In [1]:
from IPython.display import display, HTML
import bubble_plot
import pandas as pd
from bokeh.io import show, output_notebook
output_notebook()
from IPython.html.services.config import ConfigManager
from IPython.utils.path import locate_profile
cm = ConfigManager(profile_dir=locate_profile(get_ipython().profile))
cm.update('livereveal', {
#'width': 1024,
#'height': 768,
'theme': 'solarized',
'transition': 'fade',
'start_slideshow_at': 'selected',
})
https://github.com/bokeh/bokeh-notebooks/
conda install bokeh
conda install ipython-notebook
conda install pandas
In [2]:
bubble_plot.get_bubble_html()
Out[2]:
u'<!DOCTYPE html>\n<html lang="en">\n <head>\n <meta charset="utf-8">\n <title>Bokeh - Gapminder demo</title>\n <link href="assets/bubble_styles.css" type="text/css" rel="stylesheet" />\n </head>\n <body>\n <div class="plotdiv" id="797cd55d-fbcf-40d0-838d-e4624e0de456"></div>\n \n <script type="text/javascript" src="/tree/bokehjs/static/js/bokeh.min.js"></script>\n <script type="text/javascript">\n Bokeh.$(function() {\n var all_models = [{"attributes": {"x_range": {"type": "Range1d", "id": "0f6a8bdc-f595-4d34-b76c-8b8360c62345"}, "right": [], "y_range": {"type": "Range1d", "id": "c11ed62d-6bc5-432f-aa20-25669ae20d5c"}, "tags": [], "toolbar_location": null, "title": "", "outline_line_color": null, "plot_width": 800, "renderers": [{"type": "LinearAxis", "id": "abccd593-2216-433a-b992-dff32e35ba00"}, {"type": "LinearAxis", "id": "e4a43cb6-a83e-4842-be0a-022730d4bd9b"}, {"type": "GlyphRenderer", "id": "e6800ddd-02b9-4c1f-a0d9-842fa5cc58a8"}, {"type": "GlyphRenderer", "id": "f52f9159-f44d-48a4-8cc4-526959d05d10"}, {"type": "GlyphRenderer", "id": "608c11e7-2463-48b8-94e9-38be823ff367"}, {"type": "GlyphRenderer", "id": "6ff8fddf-d3b2-412f-ab9b-804319de9123"}, {"type": "GlyphRenderer", "id": "2eb6b33d-56c7-48a3-9796-e60181a2b7b0"}, {"type": "GlyphRenderer", "id": "30cf8e27-32d5-438e-9fe4-bd7a03645338"}, {"type": "GlyphRenderer", "id": "37dd9f31-e0da-4a8d-bdfd-50fd6ac95842"}, {"type": "GlyphRenderer", "id": "cdb81f68-3c0e-4eac-a2ef-83350e296513"}, {"type": "GlyphRenderer", "id": "d68cafe1-24b7-4a0c-8f98-9e41a0dfe8a1"}, {"type": "GlyphRenderer", "id": "f5a3b48e-8798-4caa-8646-c6353f012160"}, {"type": "GlyphRenderer", "id": "281fa2c0-ceab-4da5-b660-e877f52c7d71"}, {"type": "GlyphRenderer", "id": "dc3edbce-bae7-4476-8bed-37ead5197703"}, {"type": "GlyphRenderer", "id": "d923b011-4123-45dd-896f-94a2ebe9e709"}, {"type": "GlyphRenderer", "id": "54b1e010-bd11-4def-a55b-cc7840d725ec"}], "extra_x_ranges": {}, "doc": null, "tool_events": {"type": "ToolEvents", "id": 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"10pt"}, "axis_line_color": {"value": "#AAAAAA"}, "minor_tick_in": null, "major_label_text_color": {"value": "#666666"}, "axis_label": "Life expectancy at birth (years)", "major_tick_in": null, "id": "e4a43cb6-a83e-4842-be0a-022730d4bd9b", "major_tick_line_cap": "round", "plot": {"type": "Plot", "id": "fa52c8ac-8973-4731-b6f4-754f125a12b5"}, "minor_tick_out": null, "major_tick_line_color": {"value": "#AAAAAA"}, "axis_line_cap": "round", "ticker": {"type": "SingleIntervalTicker", "id": "e11b077f-f496-43bf-ba48-a04767bff683"}, "tags": [], "major_tick_line_width": {"value": 1}, "doc": null, "major_label_text_font_style": "normal", "axis_line_width": {"value": 1}, "formatter": {"type": "BasicTickFormatter", "id": "259ba5ed-3bf0-41eb-9b67-28922bec1f23"}, "major_label_text_font_size": {"value": "10pt"}}, "type": "LinearAxis", "id": "e4a43cb6-a83e-4842-be0a-022730d4bd9b"}, {"attributes": {"column_names": ["region_color", "index", "life", "fertility", "population"], "tags": [], "doc": null, 