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Visualise data the easy way with sane defaults

License: GNU Affero General Public License v3.0

Python 100.00%
python python3 matplotlib data data-visualization data-visualisation sane-defaults pyplot

dataviz's Introduction

dataviz

Visualise data the easy way, with sane defaults.

Note: This package is work in (extremely slow) progress! Stage: \alpha!

This package shall at one point provide you with the right tools to do the following:

  1. Import your data from almost everywhere.
  2. Easily perform scientific calculations with uncertainties and units.
  3. Visualise your work with error bars and fits.
  4. Optimally, this package should be able to do the labelling, including units, for you.

Implementation order

Units

The unit system is a good point to start with, because it should have all of the following:

  • understanding of your input: Use the units you like (imperial, metric, with prefixes).
  • under–the–hood converter tools (do the calculations with SI units internally).
  • unit simplification: 5~\mathrm{kg}\cdot 2\frac{\mathrm{m}}{\mathrm{s}^2} should give you 10~\mathrm{N}, not 10\frac{\mathrm{kg~m}}{\mathrm{s}^2}.

Most unit system implementations have the first two properties, but they lack the last one. A good test is to combine a ton of units and see if you get more of them back than the number of base units:
1=\frac{\mathrm{JCmolSvH}}{\mathrm{Nm}^3\mathrm{s}^2~\mathrm{GyTkat~\Omega~S}}
It is rather obvious that 1 means a dimensionless quantity (amount), whereas it is not obvious that the right hand side is dimensionless.

Esoteric units in the above formula:

  • \mathrm{Gy}: Gray
  • \mathrm{S}: Siemens
  • \mathrm{Sv}: Sievert

This is (hopefully) enough to convince you that the unit simplification is one of the most important aspects of the implementation.

Measurements

A measurement is a combination of a number (int, float, uncertainties.ufloat) and a unit (Meter, Kilogram, Second). Maybe the implementation will contain an option for a prefix, so that nano is not converted to 1e-9 and then multiplied with the number but instead left unevaluated so that there is no risk of a loss of precision when multiplying / dividing numbers with prefixes.

Measurements Math

Measurements are quite useless when we cannot perform calculations with them.

dataviz's People

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dataviz's Issues

dataviz on pypi

Hi,
sorry but I did not find another way to contact you.
I have a Python project that is also named dataviz (https://gitlab.com/librecube/lib/python-dataviz), and which I would like to put on pypi.
However, the name is already reserved by your project, which however seems to be at a stale state.
Would you mind to remove your project from pypi? Of course only if you don't intend to continue your project.
Regards
Artur
[email protected]

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