numpy

NumPy is a general-purpose array-processing package designed to efficiently manipulate large multi-dimensional arrays of arbitrary records without sacrificing too much speed for small multi-dimensional arrays.

Sample histogram

From http://bespokeblog.wordpress.com/2011/07/11/basic-data-plotting-with-matplotlib-part-3-histograms/

   1 import matplotlib.pyplot as plt
   2 from numpy.random import normal
   3 gaussian_numbers = normal(size=1000)
   4 plt.hist(gaussian_numbers)
   5 plt.title("Gaussian Histogram")
   6 plt.xlabel("Value")
   7 plt.ylabel("Frequency")
   8 plt.show()

SlackBuilds

numpy

Package 32 bit: numpy-1.6.2-i486-1_SBo.tgz

Package 64 bit: numpy-1.6.2-x86_64-1_SBo.tgz

pytz

Package 32 bit: pytz-2012h-i486-1_SBo.tgz

Package 64 bit: pytz-2012h-x86_64-1_SBo.tgz

python-dateutil

Package 32 bit: python-dateutil-2.1-i486-1_SBo.tgz

Package 64 bit: python-dateutil-2.1-x86_64-1_SBo.tgz

six

Package 32 bit: six-1.3.0-i486-1_SBo.tgz

Package 64 bit: six-1.4.1-x86_64-1_SBo.tgz

pysetuptools

Package 32 bit: pysetuptools-0.8-i486-1_SBo.tgz

Package 64 bit: pysetuptools-0.9.8-x86_64-1_SBo.tgz

matplotlib

Package 32 bit: matplotlib-1.1.1-i486-1_SBo.tgz

Package 64 bit: matplotlib-1.1.1-x86_64-1_SBo.tgz

Python/numpy (last edited 2013-11-05 11:25:59 by bl13-23-50)