Maximum Temperature: Testing Code

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En provenance du cours de Duke University

Java Programming: Solving Problems with Software

2567 notes

Duke University

Java Programming: Solving Problems with Software

2567 notes

Cours 1 sur 4 dans Specialization Object Oriented Programming in Java

Learn to code in Java and improve your programming and problem-solving skills. You will learn to design algorithms as well as develop and debug programs. Using custom open-source classes, you will write programs that access and transform images, websites, and other types of data. At the end of the course you will build a program that determines the popularity of different baby names in the US over time by analyzing comma separated value (CSV) files. After completing this course you will be able to: 1. Edit, compile, and run a Java program; 2. Use conditionals and loops in a Java program; 3. Use Java API documentation in writing programs. 4. Debug a Java program using the scientific method; 5. Write a Java method to solve a specific problem; 6. Develop a set of test cases as part of developing a program; 7. Create a class with multiple methods that work together to solve a problem; and 8. Use divide-and-conquer design techniques for a program that uses multiple methods.

À partir de la leçon

CSV Files and Basic Statistics in Java

A common format for storing tabular data (any data organized into columns and rows) is in comma separated values (CSV) files. In this module, you will learn how to analyze and manipulate data from multiple CSV data files using a powerful open-source software package: Apache Commons CSV. Using this library will empower you to solve problems that could prove too complex to solve with a spreadsheet. By the end of this module, you will be able to: (1) Use the open-source Apache Commons CSV package in your own Java programs; (2) Access data from one or many CSV files using Java; (3) Convert strings into numbers; (4) Understand how to use “null” in Java programs (when you want to represent “nothing”); (5) Devise an algorithm (and implement in Java) to answer questions about CSV data; and (6) Analyze CSV data across multiple CSV files (for example, find maximums, minimums, averages, and other simple statistical results).

Hottest Day in a Year: Comma Separated Values2:29

Converting Strings to Numbers4:27

Maximum Temperature: Developing an Algorithm5:13

Java for Nothing—null: When You Don't Have an Object4:17

Maximum Temperature: Translating into Code4:42

Maximum Temperature: Testing Code3:33

Maximum Temperature from Multiple Datasets5:51

Maximum Temperature Refactored4:07

CSVMax: Summary0:41

Rencontrer les enseignants

Owen Astrachan
Professor of the Practice
Computer Science
Robert Duvall
Lecturer
Computer Science
Andrew D. Hilton
Associate Professor of the Practice
Electrical and Computer Engineering
Susan H. Rodger
Professor of the Practice
Computer Science

Let's take a quick at how the data is organized on the file system and

what an actual file looks like.

So we have a data folder and inside of that data folder it's organized into years

and then within each year we have, a weather file for each day.

So there's 365 or 6, depending on if it's leap year,

of those files for each of the years.

So that's how it looks on the file system.

And then here's how an individual file looks, so in this case I've chosen January

1st, 2015 as the one that I'm gonna test that, the file I'm gonna test.

And you can see we've got the column information up top and

we've got the column data for each of those.

We have two files loaded up in a spreadsheet

because CSV files are easily represented as spreadsheets.

So this is a nice way to visualize them.

The other method that I've already included in the CSV Max class,

is testHottestInDay, so we can test our code to make sure that it's right.

First line in there creates a file resource already set to January 1st, 2015.

The second line calls our hottest hour on file method that we just wrote,

passing it the parser that we created for that particular data set.

And then that returns us the CSV record that is the largest one.

And then we print out that hottest temperature and

the time that it appeared at just to see when that was, and

that's gonna give us a sense of whether or not a program is correct.

So, I'm gonna compile our code, and I'm gonna come over

to the BlueJ environment and create a new CSVMax object.

And then call my test hottest day.

And it says the hottest temperature was 51.1 at 2:51 PM.

And if I go over to my data file, and I look at the temperatures,

I see that they are in the 20s and the 30s, 50, 51.1,

back down the 50, back to the 40s, and 42.1.

So, indeed, the hottest temperature was 51.1 occurring at 2:51 PM.

Let's also check the 2nd of January

just to try it on a second data file to see how we're doing.

So I'm going to come over and change that from January 1st to January 2nd.

I'm going to recompile.

I'm going to go ahead and create a new CSVMax, and call test hottest day.

This time it thinks it was 54 at 12:51 PM.

And again, if I come over and I look at my temperature.

I'm in the 40s.

I'm now in the 50s, 51.1.

I have 54s and then back down to the 40s.

You'll notice that there was actually 4 times when it

was recorded as being 54 degrees.

And we've recorded the first time that that occurred,

12:51 PM, as opposed to the last time that that occurred, 3:51 PM.

So now that I've tested it on

two separate files, and I've seen that it worked for those.

I feel reasonably confident that my code is correct, but I encourage you to

test it on more files, and try it out on your own and see what you get.

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