Elegant data visualizations via simple function calls with sensible defaults.
- Many implementations, one way of access.
- Visual representation of data sets, providing insights into structure and relationships of variables.
This package aims to simplify plotting in Python by providing:
- Sensible defaults to quickly generate publication-quality plots with minimal chartjunk.
- A configuration system supporting user-defined plot styles to reproduce figures without effort.
Decreasing the cognitive burden of data visualization may lead to the creation of more plots which can cause new insights and ideas. This can improve the overall experience in different areas of data analysis such as machine learning or data mining.
Plotting is simplified via:
- A user-friendly syntax based only on function calls.
- An intuitive set of optional arguments for tweaking all plot elements.
- A unified and consistent interface accross different plots and libraries.
Sensible default values for the optional arguments allow to quickly generate beautiful plots. They can be overwritten by the user either locally (=for a single plot by passing arguments to a function) or globally (=for all plots by modifying a central settings object).
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