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The increasing availability of textual corpora and data fetched from socialnetworks is fuelling a huge production of works based on the model proposed bypsychologist Robert Plutchik, often referred simply as the ``Plutchik Wheel''.Related researches range from annotation tasks description to emotionsdetection tools. Visualisation of such emotions is traditionally carried outusing the most popular layouts, as bar plots or tables, which are howeversub-optimal. The classic representation of the Plutchik's wheel follows theprinciples of proximity and opposition between pairs of emotions: spatialproximity in this model is also a semantic proximity, as adjacent emotionselicit a complex emotion (a primary dyad) when triggered together; spatialopposition is a semantic opposition as well, as positive emotions are oppositeto negative emotions. The most common layouts fail to preserve both features,not to mention the need of visually allowing comparisons between differentcorpora in a blink of an eye, that is hard with basic design solutions. Weintroduce PyPlutchik, a Python library specifically designed for thevisualisation of Plutchik's emotions in texts or in corpora. PyPlutchik drawsthe Plutchik's flower with each emotion petal sized after how much that emotionis detected or annotated in the corpus, also representing three degrees ofintensity for each of them. Notably, PyPlutchik allows users to display alsoprimary, secondary, tertiary and opposite dyads in a compact, intuitive way. Wesubstantiate our claim that PyPlutchik outperforms other classic visualisationswhen displaying Plutchik emotions and we showcase a few examples that displayour library's most compelling features.

PyPlutchik: visualising and comparing emotion-annotated corpora