[Blends-commit] r2953 - /projects/science/trunk/debian-science/tasks/statistics

[yoh at users.alioth.debian.org]

Author: yoh
Date: Tue Sep 13 15:32:07 2011
New Revision: 2953

URL: http://svn.debian.org/wsvn/blends/?sc=1&rev=2953
Log:
injecting pandas

Modified:
    projects/science/trunk/debian-science/tasks/statistics

Modified: projects/science/trunk/debian-science/tasks/statistics
URL: http://svn.debian.org/wsvn/blends/projects/science/trunk/debian-science/tasks/statistics?rev=2953&op=diff
==============================================================================
--- projects/science/trunk/debian-science/tasks/statistics (original)
+++ projects/science/trunk/debian-science/tasks/statistics Tue Sep 13 15:32:07 2011
@@ -71,3 +71,28 @@
 
 Depends: python-openturns
 Why: Uncertainty quantification in numerical simulation
+
+ ; Added by blends-inject 0.0.7. [Please note here if modified manually]
+Suggests: pandas
+Homepage: http://pandas.sourceforge.net
+Language: Python, Cython
+WNPP: 641464
+License: BSD-3
+Pkg-URL: http://neuro.debian.net/pkgs/cctools.html
+Pkg-Description: data structures for "relational" or "labeled" data
+ pandas is a Python package providing fast, flexible, and expressive
+ data structures designed to make working with "relational" or
+ "labeled" data both easy and intuitive. It aims to be the fundamental
+ high-level building block for doing practical, real world data
+ analysis in Python. pandas is well suited for many different kinds of
+ data:
+ .
+  - Tabular data with heterogeneously-typed columns, as in an SQL
+    table or Excel spreadsheet
+  - Ordered and unordered (not necessarily fixed-frequency) time
+    series data.
+  - Arbitrary matrix data (homogeneously typed or heterogeneous) with
+    row and column labels
+  - Any other form of observational / statistical data sets. The data
+    actually need not be labeled at all to be placed into a pandas
+    data structure