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Sts.", "Moldova", "Monaco", "Mongolia", "Montenegro", "Montserrat", "Morocco", "Mozambique", "Myanmar", "Namibia", "Nauru", "Nepal", "Netherlands", "Netherlands Antilles", "New Caledonia", "New Zealand", "Nicaragua", "Niger", "Nigeria", "Niue", "Norfolk Island", "Northern Cyprus", "Northern Mariana Islands", "Norway", "Oman", "Pakistan", "Palau", "Panama", "Papua New Guinea", "Paraguay", "Peru", "Philippines", "Pitcairn", "Poland", "Portugal", "Puerto Rico", "Qatar", "Reunion", "Romania", "Russia", "Rwanda", "Saint Barth\\u00e9lemy", "Saint Helena", "Saint Kitts and Nevis", "Saint Lucia", "Saint Martin", "Saint Vincent and the Grenadines", "Saint-Pierre-et-Miquelon", "Samoa", "San Marino", "Sao Tome and Principe", "Saudi Arabia", "Senegal", "Serbia", "Serbia excluding Kosovo", "Seychelles", "Sierra Leone", "Singapore", "Slovak Republic", "Slovenia", "Solomon Islands", "Somalia", "South Africa", "South Sudan", "Spain", "Sri Lanka", "Sudan", "Suriname", "Svalbard", "Swaziland", "Sweden", 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5.828087955947273, 3.0, 4.32039754713224, 3.0, 3.0, 14.849188759724242, 11.583893829513093, 18.57379268150958, 3.7337587526799645, 3.0, 13.437838791623738, 11.14392865316701, 3.0, 3.0, 5.464294079651718, 6.196332020941234, 8.847144360555028, 30.28661897282437, 3.0, 3.0, 3.0, 3.0, 5.925395561379032, 4.246879705822529, 32.68600495648576, 3.0, 4.709570647756212, 6.2891817561170775, 6.317065518798159, 14.010588211077227, 24.00743192582175, 3.0, 17.47829736033829, 9.014365885769093, 5.470499565753027, 3.0, 3.0, 13.370654533162526, 34.33445625253492, 7.0792490322877875, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 12.302903554885907, 8.374317796725984, 9.033002957018272, 7.776068682089956, 3.0, 5.580688473812313, 5.404668979330828, 6.549154265996073, 3.9651681842547846, 3.0, 7.348900143441223, 18.47093172417627, 7.187913129817702, 17.753749963045394, 12.109806344689874, 14.172616681661715, 3.0, 3.0, 3.0, 8.393888734994636, 7.511609076486381, 10.873085308381407, 13.122411770641714, 6.8782444843361645, 15.855747509788916, 22.020340406015144, 3.0, 5.8831130899456285, 3.0, 3.0, 3.1858732218654655, 8.539075047709895, 21.993123291812516, 5.874071845202314, 3.0, 3.0, 13.268410322428368, 20.015383479931764, 4.558786247063053, 21.542656149711757, 46.5792524961942, 5.100614740427258, 13.748097983438505, 3.0, 13.517675422421055, 24.61042382970684, 3.0, 3.0, 4.760936958993933, 3.0, 11.363532448023621, 8.65719455895685, 9.807214802440376, 3.0]}, "id": "41547e78-6e10-4814-984d-6aa9b4c6f7a4"}, "type": "ColumnDataSource", "id": "41547e78-6e10-4814-984d-6aa9b4c6f7a4"}, {"attributes": {"tags": [], "doc": null, "id": "18719d9a-a36a-4981-868e-d40657723975", "children": [{"type": "Slider", "id": "aef1123a-1a87-4a8d-9aab-d8bebe6ccc12"}]}, "type": "HBox", "id": "18719d9a-a36a-4981-868e-d40657723975"}];\n Bokeh.load_models(all_models);\n var plots = [{\'modeltype\': \'VBox\', \'elementid\': \'#797cd55d-fbcf-40d0-838d-e4624e0de456\', \'modelid\': \'b517ae64-0eaa-4cc7-a452-48fe4f7cde05\'}];\n for (idx in plots) {\n \tvar plot = plots[idx];\n \tvar model = Bokeh.Collections(plot.modeltype).get(plot.modelid);\n \tBokeh.logger.info(\'Realizing plot:\')\n \tBokeh.logger.info(\' - modeltype: \' + plot.modeltype);\n \tBokeh.logger.info(\' - modelid: \' + plot.modelid);\n \tBokeh.logger.info(\' - elementid: \' + plot.elementid);\n \tvar view = new model.default_view({\n \t\tmodel: model,\n \t\tel: plot.elementid\n \t});\n \tBokeh.index[plot.modelid] = view;\n }\n });\n </script>\n </body>\n</html>\n'
In [3]:
display(HTML(bubble_plot.get_bubble_html()))
Bokeh - Gapminder demo
In [4]:
