Writing Interactive Report with IPython


IPython Notebook

The IPython Notebook is an interactive computational environment, in which you can combine code execution, rich text, mathematics, plots and rich media

mpld3: A D3 Viewer for Matplotlib

This is an interactive D3js-based viewer which brings matplotlib graphics to the browser.


Run Cell

Keyboard Action
Shift-Enter run cell
Ctrl-Enter run cell in-place
Alt-Enter run cell, insert below

Cope and Paste

Keyboard Action
Ctrl-m x cut cell
Ctrl-m c copy cell
Ctrl-m v paste cell

Delete and Insert

Keyboard Action
Ctrl-m d delete cell
Ctrl-m z undo last cell deletion
Ctrl-m – split cell
Ctrl-m a insert cell above
Ctrl-m b insert cell below

Toggle Output

Keyboard Action
Ctrl-m o toggle output
Ctrl-m O toggle output scroll
Ctrl-m l toggle line numbers

Save notebook, change cells

Keyboard Action
Ctrl-m s save notebook
Ctrl-m j move cell down
Ctrl-m k move cell up
Ctrl-m y code cell
Ctrl-m m markdown cell
Ctrl-m t raw cell
Ctrl-m 1-6 heading 1-6 cell
Ctrl-m p select previous
Ctrl-m n select next
Ctrl-m i interrupt kernel
Ctrl-m . restart kernel
Ctrl-m h show keyboard shortcuts


import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import mpld3
from mpld3 import plugins

fig, ax = plt.subplots()
ax.grid(True, alpha=0.3)

N = 50
df = pd.DataFrame(index=range(N))
df['x'] = np.random.randn(N)
df['y'] = np.random.randn(N)
df['z'] = np.random.randn(N)

labels = []
for i in range(N):
 label = df.ix[[i], :].T
 label.columns = ['Row {0}'.format(i)]
 # .to_html() is unicode; so make leading 'u' go away with str()

points = ax.plot(df.x, df.y, 'o', color='b',
 mec='k', ms=15, mew=1, alpha=.6)

ax.set_title('HTML tooltips', size=20)

tooltip = plugins.PointHTMLTooltip(points[0], labels,
 voffset=10, hoffset=10, css=css)
plugins.connect(fig, tooltip)




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