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from ipywidgets import HBox, IntSlider, IntText, link

slider = IntSlider(min=0, max=10)
slider


    

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slider


    

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slider.value


    

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text = IntText()

s = IntSlider()

link((text, 'value'), (s, 'value'))
HBox([text, s])


    

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import ipywidgets as widgets
import numpy as np

from bqplot import pyplot as plt


    

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n = 2000
x = np.linspace(0.0, 10.0, n)
np.random.seed(0)
y = np.cumsum(np.random.randn(n)*10).astype(int)


    

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fig_hist = plt.figure(title='Histogram')
hist = plt.hist(y, bins=25)
fig_hist


    

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slider = widgets.IntSlider(min=1, max=100, v_model=30)
widgets.link((hist, 'bins'), (slider, 'value'));
slider


    

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import os
import json

import numpy as np
import pandas as pd

from ipywidgets import Dropdown

from bqplot import Lines, Figure, LinearScale, DateScale, Axis

from ipyleaflet import Map, GeoJSON, WidgetControl, FullScreenControl


    

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data = pd.read_json(os.path.abspath('./examples/nations.json'))


    

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def clean_data(data):
    for column in ['income', 'lifeExpectancy', 'population']:
        data = data.drop(data[data[column].apply(len) <= 4].index)
    return data

def extrap_interp(data):
    data = np.array(data)
    x_range = np.arange(1800, 2009, 1.)
    y_range = np.interp(x_range, data[:, 0], data[:, 1])
    return y_range

def extrap_data(data):
    for column in ['income', 'lifeExpectancy', 'population']:
        data[column] = data[column].apply(extrap_interp)
    return data


    

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data = clean_data(data)
data = extrap_data(data)
date_start = pd.datetime(1800, 12, 31)
date_end = pd.datetime(2009, 12, 31)
date_scale = DateScale(min=date_start, max=date_end)
date_data = pd.date_range(start=date_start, end=date_end, freq='A', normalize=True)

country_name = 'Angola'
data_name = 'income'

x_data = data[data.name == country_name][data_name].values[0]

x_scale = LinearScale()

lines = Lines(x=date_data, y=x_data, scales={'x': date_scale, 'y': x_scale})

ax_x = Axis(label='Year', scale=date_scale, num_ticks=10, tick_format='%Y')
ax_y = Axis(label=data_name.capitalize(), scale=x_scale, orientation='vertical', side='left')

figure = Figure(axes=[ax_x, ax_y], title=country_name, marks=[lines], animation_duration=500,
                layout={'height': '300px', 'width': '600px'})


    

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def update_figure(country_name, data_name):
    lines.y = data[data.name == country_name][data_name].values[0]
    ax_y.label = data_name.capitalize()
    figure.title = country_name


    

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with open('./examples/countries.geo.json') as f:
    countries = json.load(f)


    

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m = Map(zoom=3)

geo = GeoJSON(data=countries, style={'fillColor': 'white', 'weight': 0.5}, hover_style={'fillColor': '#1f77b4'}, name='Countries')
m.add_layer(geo)

m.layout.height = '800px'
m


    

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m.add_control(FullScreenControl())


    

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widget_control1 = WidgetControl(widget=figure, position='bottomright')

m.add_control(widget_control1)

def on_hover(event, feature, **kwargs):
    global country_name

    country_name = feature['properties']['name']
    update_figure(country_name, data_name)

geo.on_hover(on_hover)


    

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dropdown = Dropdown(
    options=['income', 'population', 'lifeExpectancy'],
    value=data_name,
    description='Plotting:'
)

def on_click(change):
    global data_name

    data_name = change['new']
    update_figure(country_name, data_name)

dropdown.observe(on_click, 'value')

widget_control2 = WidgetControl(widget=dropdown, position='bottomleft')

m.add_control(widget_control2)