7,\n", + " center=(-75, 45),\n", + " zoom=4,\n", + " below_layer='waterway-label'\n", + " )\n", + "viz.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Conda Py3", + "language": "python", + "name": "myenv" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +}