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N-D labeled arrays in Python

Project description

LArray: N-dimensional labelled arrays

Build Status Documentation Status

LArray is an open source Python library that aims to provide tools for easy exploration and manipulation of N-dimensional labelled data structures.

Library Highlights

  • N-dimensional labelled array objects to store and manipulate multi-dimensional data

  • I/O functions for reading and writing arrays in different formats: CSV, Microsoft Excel, HDF5, pickle

  • Arrays can be grouped into Session objects and loaded/dumped at once

  • User interface with an IPython console for rapid exploration of data

  • Compatible with the pandas library: Array objects can be converted into pandas DataFrame and vice versa.

Installation

Pre-built binaries

The easiest route to installing larray is through Conda. For all platforms installing larray can be done with:

conda install -c larray-project larray

This will install a lightweight version of larray depending only on Numpy and Pandas libraries only. Additional libraries are required to use the included graphical user interface, make plots or use special I/O functions for easy dump/load from Excel or HDF files. Optional dependencies are described below.

Installing larray with all optional dependencies can be done with

conda install -c larray-project larrayenv

You can also first add the channel larray-project to your channel list

conda config --add channels larray-project

and then install larray (or larrayenv) as

conda install larray

Building from source

The latest release of LArray is available from https://github.com/larray-project/larray.git

Once you have satisfied the requirements detailed below, simply run:

python setup.py install

Required Dependencies

  • Python 3.8, 3.9, 3.10 or 3.11

  • numpy (1.22 or later)

  • pandas (0.20 or later)

Optional Dependencies

For IO (HDF, Excel)

  • pytables: for working with files in HDF5 format.

  • xlwings: recommended package to get benefit of all Excel features of LArray. Only available on Windows and Mac platforms.

  • openpyxl: recommended package for reading and writing Excel 2010 files (ie: .xlsx)

  • xlsxwriter: alternative package for writing data, formatting information and, in particular, charts in the Excel 2010 format (ie: .xlsx)

  • xlrd: for reading data and formatting information from older Excel files (ie: .xls)

  • xlwt:

    for writing data and formatting information to older Excel files (ie: .xls)

  • larray_eurostat: provides functions to easily download EUROSTAT files as larray objects. Currently limited to TSV files.

For Graphical User Interface

LArray includes a graphical user interface to view, edit and compare arrays.

  • pyqt (version 5): required by larray-editor (see below).

  • pyside: alternative to PyQt.

  • qtpy: required by larray-editor.

  • larray-editor: required to use the graphical user interface associated with larray. It assumes that qtpy and either pyqt or pyside are installed. On windows, creates also a menu LArray in the Windows Start Menu.

For plotting

Miscellaneous

  • pydantic: required to use CheckedSession.

Documentation

The official documentation is hosted on ReadTheDocs at http://larray.readthedocs.io/en/stable/

Get in touch

  • To be informed of each new release, please subscribe to the announce mailing list.

  • For questions, ideas or general discussion, please use the Google Users Group.

  • To report bugs, suggest features or view the source code, please go to our GitHub website.

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