satlomas-exp/line_plot_bokeh_app.py at master · undp/satlomas-exp · GitHub

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''' Create a simple stocks correlation dashboard.

Choose stocks to compare in the drop down widgets, and make selections
on the plots to update the summary and histograms accordingly.

.. note::
    Running this example requires downloading sample data. See
    the included `README`_ for more information.

Use the ``bokeh serve`` command to run the example by executing:

    bokeh serve stocks

at your command prompt. Then navigate to the URL

    http://localhost:5006/stocks

.. _README: https://github.com/bokeh/bokeh/blob/master/examples/app/stocks/README.md

'''
from functools import lru_cache
from os.path import dirname, join

import pandas as pd

from bokeh.io import curdoc
from bokeh.layouts import column, row
from bokeh.models import ColumnDataSource, PreText, Select
from bokeh.plotting import figure

DATA_DIR = join(dirname(__file__), 'daily')

DEFAULT_TICKERS = ['AAPL', 'GOOG', 'INTC', 'BRCM', 'YHOO']

def nix(val, lst):
    return [x for x in lst if x != val]

@lru_cache()
def load_ticker(ticker):
    fname = join(DATA_DIR, 'table_%s.csv' % ticker.lower())
    data = pd.read_csv(fname, header=None, parse_dates=['date'],
                       names=['date', 'foo', 'o', 'h', 'l', 'c', 'v'])
    data = data.set_index('date')
    return pd.DataFrame({ticker: data.c, ticker+'_returns': data.c.diff()})

@lru_cache()
def get_data(t1, t2):
    df1 = load_ticker(t1)
    df2 = load_ticker(t2)
    data = pd.concat([df1, df2], axis=1)
    data = data.dropna()
    data['t1'] = data[t1]
    data['t2'] = data[t2]
    data['t1_returns'] = data[t1+'_returns']
    data['t2_returns'] = data[t2+'_returns']
    return data

# set up widgets

stats = PreText(text='', width=500)
ticker1 = Select(value='AAPL', options=nix('GOOG', DEFAULT_TICKERS))
ticker2 = Select(value='GOOG', options=nix('AAPL', DEFAULT_TICKERS))

# set up plots

source = ColumnDataSource(data=dict(date=[], t1=[], t2=[], t1_returns=[], t2_returns=[]))
source_static = ColumnDataSource(data=dict(date=[], t1=[], t2=[], t1_returns=[], t2_returns=[]))
tools = 'pan,wheel_zoom,xbox_select,reset'

corr = figure(plot_width=350, plot_height=350,
              tools='pan,wheel_zoom,box_select,reset')
corr.circle('t1_returns', 't2_returns', size=2, source=source,
            selection_color="orange", alpha=0.6, nonselection_alpha=0.1, selection_alpha=0.4)

ts1 = figure(plot_width=900, plot_height=200, tools=tools, x_axis_type='datetime', active_drag="xbox_select")
ts1.line('date', 't1', source=source_static)
ts1.circle('date', 't1', size=1, source=source, color=None, selection_color="orange")

ts2 = figure(plot_width=900, plot_height=200, tools=tools, x_axis_type='datetime', active_drag="xbox_select")
ts2.x_range = ts1.x_range
ts2.line('date', 't2', source=source_static)
ts2.circle('date', 't2', size=1, source=source, color=None, selection_color="orange")

# set up callbacks

def ticker1_change(attrname, old, new):
    ticker2.options = nix(new, DEFAULT_TICKERS)
    update()

def ticker2_change(attrname, old, new):
    ticker1.options = nix(new, DEFAULT_TICKERS)
    update()

def update(selected=None):
    t1, t2 = ticker1.value, ticker2.value

    df = get_data(t1, t2)
    data = df[['t1', 't2', 't1_returns', 't2_returns']]
    source.data = data
    source_static.data = data

    update_stats(df, t1, t2)

    corr.title.text = '%s returns vs. %s returns' % (t1, t2)
    ts1.title.text, ts2.title.text = t1, t2

def update_stats(data, t1, t2):
    stats.text = str(data[[t1, t2, t1+'_returns', t2+'_returns']].describe())

ticker1.on_change('value', ticker1_change)
ticker2.on_change('value', ticker2_change)

def selection_change(attrname, old, new):
    t1, t2 = ticker1.value, ticker2.value
    data = get_data(t1, t2)
    selected = source.selected.indices
    if selected:
        data = data.iloc[selected, :]
    update_stats(data, t1, t2)

source.selected.on_change('indices', selection_change)

# set up layout
widgets = column(ticker1, ticker2, stats)
main_row = row(corr, widgets)
series = column(ts1, ts2)
layout = column(main_row, series)

# initialize
update()

curdoc().add_root(layout)
curdoc().title = "Stocks"