A Polished Notebook

This Jupyter presentation looks nice. Because it hides many of the Jupyter elements and makes code visibility optional (see button on top), it is appropriate for non-technical audiences or for those who just want a quick summary of your results. For instructions on how to do this, see my blog post.

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In [1]:
import plotly
import plotly.graph_objs as go
import string
import numpy as np

x = np.random.randn(26)
y = x + np.random.randn(26)
labels = ['Observation ' + c for c in list(string.ascii_uppercase)]

trace = go.Scatter(
    name="Sample Data",

fig = dict(data=[trace], layout={})
fig['layout']['xaxis'] = dict(title='Variable X')
fig['layout']['yaxis'] = dict(title='Variable Y')
plotly.offline.iplot(fig, show_link=False)