Getting Started

Let’s plot some stocks and make a line chart. Get data with Pandas, make visualization with Bearcart:

import bearcart
import pandas as pd

html_path = r'index.html'
data_path = r'data.json'
js_path = r'rickshaw.min.js'
css_path = r'rickshaw.min.css'


#All of the following import code comes from Wes McKinney's book, Python
#for Data Analysis

import pandas.io.data as web

all_data = {}

for ticker in ['AAPL', 'GOOG']:
    all_data[ticker] = web.get_data_yahoo(ticker, '1/1/2010', '1/1/2013')

price = pd.DataFrame({tic: data['Adj Close']
                      for tic, data in all_data.iteritems()})

vis = bearcart.Chart(price)
vis.create_chart(html_path=html_path, data_path=data_path,
                 js_path=js_path, css_path=css_path)

Go take a look at this bl.ock for the interactive example with the tooltip and legend data selection.

Lets try more companies, and an area plot:

all_data = {}
for ticker in ['AAPL', 'GOOG', 'XOM', 'MSFT', 'INTC', 'YHOO']:
    all_data[ticker] = web.get_data_yahoo(ticker, '1/1/2012', '1/1/2013')
price = pd.DataFrame({tic: data['Adj Close']
                      for tic, data in all_data.iteritems()})

vis = bearcart.Chart(price, plt_type='area')

Interactive version here. Finally, let’s make a scatterplot with some custom colors:

df = pd.concat([price['AAPL'], price['GOOG']], axis=1)[:100]

vis = bearcart.Chart(df, plt_type='scatterplot', colors={'AAPL': '#1d4e69',
                                                         'GOOG': '#3b98ca' })

Interactive example here

If you don’t want some of the chart features, like the legend, hover, x-axis, etc, you can just pass those parameters as false when defining the chart:

vis = bearcart.Chart(df, hover=False, legend=False)

That’s it- a small little library for making nice little interactive timeseries charts. Happy plotting!