A number of third party libraries defined their own custom display logic. This gives their objcts rich output by default when used in the Notebook.
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from IPython.display import display
Pandas is a data analysis library for Python. Its DataFrame objects have an HTML table representation in the Notebook.
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import pandas
Here is a small amount of stock data for APPL:
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%%writefile data.csv
Date,Open,High,Low,Close,Volume,Adj Close
2012-06-01,569.16,590.00,548.50,584.00,14077000,581.50
2012-05-01,584.90,596.76,522.18,577.73,18827900,575.26
2012-04-02,601.83,644.00,555.00,583.98,28759100,581.48
2012-03-01,548.17,621.45,516.22,599.55,26486000,596.99
2012-02-01,458.41,547.61,453.98,542.44,22001000,540.12
2012-01-03,409.40,458.24,409.00,456.48,12949100,454.53
Read this as into a DataFrame:
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df = pandas.read_csv('data.csv')
And view the HTML representation:
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df
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SymPy is a symbolic computing library for Python. Its equation objects have LaTeX representations that are rendered in the Notebook.
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from sympy.interactive.printing import init_printing
init_printing(use_latex='mathjax')
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from __future__ import division
import sympy as sym
from sympy import *
x, y, z = symbols("x y z")
k, m, n = symbols("k m n", integer=True)
f, g, h = map(Function, 'fgh')
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Rational(3,2)*pi + exp(I*x) / (x**2 + y)
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a = 1/x + (x*sin(x) - 1)/x
a
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(1/cos(x)).series(x, 0, 6)
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Vincent is a visualization library that uses the Vega visualization grammar to build d3.js based visualizations in the Notebook and on http://nbviewer.ipython.org. Visualization objects in Vincetn have rich HTML and JavaSrcript representations.
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import vincent
import pandas as pd
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import pandas.io.data as web
import datetime
all_data = {}
date_start = datetime.datetime(2010, 1, 1)
date_end = datetime.datetime(2014, 1, 1)
for ticker in ['AAPL', 'IBM', 'YHOO', 'MSFT']:
all_data[ticker] = web.DataReader(ticker, 'yahoo', date_start, date_end)
price = pd.DataFrame({tic: data['Adj Close']
for tic, data in all_data.items()})
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vincent.initialize_notebook()
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line = vincent.Line(price[['AAPL', 'IBM', 'YHOO', 'MSFT']], width=600, height=300)
line.axis_titles(x='Date', y='Price')
line.legend(title='Ticker')
display(line)