from bokeh.charts import (
Area, Bar, BoxPlot, Donut, Dot, HeatMap, Histogram,
Horizon, Line, Scatter, Step, TimeSeries,
)
In [5]:
xyvalues = bubble_plot.get_scatter_data()
xyvalues['1964'][0:5]
Out[5]:
[(7.6710000000000003, 33.639000000000003),
(5.7110000000000003, 65.474999999999994),
(7.6529999999999996, 47.953000000000003),
(7.4249999999999998, 34.603999999999999),
(4.25, 63.774999999999999)]
In [6]:
from bokeh.charts import Scatter
show(Scatter(xyvalues))
In [7]:
scatter = Scatter(
xyvalues,
tools="wheel_zoom, reset",
ylabel="Children per woman (total fertility)",
xlabel="Life expectancy at birth (years)",
title="Life expectancy vs Fertility in 1964",
width=800,
height=600,
xgrid=None,
ygrid=None,
)
scatter.outline_line_color = 'white'
scatter.logo = None
scatter.toolbar_location = 'right'
In [8]:
show(scatter)
In [9]:
from bokeh.models import Range1d, Plot
def get_plot():
xdr = Range1d(1, 9)
ydr = Range1d(20, 100)
plot = Plot(
x_range=xdr,
y_range=ydr,
title="",
plot_width=800,
plot_height=400,
outline_line_color=None,
toolbar_location=None,
)
return plot
show(get_plot())
ERROR:/Library/Python/2.7/site-packages/bokeh/validation/check.pyc:W-1000 (MISSING_RENDERERS): Plot has no renderers: Plot, ViewModel:Plot, ref _id: 93c70929-f8d6-41c3-b8eb-523cec39e873
ERROR:/Library/Python/2.7/site-packages/bokeh/validation/check.pyc:W-1001 (NO_GLYPH_RENDERERS): Plot has no glyph renderers: Plot, ViewModel:Plot, ref _id: 93c70929-f8d6-41c3-b8eb-523cec39e873
In [10]:
AXIS_FORMATS = dict(
minor_tick_in=None,
minor_tick_out=None,
major_tick_in=None,
major_label_text_font_size="10pt",
major_label_text_font_style="normal",
axis_label_text_font_size="10pt",
axis_line_color='#AAAAAA',
major_tick_line_color='#AAAAAA',
major_label_text_color='#666666',
major_tick_line_cap="round",
axis_line_cap="round",
axis_line_width=1,
major_tick_line_width=1,
)
In [11]:
from bokeh.models import LinearAxis, SingleIntervalTicker
def add_axes(plot):
xaxis = LinearAxis(SingleIntervalTicker(interval=1), axis_label="Children per woman (total fertility)", **AXIS_FORMATS)
yaxis = LinearAxis(SingleIntervalTicker(interval=20), axis_label="Life expectancy at birth (years)", **AXIS_FORMATS)
plot.add_layout(xaxis, 'below')
plot.add_layout(yaxis, 'left')
return plot
show(add_axes(get_plot()))
ERROR:/Library/Python/2.7/site-packages/bokeh/validation/check.pyc:W-1001 (NO_GLYPH_RENDERERS): Plot has no glyph renderers: Plot, ViewModel:Plot, ref _id: 715aefbc-9ebb-4a66-8214-da37c096c522
In [12]:
from bokeh.models import ColumnDataSource, Text
years, regions, fertility_df, life_expectancy_df, population_df_size, regions_df = bubble_plot._get_data()
text_source = ColumnDataSource({'year': ['1964']})
def add_text(plot):
plot = add_axes(plot)
# Add the year in background (add before circle)
text = Text(x=2, y=35, text='year', text_font_size='150pt', text_color='#EEEEEE')
plot.add_glyph(text_source, text)
return plot
show(add_text(get_plot()))
In [13]:
from bokeh.models import Circle, HoverTool
from bokeh.palettes import Spectral6
renderer_source = ColumnDataSource(bubble_plot.get_1964_data())
def add_circles(plot):
plot = add_text(plot)
# Add the circle
circle_glyph = Circle(
x='fertility', y='life', size='population',
fill_color='region_color', fill_alpha=0.8,
line_color='#7c7e71', line_width=0.5, line_alpha=0.5)
circle_renderer = plot.add_glyph(renderer_source, circle_glyph)
# Add the hover (only against the circle and not other plot elements)
tooltips = "@index"
plot.add_tools(HoverTool(tooltips=tooltips, renderers=[circle_renderer]))
return plot
show(add_circles(get_plot()))
In [14]:
def add_legend(plot):
plot = add_circles(plot)
# Add a custom legend
text_x = 7
