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Python module Y118
numpy, scipy and matplotlib
Exercises, examples and other material relating to training module Y118. This topic is presented on public courses Learning to program in Python, Python Programming

Background
Numpy is a python package for heavy numbercrunching work - written as a wrapper around the underlying C / C++ code which allows you to get virtually the performance speed of C at the same time as the coding speed of Python for scientific research projects which involve large amounts of calculation. Scipy adds a wide range of statistical and mathematical algortithms, already coded for you, on top of numpy's underlying C based objects, and matplotlib adds a very flexible data plotting capability.
Articles and tips on this subjectupdated
3554Learning more about our web site - and learning how to learn about yours
There are quite a number of tools out there which will give you statistics about your web site - and quite a lot of people who will tell you various statistics about yours and theirs. But there's "Lies, Damned lies and statistics" according to Benjamin Disraeli. How do you really understand your traffic ...
2011-12-17
(longest)
29973D graphics - web site usage - simple matplotlib and python example
Some very interesting graphs from our server log data, courtesy of Python, numpy and matplotlib. Truly, a picture paints a thousand words. The data in the first and last diagrams is raw - showing exact number of hits per hour; in other diagrams I have used proximity smoothing which makes the trends ...
2010-10-13
 
2993Arrays v Lists - what is the difference, why use one or the other
If you want a program to run quickly through a data set (that's the sort of thing you'll be doing in heavy scientific work), you'll want the data loaded into successive memory locations - but that means that you have to know how much space to allocate before you set the data up. Otherwise, you'll find ...
2010-10-10
 
2992Matplotlib - graphing in Python - teaching examples
Matplotlib provides Python with a graph drawing and data representation tool that is extremely flexible - in fact so flexible that it's hard for the newcomer to know where to start. The following examples are very straightforward, but useful, graphs showing real data sets (from the second example onwards) ...
2010-10-10
 
2990What are numpy and scipy?
In Python, all the operators are really methods - in other words, you write   c = d + e and you're really writing   c = d . __add__ ( e ) So this means that it's possible to use the language to handle data of any sort, including data types that aren't supported at standard. It's ...
2010-10-09
 
2991Loading and saving data - Python / numpy
If you're using big data sets in Python, you're probably using the numpy module - providing you with fast data handlers at C speed of running, and Python coding speed. But how do you load that data in? Numpy also provides a number of data handlers, data setup routines, and also a save and restore ...
2010-10-09
 
Examples from our training material
aa   Tuple and list to numpy array conversions
mpl1.py   Hello matplotlib world
mpl2.py   Plotting a user data set
mpl3.py   Plotting multiple user data sets
mpl4.py   Two graphs on a canvas - top to bottom
mpl5.py   Two plots on a canvas - left to right
npgd   Loading data into numpy
nphw   Basic objects in numpy
npx   Loading binary data from file into numpy array
npx2   alternative scheme for loading binary data
tog1.py   Loading and storing numpy objects
xyz.py   3d and contour plots through numpy and matplotlib
Background information
Some modules are available for download as a sample of our material or under an Open Training Notes License for free download from http://www.training-notes.co.uk.
Topics covered in this module
Introduction to numpy, scipy and matplotib.
Sourcing and installing numpy.
Data type wrappers - how and why.
N-Dimensional array objects.
Saving and loading - files, databases and broadcasting.
Matrix Manipulation.
Sourcing and installing scipy.
Linear Algebra and Fourier Transform.
Random Number capabilities.
Numerical Integration.
Ordinary Differential Equations (ODEs).
Sourcing and installing matplotlib.
First steps in data graphing with matplotlib.
Tuning your graphs.
Multiple plots, graphs, axes and more.
Pie, Polar, Histogram, Scatter plots, etc.
The artist around the graph.
Using matplotlib with numpy.
Using matplotlib with wxpython.
Complete learning
If you are looking for a complete course and not just a information on a single subject, visit our Listing and schedule page.

Well House Consultants specialise in training courses in Python, Perl, PHP, and MySQL. We run Private Courses throughout the UK (and beyond for longer courses), and Public Courses at our training centre in Melksham, Wiltshire, England. It's surprisingly cost effective to come on our public courses - even if you live in a different country or continent to us.

We have a technical library of over 700 books on the subjects on which we teach. These books are available for reference at our training centre. Also available is the Opentalk Forum for discussion of technical questions.


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