Investing in a new business venture can be risky, but it can be extremely rewarding if the investment pays off. An investor is considering backing a business plan, which involves opening ‘Waves and Ice Cream’, a shop which would serve surf boards and ice cream to locals and tourist in Oahu, Hawaii. The purpose of this analysis is to conduct an analysis on a weather dataset from Oahu, Hawaii to determine whether opening this business would be a viable option.
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Data Sources: hawaii.sqlite
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Languages: Python
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Applications: SQLite, SQLAlchemy
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Tools: Pandas, Jupyter Notebook
In conducting this analysis, it was important to sample data from different months of the year, to determine if there were vast variations in the results. Specifically, temperature data was sampled for the months of June and December in Oahu, Hawaii, to determine if the surf and ice cream shop business would be sustainable year-round.
By utilizing Python, Pandas functions and methods, and SQLAlchemy, the date column was filtered from the Measurements table in the hawaii.sqlite database in order to retrieve all the temperatures for the month of June and December. Once this data was obtained, the temperatures were initially converted to a list, then a DataFrame was created from the list, and finally summary statistics were generated.
A total of 9 weather stations captured data. For the months of June and December, various statistics were captured pertaining to the temperature.
The results indicate key differences in weather between June and December.
- There are more data points capturing temperature in June versus December.
- The lowest temperature is marked with an 8-degree difference (June: 64F, December: 56F), but the high temperature is marked with a 2-degree difference (June: 85F, December: 83F).
- The average temperature in June is 74.9 and in December is 71.0, showing little variance.
Given Oahu, Hawaii’s geographic location, it only has two seasons, summer and winter.
A histogram was created to plot the underlying frequency distribution of the various temperature observations, throughout the year, at the most active weather station. Temperatures ranging from 75F – 77F occurred the most often. The findings are consistent with the results from above.
Although there are evident temperature variations between the seasons, it would be helpful to further examine the data to evaluate how elevation and trade winds contribute to temperature fluctuations. In addition, further analysis can be done on tropical storm patterns. An initial look at precipitation patterns can be seen below.
This further analysis is necessary to determine whether “Waves and Ice Cream” should be open year-round.