text_y = 95
for i, region in enumerate(regions):
plot.add_glyph(Text(x=text_x, y=text_y, text=[region], text_font_size='10pt', text_color='#666666'))
plot.add_glyph(Circle(x=text_x - 0.1, y=text_y + 2, fill_color=Spectral6[i], size=10, line_color=None, fill_alpha=0.8))
text_y = text_y - 5
return plot
show(add_legend(get_plot()))
In [19]:
from bokeh.models import Callback, Slider
from bokeh.plotting import vplot, hplot
sources = {}
region_color = regions_df['region_color']
region_color.name = 'region_color'
def make_interactive(plot):
plot = add_legend(plot)
for year in years:
fertility = fertility_df[year]
fertility.name = 'fertility'
life = life_expectancy_df[year]
life.name = 'life'
population = population_df_size[year]
population.name = 'population'
new_df = pd.concat([fertility, life, population, region_color], axis=1)
sources['_' + str(year)] = ColumnDataSource(new_df)
dictionary_of_sources = dict(zip([x for x in years], ['_%s' % x for x in years]))
js_source_array = str(dictionary_of_sources).replace("'", "")
# Add the slider
code = """
var year = slider.get('value'),
sources = %s,
new_source_data = sources[year].get('data');
renderer_source.set('data', new_source_data);
renderer_source.trigger('change');
text_source.set('data', {'year': [String(year)]});
text_source.trigger('change');
""" % js_source_array
callback = Callback(args=sources, code=code)
slider = Slider(start=years[0], end=years[-1], value=1, step=1, title="Year", callback=callback)
callback.args["slider"] = slider
callback.args["renderer_source"] = renderer_source
callback.args["text_source"] = text_source
return vplot(plot, hplot(slider))
show(make_interactive(get_plot()))
In [ ]:
from bokeh.plotting import vplot, hplot
layout = vplot(plot, hplot(slider))
In [ ]:
for year in years:
fertility = fertility_df[year]
fertility.name = 'fertility'
life = life_expectancy_df[year]
life.name = 'life'
population = population_df_size[year]
population.name = 'population'
new_df = pd.concat([fertility, life, population, region_color], axis=1)
sources['_' + str(year)] = ColumnDataSource(new_df)
In [16]:
print(sources['_1964'])
print(sources['_1965'])
print(sources['_1966'])
ColumnDataSource, ViewModel:ColumnDataSource, ref _id: db4bbaf4-974d-4538-993c-8b8a1917fc88
ColumnDataSource, ViewModel:ColumnDataSource, ref _id: 186306e5-c65c-4e0a-a7e9-8589997406b0
ColumnDataSource, ViewModel:ColumnDataSource, ref _id: bc5d2dc8-96e7-4f62-9aea-91925ce58f72
In [ ]:
# Add the slider
code = """
var year = slider.get('value'),
sources = %s,
new_source_data = sources[year].get('data');
renderer_source.set('data', new_source_data);
renderer_source.trigger('change');
text_source.set('data', {'year': [String(year)]});
text_source.trigger('change');
""" % js_source_array
callback = Callback(args=sources, code=code)
slider = Slider(start=years[0], end=years[-1], value=1, step=1, title="Year", callback=callback)
callback.args["slider"] = slider
callback.args["renderer_source"] = renderer_source
callback.args["text_source"] = text_source
In [17]:
from jinja2 import Template
from bokeh.templates import RESOURCES
from bokeh.resources import Resources
from bokeh.embed import components
with open('assets/bubble_template.html', 'r') as f:
template = Template(f.read())
resources = Resources(mode='server', root_url='tree/')
bokeh_js = RESOURCES.render(js_files=resources.js_files)
script, div = components(make_layout(get_plot()))
html = template.render(
title="Bokeh - Gapminder demo",
bokeh_js=bokeh_js,
plot_script=script,
plot_div=div,
)
In [18]:
display(HTML(html))
Bokeh - Gapminder demo
Content source: fionapigott/Data-Science-45min-Intros
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