Using Bokeh 0.8.1, how can i display a long timeserie, but start 'zoomed-in' on one part, while keeping the rest of data available for scrolling ?
For instance, considering the following time serie (IBM stock price since 1980), how could i get my chart to initially display only price since 01/01/2014 ?
Example code :
import pandas as pd
import bokeh.plotting as bk
from bokeh.models import ColumnDataSource
bk.output_notebook()
TOOLS="pan,wheel_zoom,box_zoom,reset,save"
# Quandl data, too lazy to generate some random data
df = pd.read_csv('https://www.quandl.com/api/v1/datasets/GOOG/NYSE_IBM.csv')
df['Date'] = pd.to_datetime(df['Date'])
df = df[['Date', 'Close']]
#Generating a bokeh source
source = ColumnDataSource()
dtest = {}
for col in df:
dtest[col] = df[col]
source = ColumnDataSource(data=dtest)
# plotting stuff !
p = bk.figure(title='title', tools=TOOLS,x_axis_type="datetime", plot_width=600, plot_height=300)
p.line(y='Close', x='Date', source=source)
bk.show(p)
outputs :
but i want to get this (which you can achieve with the box-zoom tool - but I'd like to immediately start like this)
Edit: the answer below is very outdated. Most common datetime types have been usable directly with Bokeh ranges for may years now.
OLD ANSWER:
So, it looks (as of 0.8.1) that we need to add some more convenient ways to set ranges with datetime values. That said, although this is a bit ugly, it does currently work for me:
import time, datetime
x_range = (
time.mktime(datetime.datetime(2014, 1, 1).timetuple())*1000,
time.mktime(datetime.datetime(2016, 1, 1).timetuple())*1000
)
p = bk.figure(
title='title', tools=TOOLS,x_axis_type="datetime",
plot_width=600, plot_height=300, x_range=x_range
)