Open Source Python Data Management Systems

Asymptote is a powerful descriptive vector graphics language for technical drawing, inspired by MetaPost but with an improved C++-like syntax. Asymptote provides for figures the same high-quality typesetting that LaTeX does for scientific text.

pandas-profiling generates profile reports from a pandas DataFrame. The pandas df.describe() function is handy yet a little basic for exploratory data analysis. pandas-profiling extends pandas DataFrame with df.profile_report(), which automatically generates a standardized univariate and multivariate report for data understanding. High correlation warnings, based on different correlation metrics (Spearman, Pearson, Kendall, Cramér’s V, Phik). Most common categories (uppercase, lowercase, separator), scripts (Latin, Cyrillic) and blocks (ASCII, Cyrilic). File sizes, creation dates, dimensions, indication of truncated images and existance of EXIF metadata. Mostly global details about the dataset (number of records, number of variables, overall missigness and duplicates, memory footprint). Comprehensive and automatic list of potential data quality issues (high correlation, skewness, uniformity, zeros, missing values, constant values, between others).

Great Expectations helps data teams eliminate pipeline debt, through data testing, documentation, and profiling. Software developers have long known that testing and documentation are essential for managing complex codebases. Great Expectations brings the same confidence, integrity, and acceleration to data science and data engineering teams. Expectations are assertions for data. They are the workhorse abstraction in Great Expectations, covering all kinds of common data issues. Expectations are a great start, but it takes more to get to production-ready data validation. Where are Expectations stored? How do they get updated? How do you securely connect to production data systems? How do you notify team members and triage when data validation fails? Great Expectations supports all of these use cases out of the box. Instead of building these components for yourself over weeks or months, you will be able to add production-ready validation to your pipeline in a day.

This is an ETL software which loads data from DBF/XBase files into MySQL. This utility has command line interface, designed to work without user interaction.

Parse, analyze and -- most importantly -- use COBOL data definitions. This gives you access to COBOL data from Python programs. Write data analyzers, one-time data conversion utilities and Python programs that are part of COBOL systems. Really.

FEVal, the Finite Element Evaluator written in Python, provides easy conversion for many Finite Element data formats (both binary and ascii). Mesh modification is very easy. Values of model results can be accessed given coordinates in physical space.

Tool for annotating (bike race) videos with data from GPS devices to display time, distance, speed, power, HR, CAD, elevation, laps. Outputs a series of SVG files importable as image sequence into the OpenShot Video editor as overplayed video track.

GTO is a file format whose primary usage is storage of static geometric data, though it can be used to store just about anything.

InkPlot is an extension (plugin) for the SVG Editor Inkscape to insert graphs from Gnuplot. It allows you to - preview the graph - add it as SVG into Inkscape - edit already generated graphs - use a preamble file for reusable style and commands - customize default settings in a config file

A pure python canvas for drawing 2D primitives which outputs its data as SVG or VML but can be easily extended to output more formats.

QuickDicom is an easy to use dicom medical imaging package for Mac OSX, providing QuickLook, Spotlight, Quartz Composer, Window/Level and a dicom file analyzer. Also included is the iiDicom Framework for image/dictionary usage in Objective C and Python.

SnapLogic is an Open Source Data Integration framework that combines the power of state-of-the-art dynamic programming languages with standard Web interfaces to solve today's most pressing problems in data integration.

This is a collection of Python functions, with which data can be exported from the Python environment to a file which can be viewed in GoogleEarth.

Geo-Spatial Data Viewer (GSDView) is a lightweight viewer for geo-spatial data and products. It is written in python and Qt4 and uses the GDAL library. GSDView is modular and has a simple plug-in architecture.

L(atex)equation aims to be the simplest latex to bitmap converter there is. Its goals are: simple gui, simple install, mac + windows + ubuntu binaries and it just should work.

A tool for autonomous and virtual topical data integration using the focused web-harvesting method.

xyz2eps.py is an command line utility written in Python programing language which prints the geometry from xyz-file directly to the eps-file format. Originally it was designed to study the problems related to grain boundaries in graphene.

An Inkscape extension for editable (digital) timing diagrams in publication quality, based on a very simple state-oriented language for signal description.