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Visualisations of data are at the core of every publication of scientific research results. They have to be as clear as possible to facilitate the communication of research. As data can have different formats and shapes, the visualisations often have to be adapted to reflect the data as well as possible. We developed Pylustrator, an interface to directly edit python generated matplotlibgraphs to finalize them for publication. Therefore, subplots can be resized and dragged around by the mouse, text and annotations can be added. The changes can be saved to the initial plot file as python code.
python, visualisation, matplotlib
python, visualisation, matplotlib
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 5 |

Views provided by UsageCounts