`Dark` is an acronym for "Data Analysis and Reporting Kit". It helps find patterns in a set of irregular (mixed) data, sort various documents and pile them in stacks by certain properties, define schemata for existing data, build pivot tables and calculate various aggregates. Great for CSV, JSON, etc. ***NOTE*** this is a mirror of the repo at B…
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neithere/dark
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Dark ==== `Dark` is an acronym for "Data Analysis and Reporting Kit". It helps find patterns in a set of irregular (mixed) data, sort various documents and pile them in stacks by certain properties, define schemata for existing data, build pivot tables and calculate various aggregates. Great for CSV, JSON, etc. Moreover, it has cookies. Installation ------------ $ pip install dark Documentation ------------- See the `complete documentation`_ for details. .. _complete documentation: http://packages.python.org/dark Author ------ Initially written by Andrey Mikhailenko in 2009 with invaluable feedback from Ilya Musabirov. See the file AUTHORS for a complete authors list of this application. Please feel free to submit patches, report bugs or request features: http://bitbucket.org/neithere/dark/ Licensing --------- Dark is free software; you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation; either version 3 of the License, or (at your option) any later version. Dark is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. You should have received a copy of the GNU Lesser General Public License along with this program; see the file COPYING.LESSER. If not, see <http://www.gnu.org/licenses/>.
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`Dark` is an acronym for "Data Analysis and Reporting Kit". It helps find patterns in a set of irregular (mixed) data, sort various documents and pile them in stacks by certain properties, define schemata for existing data, build pivot tables and calculate various aggregates. Great for CSV, JSON, etc. ***NOTE*** this is a mirror of the repo at B…
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