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ACIS2 Data Analysis and Graphical Generation

Project description

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xmACIS2Py

Creating xmACIS2 Summary Graphics in Python

Table Of Contents

  1. plot_temperature_summary(station, product_type)
  2. plot_precipitation_summary(station, product_type)
  3. References

plot_temperature_summary(station, product_type)

This function plots a graphic showing the Temperature Summary for a given station for a given time period.

Required Arguments:

  1. station (String) - The identifier of the ACIS2 station.
  2. product_type (String or Integer) - The type of product. 'Past 7 Days' as a string or enter 7 for the same result. A value of 'custom' or 'Custom' will result in the user entering a custom start/stop date.

Optional Arguments:

  1. start_date (String) - Default=None. Enter the start date as a string (i.e. 01-01-2025)
  2. end_date (String) - Default=None. Enter the end date as a string (i.e. 01-01-2025)

plot_precipitation_summary(station, product_type)

This function plots a graphic showing the Precipitation Summary for a given station for a given time period.

Required Arguments:

  1. station (String) - The identifier of the ACIS2 station.
  2. product_type (String or Integer) - The type of product. 'Past 7 Days' as a string or enter 7 for the same result. A value of 'custom' or 'Custom' will result in the user entering a custom start/stop date.

Optional Arguments:

  1. start_date (String) - Default=None. Enter the start date as a string (i.e. 01-01-2025)
  2. end_date (String) - Default=None. Enter the end date as a string (i.e. 01-01-2025)

References

  1. xmACIS2: https://www.rcc-acis.org/docs_webservices.html

  2. MetPy: May, R. M., Goebbert, K. H., Thielen, J. E., Leeman, J. R., Camron, M. D., Bruick, Z., Bruning, E. C., Manser, R. P., Arms, S. C., and Marsh, P. T., 2022: MetPy: A Meteorological Python Library for Data Analysis and Visualization. Bull. Amer. Meteor. Soc., 103, E2273-E2284, https://doi.org/10.1175/BAMS-D-21-0125.1.

  3. NumPy: Harris, C.R., Millman, K.J., van der Walt, S.J. et al. Array programming with NumPy. Nature 585, 357–362 (2020). DOI: 10.1038/s41586-020-2649-2. (Publisher link).

  4. Pandas: author = {The pandas development team}, title = {pandas-dev/pandas: Pandas}, publisher = {Zenodo}, version = {latest}, doi = {10.5281/zenodo.3509134}, url = {https://doi.org/10.5281/zenodo.3509134} }

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