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><em><strong>My main focus is how to write code for same visualization in Bokeh</strong></em></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="https://i.stack.imgur.com/dmCHs.png" rel="noreferrer"><img src="https://i.stack.imgur.com/dmCHs.png" alt="enter image description here" /></a></p>