Plotting data with python and pylab

Barcelona Python Meetup Plotting data with python and pylab Giovanni M. Dall'Olio

Problem statement  Let's say we have a table of data like this: name country apples pears Giovanni Italy 31 13 Mario Italy 23 33 Luigi Italy 0 5 Margaret England 22 13 Albert Germany 15 6  How to read it in python?  How to do some basic plotting?

Alternatives for plotting data in python  Pylab (enthought)→ Matlab/Octave approach  Enthought → extended version of Pylab (free for academic use)  rpy/rpy2 → allows to run R commands within python  Sage → interfaces python with Matlab, R, octave, mathematica, ...

The Pylab system  pylab is a system of three libraries, which together transform python in a Matlablike environment  It is composed by:  Numpy (arrays, matrices, complex numbers, etc.. in python)  Scipy (extended scientific/statistics functions)  Matplotlib (plotting library)  iPython (extended interactive interpreter)

How to install pylab  There are many alternatives to install PyLab:  use the package manager of your linux distro  use enthought's distribution ( http://www.enthought.com/products/epd.php) (free for academic use)  compile and google for help!  Numpy and scipy contains some Fortran libraries, therefore easy_install doesn't work well with them

ipython -pylab  Ipython is an extended version of the standard python interpreter  It has a modality especially designed for pylab  The standard python interpreter doesn't support very well plotting (not multithreading)  So if you want an interactive interpreter, use ipython with the pylab option: $: alias pylab=”ipython -pylab” $: pylab In [1]:

Why the python interpreter is not the best for plotting Gets blocked when you create a plot

How to read a CSV file with python  To read a file like this in pylab: name country apples pears Giovanni Italy 31 13 Mario Italy 23 33 Luigi Italy 0 5 Margaret England 22 13 Albert Germany 15 6  → Use the function 'matplotlib.mlab.csv2rec' >>> data = csv2rec('exampledata.txt', delimiter='t')

Numpy - record arrays  csv2rec stores data in a numpy recarray object, where you can access columns and rows easily: >>> print data['name'] ['Giovanni' 'Mario' 'Luigi' 'Margaret' 'Albert'] >>> data['apples'] array([31, 23, 0, 22, 15]) >>> data[1] ('Mario', 'Italy', 23, 33)

Alternative to csv2rec  numpy.genfromtxt (new in 2009)  More options than csv2rec, included in numpy  Tricky default parameters: need to specify dtype=None >>> data = numpy.genfromtxt('datafile.txt', dtype=None) >>> data array....

Barchart >>> data = csv2rec('exampledata.txt', delimiter='t') >>> bar(arange(len(data)), data['apples'], color='red', width=0.1, label='apples') >>> bar(arange(len(data))+0.1, data['pears'], color='blue', width=0.1, label='pears') >>> xticks(range(len(data)), data['name'], ) >>> legend() >>> grid('.')

Barchart >>> data = csv2rec('exampledata.txt', delimiter='t') >>> figure() >>> clf() Read a CSV file and storing it in a recordarray object Use figure() and cls() to reset the graphic device

Barchart >>> data = csv2rec('exampledata.txt', delimiter='t') >>> bar(x=arange(len(data)), y=data['apples'], color='red', width=0.1, label='apples')  The bar function creates a barchart

Barchart >>> data = csv2rec('exampledata.txt', delimiter='t') >>> bar(x=arange(len(data)), y=data['apples'], color='red', width=0.1, label='apples') >>> bar(arange(len(data))+0.1, data['pears'], color='blue', width=0.1, label='pears')  This is the second barchart

Barchart >>> data = csv2rec('exampledata.txt', delimiter='t') >>> bar(x=arange(len(data)), y=data['apples'], color='red', width=0.1, label='apples') >>> bar(arange(len(data))+0.1, data['pears'], color='blue', width=0.1, label='pears') >>> xticks(range(len(data)), data['name'], )  Redefining the labels in the X axis (xticks)

Barchart >>> data = csv2rec('exampledata.txt', delimiter='t') >>> bar(x=arange(len(data)), y=data['apples'], color='red', width=0.1, label='apples') >>> bar(arange(len(data))+0.1, data['pears'], color='blue', width=0.1, label='pears') >>> xticks(range(len(data)), data['name'], ) >>> legend() >>> grid('.') >>> title('apples and pears by person')  Adding legend, grid, title

Barchart (result)

Pie Chart >>> pie(data['pears'], labels=data['name']) >>> pie(data['pears'], labels=['%sn(%s pears)' % (i,j) for (i, j) in zip(data['name'], data['pears'])] )

Pie chart (result)

A plot chart >>> x = linspace(1,10, 10) >>> y = randn(10) >>> plot(x,y, 'r.', ms=15)

An histogram >>> x = randn(1000) >>> hist(x, bins=40) >>> title('histogram of random numbers')

Matplotlib gallery

Scipy Cookbook

Thanks for the attention!!  PyLab http://www.scipy.org/PyLab  matplotlib http://matplotlib.sourceforge.net/  scipy http://www.scipy.org/  numpy http://numpy.scipy.org/  ipython http://ipython.scipy.org/moin/  These slides: http://bioinfoblog.it

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Plotting data with python and pylab

by Giovanni Dall'Olio

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