1. Python Visualization Tools: Pandas, Seaborn, ggplot郝蕊

2. Pandas
the fundamental high-level building block for doing practical, real world data analysis in Python
get data from csv, excel, hdf, sql, json, html, stata
basic plot function, may need to learn matplotlib to customize
pandas + other visualization library

3. Pandas - Data Structures
Series
one-dimensional labeled array
s = Series(data, index=index)
python dict
ndarray
scalar value
ndarray-like
dict-like
vectorized operation
Series(randn(5), index=['a', 'b', 'c', 'd', 'e']) a b c d e
d = {'a' : 0., 'b' : 1., 'c' : 2.}
Series(d, index=['b', 'c', 'd', 'a'])
b 1
c 2
d NaN
a 0

4. Pandas – Data Structures
DataFrame
2-dimensional labeled
columns, index
df = DataFrame(data, index=index)
dict of series or dicts
dict of ndarrays / lists
list of dicts …
d =
{'one' : Series([1., 2.], index=['a', 'b']),
'two' : Series([1., 2., 3.], index=['a', 'b', 'c'])}
DataFrame(d, index=[‘c', 'a'],
columns=['two', 'three'])
two three
c NaN
a NaN
d = {'one' : [1., 2., 3., 4.], 'two' : [4., 3., 2., 1.]}
DataFrame(d, index=['a', 'b', 'c', 'd'])
one two a b c d

5. Pandas – Data Structures
Panel
3-dimensional data
wp = Panel(data, items,major_axis,minor_axis)
3D ndarray
dict of dataframe
wp = Panel(randn(2, 5, 4),
items=['Item1','Item2'],
major_axis=date_range('1/1/2000', periods=5),
minor_axis=['A', 'B', 'C', 'D']) A B C D

6. Seaborn Python visualization library based on matplotlib
making more complicated plots simpler to create, does not do much for simple chart
built in styles to quickly change the color theme
support for numpy, pandas data structures
support for scipy, statsmodels statictical routines

7. Seaborn – Plot Gallery

8. Seaborn – Plot Types Linear model plots quantitative data
categorical data
regression: simple or multiple
faceted linear model
nonlinear, logistic regression
outliers
marginal distributions
examining model residuals
pairwise relationship
Residuals: 残差

9. Seaborn – Plot Types Matrix plots Timeseries plots Miscellaneous plots
cluster map
heat map
Timeseries plots
Miscellaneous plots

10. Seaborn - Example

11. ggplot
improve the visual appeal of matplotlib visualizations in a simple way
port of ggplot2 of R, some API is non-pythonic but very powerful
support pandas

12. ggplot – Plot Gallery bar density facetgrid histogram line scatter
smooth

13. ggplot - Example