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3520135210 of 42403 results
66194.
Numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. It accepts the expression as a string, analyzes it, rewrites it more efficiently, and compiles it to faster Python code on the fly. It's the next best thing to writing the expression in C and compiling it with a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler at runtime.
Description
(no translation yet)
Located in Package: python3-numexpr-dbg Package: python3-numexpr Package: python-numexpr-dbg Package: python-numexpr
66195.
Module for exploring Python object reference graphs (Python3 version)
Summary
(no translation yet)
Located in Package: python3-objgraph
66196.
objgraph is a module that lets you visually explore Python object graphs.
Description
(no translation yet)
Located in Package: python3-objgraph Package: python-objgraph-doc Package: python-objgraph
66197.
It can be used for counting and statistics, finding root references responsible for large object trees and export the object reference graphs in graphviz format.
Description
(no translation yet)
Located in Package: python3-objgraph Package: python-objgraph-doc Package: python-objgraph
66198.
nosetests output to mimic the output of openstack's run_tests.py - Python 3.x
Summary
(no translation yet)
Located in Package: python3-openstack.nose-plugin
66199.
This package provides a nose plugin that allow's nosetests output to mimic the output of openstack's run_tests.py.
Description
(no translation yet)
Located in Package: python3-openstack.nose-plugin Package: python-openstack.nose-plugin
66200.
data structures for "relational" or "labeled" data - Python 3
Summary
(no translation yet)
Located in Package: python3-pandas
66201.
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:
Description
(no translation yet)
Located in Package: python3-pandas Package: python-pandas
66202.
- 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
Description
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Located in Package: python3-pandas Package: python-pandas
66203.
low-level implementations and bindings for pandas - Python 3
Summary
(no translation yet)
Located in Package: python3-pandas-lib
3520135210 of 42403 results

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