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Sinusoidal Regression - Sacramento International Airport Daily Temperatures

About

A Python Jupyter Notebook showcasing 1.) pandas/numpy for data wrangling and 2.) scipy for Sinusoidal Regression of daily maximum temperatures of the Sacramento International Airport, downloaded from the National Centers for Environmental Information, National Oceanic and Atmospheric Administration (NOAA). This is a followup to a prior project using sparser water temperature data from the Yuba River.

It produces visualization of datapoints and regressions, coefficient of determination statistic, and minimum and maximum dates and temperatures during a forecasted period. Jupyter Notebook image.

Installation

Clone (for developers):

https://github.com/pjpardun/sinusoidal-regression-SMF

Requirements

  • Python (tested on version = 3.9.1)
  • pandas (tested on version = 1.3.4)
  • numpy (tested on version = 1.21.4)
  • scipy (tested on version = 1.7.2)
  • matplotlib (tested on version = 3.5.0)

License

MIT License

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