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https://github.com/open-cogsci/datamatrix

An intuitive, Pythonic way to work with tabular data

https://github.com/open-cogsci/datamatrix

Science Score: 26.0%

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    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
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    .zenodo.json file
    Found .zenodo.json file
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    DOI references
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    Academic publication links
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    Scientific vocabulary similarity
    Low similarity (12.1%) to scientific vocabulary

Keywords

analysis data-analysis data-structures python scientific-computing
Last synced: 5 months ago · JSON representation

Repository

An intuitive, Pythonic way to work with tabular data

Basic Info
  • Host: GitHub
  • Owner: open-cogsci
  • License: gpl-3.0
  • Language: Python
  • Default Branch: 1.0
  • Homepage: https://pydatamatrix.eu/
  • Size: 35.2 MB
Statistics
  • Stars: 26
  • Watchers: 3
  • Forks: 10
  • Open Issues: 0
  • Releases: 24
Topics
analysis data-analysis data-structures python scientific-computing
Created about 10 years ago · Last pushed 8 months ago
Metadata Files
Readme License

readme.md

Python DataMatrix

An intuitive, Pythonic way to work with tabular data.

Sebastiaan Mathôt
Copyright 2015-2025
https://pydatamatrix.eu/

Publish to PyPi

Tests

Contents

About

DataMatrix is an intuitive Python library for working with column-based, time-series, and multidimensional data. It's a light-weight and easy-to-use alternative to pandas.

DataMatrix is also one of the core libraries of OpenSesame, a graphical experiment builder for the social sciences, and Rapunzel, a modern code editor for numerical computing with Python and R.

Features

  • An intuitive syntax that makes your code easy to read
  • Mix tabular data with time series and multidimensional data in a single data structure
  • Support for large data by intelligent (and automatic) offloading of data to disk when memory is running low
  • Advanced memoization (caching)
  • Requires only the Python standard libraries (but you can use numpy to improve performance)
  • Compatible with your favorite data-science libraries:
    • seaborn and matplotlib for plotting
    • scipy, statsmodels, and pingouin for statistics
    • mne for analysis of electroencephalographic (EEG) and magnetoencephalographic (MEG) data
    • Convert to and from pandas.DataFrame
    • Looks pretty inside a Jupyter Notebook

Ultra-short cheat sheet

```python from datamatrix import DataMatrix, io

Read a DataMatrix from file

dm = io.readtxt('data.csv')

Create a new DataMatrix

dm = DataMatrix(length=5)

The first two rows

print(dm[:2])

Create a new column and initialize it with the Fibonacci series

dm.fibonacci = 0, 1, 1, 2, 3

You can also specify column names as if they are dict keys

dm['fibonacci'] = 0, 1, 1, 2, 3

Remove 0 and 3 with a simple selection

dm = (dm.fibonacci > 0) & (dm.fibonacci < 3)

Get a list of indices that match certain criteria

print(dm[(dm.fibonacci > 0) & (dm.fibonacci < 3)])

Select 1, 1, and 2 by matching any of the values in a set

dm = dm.fibonacci == {1, 2}

Select all odd numbers with a lambda expression

dm = dm.fibonacci == (lambda x: x % 2)

Change all 1s to -1

dm.fibonacci[dm.fibonacci == 1] = -1

The first two cells from the fibonacci column

print(dm.fibonacci[:2])

Column mean

print(dm.fibonacci[...])

Multiply all fibonacci cells by 2

dm.fibonaccitimestwo = dm.fibonacci * 2

Loop through all rows

for row in dm: print(row.fibonacci) # get the fibonacci cell from the row

Loop through all columns

for colname, col in dm.columns: for cell in col: # Loop through all cells in the column print(cell) # do something with the cell

Or just see which columns exist

print(dm.column_names) ```

Documentation

The basic documentation (including function and module references) is hosted on https://pydatamatrix.eu/. Additional tutorials can be found in the data-science course on https://pythontutorials.eu/.

Dependencies

DataMatrix requires only the Python standard library. That is, you can use it without installing any additional Python packages (although the pip and conda packages install some of the optional dependencies by default). Python 3.7 and higher are supported.

The following packages are required for extra functionality:

  • numpy and scipy for using the FloatColumn, IntColumn, SeriesColumn, MultiDimensionalColumn objects
  • pandas for conversion to and from pandas.DataFrame
  • mne for conversion to and from mne.Epochs and mne.TFR
  • fastnumbers for improved performance
  • prettytable for creating a text representation of a DataMatrix (e.g. to print it out)
  • openpyxl for reading and writing .xlsx files
  • json_tricks for hashing, serialization to and from json, and memoization (caching)
  • tomlkit for reading configuration from pyproject.toml
  • psutil for dynamic loading of large data

Installation

PyPi

