Join Carlos Rivas for an in-depth discussion in this video Solution Overview, part of Code Clinic: Java.
- [Instructor] The dataset consists of several data points such as air temperature, barometric pressure, and others, captured thousands of times and stored in tab-separated text files in this format. To perform the desired calculation, we'll use the following formula. For our X axis, we'll use our time series, and the barometric pressure will be our Y axis. The XY pair labeled as one will represent our oldest data point and the ones labeled as two will represent our most recent data point measurement.
The result will be our slope coefficient. Based on the values of the slope, we can conclude the following. A slope equal to zero means that there is no significant change in the trend. A positive slope indicates an upward trending barometric pressure, and finally, a negative value will tell us that the pressure is trending down. My solution consists of three methods and a supporting class. A read data method that collects all the information from the provided comma-separated files and loads them into an array in memory.
A perform calculation method that filters the data based on a specified date range, as required by the co clinic, and calculates the desired result. Also, the main method that manages the loading of the provided data files calls the require methods, performs several tests, and outputs the result. Also, the main method that manages the loading of the provided data files calls the require methods, performs several tests, and outputs the result.
Before we go into the details of each method, let's take a look at the output of the program. Let's run it right now and see what the output looks like. Let's go over to the console and run the application. We execute our program. We get our three test cases printed, and the number of records that were loaded. Each test case is going to show us a date range, the calculated slope, and a meaningful assessment based on the value of the slope, which is our weather forecast.
Visit other courses in the series to see how to solve the exact same challenges in languages like C#, C++, PHP, Python, and Ruby.