To conduct an analysis on weather data collected by several stations for a future business owner looking to run a surf shop from Oahu.
The purpose of this analysis is to compare the weather data from June and December to determine if running a surf shop is sustainable year-round. We ran the queries separately and turned the results into a data frame which we will discuss below, we also gathered the statistics through the function .describe() to better understand and compare the data for the two months.
-
After conducting the analysis, we gather the following statistics for the months of June and December.
- June had a min of 64.00, max of 85.0 and a mean of 74.9.
-December had a min of 56.00, max of 83.0 and a mean of 71.0.
-
The difference in the standard deviation between June and December was only 0.49 since the standard deviation for June is "3.25" and "3.74" in December, showing there is not a significant difference in the two months.
Overall, running a surf shop from Oahu seems like a profitable business as the weather during the winter is not too cold. Since there are only two seasons in Hawaii, fall and winter, it would be insightful to run a query on precipitation data as this can severely influence conditions for surfing. Depending on how much data is collected by the stations we could also run a query on areas of the island that have better tides or are located closer to tourist spots that can guarantee more customers and revenue for the business.
Data Source: hawaii.sqlite
Software: Python 3.6.1, Visual Studio Code, 1.38.1, Jupyter Notebook, SQLite