~~~ pip install datamatrix ~~~

Historical note: The DataMatrix project used to correspond to another package of the same name, which was discontinued in 2010. If you want to install this package, you can do still do so by providing an explicit version (0.9 is the latest version of this package), as shown below. With thanks to dennogumi.org for handing over this project's entry on PyPi, thus avoiding much unnecessary confusion!

~~~

Doesn't install datamatrix but a previous package by the same name!

pip install datamatrix==0.9 ~~~

Anaconda

~~~ conda install datamatrix -c conda-forge ~~~

Ubuntu

~~~ sudo add-apt-repository ppa:smathot/cogscinl # for stable releases sudo add-apt-repository ppa:smathot/rapunzel # for development releases sudo apt-get update sudo apt install python3-datamatrix ~~~

License

python-datamatrix is licensed under the GNU General Public License v3.

Owner

  • Name: Cogsci.nl
  • Login: open-cogsci
  • Kind: organization
  • Email: smathot@cogsci.nl
  • Location: Groningen

Open-source scientific software

GitHub Events

Total
  • Release event: 2
  • Watch event: 2
  • Push event: 5
  • Create event: 2
Last Year
  • Release event: 2
  • Watch event: 2
  • Push event: 5
  • Create event: 2

Committers

Last synced: about 2 years ago

All Time
  • Total Commits: 523
  • Total Committers: 3
  • Avg Commits per committer: 174.333
  • Development Distribution Score (DDS): 0.004
Past Year
  • Commits: 69
  • Committers: 2
  • Avg Commits per committer: 34.5
  • Development Distribution Score (DDS): 0.014
Top Committers
Name Email Commits
Sebastiaan Mathot s****t@c****l 521
Julieta j****o@g****m 1
pgajdos p****s@s****z 1
Committer Domains (Top 20 + Academic)
suse.cz: 1 cogsci.nl: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 15
  • Total pull requests: 3
  • Average time to close issues: over 1 year
  • Average time to close pull requests: 2 months
  • Total issue authors: 6
  • Total pull request authors: 3
  • Average comments per issue: 0.67
  • Average comments per pull request: 1.33
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • smathot (10)
  • courtneygoodridge (1)
  • egaudrain (1)
  • dschreij (1)
  • JulietaLaurino (1)
  • leeweizhe1993 (1)
Pull Request Authors
  • JulietaLaurino (1)
  • pgajdos (1)
  • TrellixVulnTeam (1)
Top Labels
Issue Labels
bug (5) enhancement (4)
Pull Request Labels

Packages

  • Total packages: 2
  • Total downloads:
    • pypi 940 last-month
  • Total dependent packages: 7
    (may contain duplicates)
  • Total dependent repositories: 2
    (may contain duplicates)
  • Total versions: 36
  • Total maintainers: 1
pypi.org: datamatrix

This file is part of datamatrix.

  • Versions: 19
  • Dependent Packages: 5
  • Dependent Repositories: 2
  • Downloads: 940 Last month
Rankings
Dependent packages count: 1.6%
Downloads: 7.8%
Average: 9.0%
Forks count: 11.4%
Dependent repos count: 11.5%
Stargazers count: 12.7%
Maintainers (1)
smathot
Last synced: 6 months ago
conda-forge.org: datamatrix
  • Versions: 17
  • Dependent Packages: 2
  • Dependent Repositories: 0
Rankings
Dependent packages count: 19.5%
Average: 26.8%
Dependent repos count: 34.0%
Last synced: 6 months ago

Dependencies

.github/workflows/publish-package.yaml actions
  • actions/checkout v3 composite
  • actions/setup-python v3 composite
  • pypa/gh-action-pypi-publish 27b31702a0e7fc50959f5ad993c78deac1bdfc29 composite
.github/workflows/run-unittests.yaml actions
  • actions/checkout v3 composite
  • actions/setup-python v4 composite
pyproject.toml pypi
  • json-tricks *
  • numpy *
  • openpyxl *
  • prettytable *
  • psutil *
  • scipy *
  • tomlkit *
setup.py pypi