Python: Forecasting with Seasonal Autoregressive Integrated Moving Average (SARIMA) in Python/Excel

[admin]

Official Website: https://virtual-school.org/
Forums: https://virtual-school.org/forums/
SQL Server for Practice (Adventure Works Database): https://virtual-school.org/post?t=118
SQL Server for Practice (Star Corps Database): https://virtual-school.org/post?t=117
MySQL Server for Practice (Star Bakery Database): https://virtual-school.org/post?t=116

In this Python forecasting tutorial, we delve into predicting future global temperature changes using the SARIMA model, utilizing both Python and MS Excel. We start by acquiring data from NASA's global climate change website and loading it into Python using the Pandas library. After cleaning and formatting the data, we construct our SARIMA model, setting parameters such as auto-regression order and differencing order. Following model training and prediction, we encounter and resolve errors in data input. Transitioning to MS Excel, we repeat the process, demonstrating data cleansing and model application within Excel. Finally, we visualize our predictions alongside actual data on line charts, providing a comprehensive guide to forecasting temperature changes.

#PythonForecasting #SARIMAModel #ClimateChangePrediction #DataAnalysis #ExcelForecasting #DataCleansing #TemperatureTrends #PandasLibrary #ExcelDataAnalysis #DataVisualization #ForecastingTutorial #ClimateScience