Time Series Visualization in Python
Keywords:
python, graphing
Abstract
It is shown how to use the Python programming language
in order to get graphical representations of time series. Furthermore,
Python is used to study the concept of the visibility graph
of a time series. The examples shown here could be useful in contexts where programming may be applied in scientific problems.
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References
Bezsudnov, I. V., Snarskii, A. A., 2014. From the time series to the complex
networks: the parametric natural visibility graph. Phys. A 414, 53–60.
URL http://dx.doi.org/10.1016/j.physa.2014.07.002
Brockwell, P. J., Davis, R. A., 2016. Introduction to time series and forecasting,
3rd Edition. Springer Texts in Statistics. Springer, [Cham].
URL http://dx.doi.org/10.1007/978-3-319-29854-2
Devaney, R. L., 1989. An introduction to chaotic dynamical systems, 2nd Edition.
Addison-Wesley Studies in Nonlinearity. Addison-Wesley Publishing
Company, Advanced Book Program, Redwood City, CA.
Gutin, G., Mansour, T., Severini, S., 2011. A characterization of horizontal visibility
graphs and combinatorics on words. Phys. A 390 (12), 2421–2428.
URL http://dx.doi.org/10.1016/j.physa.2011.02.031
Harary, F., 1969. Graph theory. Addison-Wesley Publishing Co., Reading,
Mass.-Menlo Park, Calif.-London.
Lacasa, L., Luque, B., Ballesteros, F., Luque, J., Nuño, J. C., 2008. From time
series to complex networks: the visibility graph. Proc. Natl. Acad. Sci. USA
105 (13), 4972–4975.
URL http://dx.doi.org/10.1073/pnas.0709247105
Langtangen, H. P., 2016. A primer on scientific programming with Python, 5th
Edition. Vol. 6 of Texts in Computational Science and Engineering. Springer,
Heidelberg, for the fourth edition see [ MR3237666].
URL http://dx.doi.org/10.1007/978-3-662-49887-3
Luque, B., Lacasa, L., Ballesteros, F., Luque, J., 2009. Horizontal visibility
graphs: Exact results from random time series. Physical Review E 80.
Supriya, S., Siuly, S., Wang, H., Cao, J., Zhang, Y., 2016. Weighted visibility
graph with complex network features in the detection of epilepsy. IEEE Access
4, 6554 – 6566.
networks: the parametric natural visibility graph. Phys. A 414, 53–60.
URL http://dx.doi.org/10.1016/j.physa.2014.07.002
Brockwell, P. J., Davis, R. A., 2016. Introduction to time series and forecasting,
3rd Edition. Springer Texts in Statistics. Springer, [Cham].
URL http://dx.doi.org/10.1007/978-3-319-29854-2
Devaney, R. L., 1989. An introduction to chaotic dynamical systems, 2nd Edition.
Addison-Wesley Studies in Nonlinearity. Addison-Wesley Publishing
Company, Advanced Book Program, Redwood City, CA.
Gutin, G., Mansour, T., Severini, S., 2011. A characterization of horizontal visibility
graphs and combinatorics on words. Phys. A 390 (12), 2421–2428.
URL http://dx.doi.org/10.1016/j.physa.2011.02.031
Harary, F., 1969. Graph theory. Addison-Wesley Publishing Co., Reading,
Mass.-Menlo Park, Calif.-London.
Lacasa, L., Luque, B., Ballesteros, F., Luque, J., Nuño, J. C., 2008. From time
series to complex networks: the visibility graph. Proc. Natl. Acad. Sci. USA
105 (13), 4972–4975.
URL http://dx.doi.org/10.1073/pnas.0709247105
Langtangen, H. P., 2016. A primer on scientific programming with Python, 5th
Edition. Vol. 6 of Texts in Computational Science and Engineering. Springer,
Heidelberg, for the fourth edition see [ MR3237666].
URL http://dx.doi.org/10.1007/978-3-662-49887-3
Luque, B., Lacasa, L., Ballesteros, F., Luque, J., 2009. Horizontal visibility
graphs: Exact results from random time series. Physical Review E 80.
Supriya, S., Siuly, S., Wang, H., Cao, J., Zhang, Y., 2016. Weighted visibility
graph with complex network features in the detection of epilepsy. IEEE Access
4, 6554 – 6566.
Published
2018-07-05
How to Cite
Villarroel Flores, R., Tetlalmatzi Montiel, M., & Rodríguez Torres, E. E. (2018). Time Series Visualization in Python. Pädi Boletín Científico De Ciencias Básicas E Ingenierías Del ICBI, 6(11), 5. https://doi.org/10.29057/icbi.v6i11.3021
Section
Research papers
