WeatherWonders

Our project seeks to explore whether there is a connection between weather conditions and student absences. By analyzing attendance records alongside weather data, we aim to determine if certain weather patterns or events are linked to changes in student’s absences. Our analysis could provide valuable insights into the impact of weather on school attendance rates, potentially informing future school policies and decision-making. For this project, we will be using data from two different sources. We will be using weather data from the National Oceanic and Atmospheric Association (NOAA) National Center for Environmental Information. It is publicly available and can be requested on their website for a specific location and date range. We will have access to daily air temperature (average, minimum, maximum), precipitation (snowfall, snow depth, multi day totals), weather type (rain, freezing rain, snow, high winds, thunder, fog, etc), and other potentially useful information. The other source of data that we will utilize is attendance data from New York City’s Department of Education provided by NYC Open Data. There are a variety of data sets available that cover different year ranges from 2006 - 2021. We plan to look at data from when students were attending school in person, prior to the shift to remote learning and then a hybrid schedule due to the COVID-19 pandemic. Each data set provides the school’s identification number, date, total enrollment, number of students present, and number of students absent. These data sets are free public data published by NYC agencies. The main question we wish to answer is how much of a correlation there is between NYC weather and absences in NYC schools. In addition, we would like to investigate whether or not rain or snow accumulation lead to an increase in absences, if there is a correlation between the daily high or low and the number of absences, and whether or not school districts in different boroughs are affected by weather relative to others