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Part of the book series: Palgrave Studies in Risk and Insurance ((PSRIIN))

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Abstract

This chapter provides an overview of the relevant content of data visualization, comprehensively introduces its basic knowledge, and common tools to use, and gives a related case for a complete visualization process; this chapter elaborates on the applications of (i) data visualization, (ii) introduction to Python visualization tools, (iii) data distribution chart, and (iv) financial data case analysis.

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References

  • Cao, S., Zeng, Y., Yang, S., and Cao, S. (2021). “Research on Python Data Visualization Technology.” Journal of Physics: Conference Series, 1757(1), 012122). IOP Publishing.

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  • Marghescu, D. (2007). “Multidimensional Data Visualization Techniques for Financial Performance Data: A Review.” TUCS Technical Report, 810.

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  • Zhang, Y., Hou, S. H. U., Liu, H., Wang, S., and Zhang, X. (2020). “Research on Application of Data Visualization in Finance.” DEStech Transactions on Engineering and Technology Research (acaai).

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Correspondence to Qingquan Tony Zhang .

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Zhang, Q.T., Li, B., Xie, D. (2022). Data Visualization. In: Alternative Data and Artificial Intelligence Techniques. Palgrave Studies in Risk and Insurance. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-031-11612-4_14

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  • DOI: https://doi.org/10.1007/978-3-031-11612-4_14

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  • Publisher Name: Palgrave Macmillan, Cham

  • Print ISBN: 978-3-031-11611-7

  • Online ISBN: 978-3-031-11612-4

  • eBook Packages: Economics and FinanceEconomics and Finance (R0)

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