Python DataMatrix

An intuitive, Pythonic way to work with tabular data.

Sebastiaan Mathôt
Copyright 2015-2022
https://pydatamatrix.eu/

Contents

• About
• Features
• Ultra-short cheat sheet
• Documentation
• Dependencies
• Installation
• License

About

DataMatrix is an intuitive Python library for working with column-based and continuous 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
• Requires only the Python standard libraries (but you can use numpy to improve performance)
• Great support for functional programming, including advanced memoization (caching)
• Mix two-dimensional (series) and one-dimensional data in a single data structure
• Compatible with your favorite tools for numeric computation:
  • seaborn and matplotlib for plotting
  • scipy, statsmodels, and pingouin for statistics
  • Convert to and from pandas.DataFrame
  • Looks pretty inside a Jupyter Notebook

Ultra-short cheat sheet

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('Mean: %s' % dm.fibonacci.mean)
# Multiply all fibonacci cells by 2
dm.fibonacci_times_two = 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

• Python >= 3.7

Optional:

• numpy and scipy for using the FloatColumn, IntColumn, and SeriesColumn objects
• prettytable for creating a text representation of a DataMatrix (e.g. to print it out)
• openpyxl for reading and writing .xlsx files
• fastnumbers for improved performance

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!

pip install datamatrix==0.9

Anaconda

conda install datamatrix -c conda-forge

Ubuntu

sudo add-apt-repository ppa:smathot/cogscinl
sudo apt-get update
sudo apt install python3-datamatrix

License

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