Which Countries Export...? Developing an Algorithm

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Do curso por Duke University

Java Programming: Solving Problems with Software

2628 classificações

Duke University

Java Programming: Solving Problems with Software

2628 classificações

Curso 1 de 4 em Specialization Object Oriented Programming in Java

Building upon Duke’s “Programming and the Web for Beginners” course, you will grow in your ability to be a problem-solver and programmer by writing Java programs. We are excited that you've chosen to learn Java with us! You will soon be able to solve problems that you find interesting and useful by practicing a design process you will learn in this course. Java concepts presented in this course include basic control flow; object-oriented concepts including classes and methods; custom, open-source classes; and a design-implement-debug process that you can continue to leverage as you build your experience and knowledge of programming principles. The custom, open-source classes will provide a consistent application programming interface (API) so that you can write programs that access and transform images, websites, comma separated value (CSV) files and other data files using simple and accessible coding idioms built on the Java Iterable interface. You will learn to design, test, and debug programs and to find and read Java documentation that can serve as the basis for continued study of Java and programming. After completing this course you will be able to: 1. Edit, compile, and run a Java program; 2. Use conditionals and for loops appropriately in a Java program; 3. Use Java API documentation in writing programs. 4. Debug a Java program using the scientific method; 5. Develop 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 more than one method.

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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).

CSV Data: Comma Separated Values2:47

Using CSV Libraries7:11

Which Countries Export...? Developing an Algorithm4:14

Which Countries Export...? Translating into Code5:28

CSVExport: Summary0:48

Conheça os instrutores

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

Welcome back.

Now that you know a little bit about the basics of working with CSV files,

it is time for you to solve a problem using them.

Here, we have a CSV file, which shows export data for 218 countries.

The columns are the country name, the main export, and

the total value of their exports in 2014 in US dollars.

A problem you might want to solve with this data,

is to find which countries export a particular item.

For example, you might want to print all of the countries which export lobsters, or

all of the countries which export iron.

There's a lot of data in this file, way too much to look at by hand,

which would be tedious and error prone.

Instead, you would rather write a program to perform this analysis for you.

As always,

we will walk through how you write such a program using the seven steps.

Step one is to work a small instance of the problem by hand.

Here, we've cut the table down to four countries and

only listed a few exports for each of them.

Which of these countries exports coffee?

After looking at the table for a few seconds, you can see that Madagascar and

Malawi export coffee, and Macedonia and Malaysia do not.

Next, you need to write down what you just did.

If you just say, I just looked at it and saw the answer, that will not help for

step three.

Instead, you need to think through what you did in a more step-by-step fashion.

How did you look at the table and see the answer?

You probably looked at the first row's exports column and

saw that it did not contain coffee.

Next, you looked at the second row's export column and

saw that it contains coffee.

So, you wrote down Madagascar.

Next, you looked at the third row's export column and

saw that it also contains coffee, so you wrote down Malawi.

Finally, you looked at the forth row's exports column, and

saw that it did not contain coffee.

Thinking through this in a step-by-step fashion leads to these ten steps for

this particular instance of a problem.

Now, we're ready to look for patterns and generalize.

Notice how you are doing very similar things for each row.

This similarity suggests you will eventually want to loop over each row.

However, there are some differences in the steps for each row that you need to

think through before you can express this algorithm in terms of for each row.

The first difference you might notice is that on line five you wrote down

Madagascar, and on line eight, you wrote down Malawi.

Where did these particular words come from?

They are the value of the country column for the row you are looking at.

The next difference you might notice, is that you do not write down the country for

the first and fourth rows, but you do for the second and third.

How did you know whether to write the country down or not?

You made this choice based on whether or

not the row contained coffee in the Exports column.

Now that you have figured out how to operate on each row in the same way,

you can write down the generalized steps in terms of for

each row in the CSV file, generalizing over how many rows the file has.

Now that you have a general algorithm to solve this problem,

it is time to test it out.

Here is a table of data which contains two countries.

Use the algorithm to find out which ones export lobster.

Is this algorithm correct?

According to our algorithm, Brazil is the country which exports lobster.

Oops, that's not correct.

We should have gotten Angola.

Did you test the algorithm carefully enough to notice this mistake?

The problem is that our algorithm always checks for coffee, not for

whatever expert we are interested in.

We should have thought this through as we generalized, but we missed doing that.

This is exactly the sort of problem step four,

testing your algorithm is intended to catch before you write code.

You can fix this algorithm by referring to the parameter, we'll call it

exportative interest, which indicates which export you want to look for.

Making this correction to the algorithm will have it yield the right answer on

this test case.

Now that you have an algorithm, it's time to write the code.

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