Transforming visualization from Seaborn to Bokeh
<p>I want the similar visualization as shown below using <strong>Bokeh</strong>. As I am new to <strong>Bokeh</strong> , I might be wondering is there any code that is as concise as the below one using <strong>Seaborn</strong> ?</p>

<p><strong><em>My main focus is how to write code for same visualization in Bokeh</em></strong></p>

<h1>dataset</h1>

<pre><code>data = pd.read_csv('http://www-bcf.usc.edu/~gareth/ISL/Advertising.csv',index_col = 0)
</code></pre>

<h1>Plotting the dataset</h1>

<pre><code>import seaborn as sns  

sns.pairplot(data, x_vars = ['TV', 'Radio','Newspaper'], y_vars = ['Sales'],               
             size =7, aspect =.7, kind = 'reg')
</code></pre>

<p><strong>Also the code in Seaborn doesn't require to enter the best fitted line</strong> . It automatically generates the best fitted line in the graph with a shadow of <strong>confidence interval</strong> . <strong>Is this kind of plotting possible in Bokeh ?</strong></p>

<p><a href="http://i.stack.imgur.com/dmCHs.png" rel="nofollow"><img src="http://i.stack.imgur.com/dmCHs.png" alt="enter image description here"></a></p>

<p>The above charts are certainly <em>possible</em> with Bokeh, in the sense that Bokeh could draw them, without any question. But it would take some work, and require more code, than with Seaborn. Basically you'd have to compute all the coordinates and set up all the glyphs "by hand". As of Bokeh <code>0.12.2</code>, there is not currently any comparable "single line" high level function or chart in <code>bokeh.charts</code>. </p>

<p>Adding more high level chart types lie this to <code>bokeh.charts</code> is definitely something that we'd like, but it will probably require motivated new contributors to make that happen. Fortunately, this area of Bokeh is pure-python and probably the most approachable for new contributors. If you are possibly interested in contributing to Bokeh, I encourage you to reach out on the <a href="https://groups.google.com/a/continuum.io/forum/?pli=1#!forum/bokeh" rel="nofollow">public mailing list</a> or <a href="https://gitter.im/bokeh/bokeh" rel="nofollow">gitter chat channel</a>. We are always happy to answer questions and help people get started. </p>

python data-visualization linear-regression seaborn bokeh