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Nominal data, due to their nature, are often analysed statistically in a quite limited and traditional way. Usually they come from open-ended or simple/multiple choice questions. In typical research projects, such data are often presented in the form of more or less complex tables (including contingency tables) and standard charts. The author’s experience shows that such a visualisation is perceived as boring, especially by younger people, accustomed to the presentation of content in the form of infographics. The article presents examples of data analysis and a visualisation of the nominal data based on the results of the author’s research, including theoretical reflections on the techniques and tools used. The starting point is the raw text data from the responses to the open-ended questions subjected to analyses of the frequency of words and expressions, including its visualisation through word clouds. The next step is categorization and tabulation at the level of individual variables including the visualisation of categories, to assess the contingency between two nominal variables (or the nominal and the ordinal one), including visualising the relationships via chord diagrams and the correspondence analysis.
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