findthefunction / surfs_up

Surfs Up

Analysis

The purpose of this assignment is to determine the optimal location for a surf and icecream shop using temperature data and leveraging the power of Python, SQLAlchemy, SQLite and Flask.

Overview of the statistical analysis:

In order to compile and analyse the temperature data we created an sqlite engine and reflected the tables containing measurement and station data into a new model.

We then created a query to retrieve the temperatures from the measurement table and extract all the june data. The same steps were repeated for the December data.

Results

The key three differences between the statistical analysis performed on Decemeber and June:

• June had a larger number of temperature readings in relation to December.
• The minimum temperature was 8 degrees lower in December (56 degrees) than Junes temperature of 64 degrees.
• The mean temperatures were within 3 degrees of each other, which is favourable.

Summary

In summation, the target location for the ice cream surf shop is ideal; the limited temperature variances are generally always in a favourable range. Additional information that could be included in this analysis would be to perform precipitation queries and to analyse other weather factors such as uv index and wind speeds.