MySQL: Calculating totals for user-selectable year ranges - php

Question

Let me start off by stating that I'm a just a self-taught hobbyist at this, so I'm sure I'm doing some things wrong or ineffciently, so any feedback is appreciated. If this question is moot because I've made fundamental errors and need to start from scratch, I guess I need to know so I'll become better.
With that, here's the problem:
I have a database of birth names in MySQL that is intended to let you find the frequency of those names within a given year range. My only table has a lot of columns:
**Name** **Begins** **Popularity** **1800** **1801** **1802**
Aaron A 500 6 7 4
Amy A 100 10 2 12
Ashley A 250 2 5 7
...and so forth until 2013.
Right now I've written a PHP page that can call up a list of names based on the start letter over the entire year range (1800-2013). That works, but what I'd like to do is to let the user specify a custom year range from the dropdowns I put on the home page and use that to calculate the frequency of each name for the custom year range only. I'd also like to be able to sort the resulting list based on those frequency values, not the all-time frequency stored in 'Popularity'.
From what I've looked at, I'm thinking part of the solution might lie in using custom views but I just can't seem to put the pieces all together. Or should I somehow pre-calculate all possible combinations?
Here's is the working query code I'm using right now:
{$query = "SELECT Name
FROM nametable
WHERE Gender = '$genselect'
AND
(BeginsWith = '$begins')
ORDER BY $sortcolumn $sortorder";
goto resultspage;
}
resultspage:
$result = mysqli_query($dbcnx, $query)
or die ("Error in query: $query.".mysqli_error($dbcnx));
$rows = $result->num_rows;
echo "<br>You found $rows names!<br>";
while($row=mysqli_fetch_assoc($result))
{
echo '<br>'.$row['Name'];
}

Answer 1

I think you're going to have to consider structuring your data in a different way to make the most of using an RDBMS.
If it were me, I'd be looking at normalising data into different tables in the first instance and disposing of unnecessary fields such as "Begins" and "Popularity". That kind of information can easily be reproduced or sought out in PHP or within a query itself. The advantage here is that you also reduce the number of columns that actually need to be maintained.
I haven't worked out a silver bullet schema but, roughly, I'd start with something along these lines and expand/modify where appropriate:
Names
- id
- name
- genderID
Genders
- id
- code
Years
- id
Frequencies
- id
- nameID
- yearID
- number
So, for example, a segment of your data may take the following shape:
Names (1, Aaron, 1)
Genders (1, Male)
Years (1987)
Frequencies (1, 1, 1987, 6), (1, 1, 1988, 19)
The beauty of having your data separated out like this is that it becomes much easier to query it. So, if you wanted the frequency of occurrences of the name Aaron between 1987 and 1988 you could do something like the following:
SELECT SUM(frequencies.number) FROM frequencies WHERE frequencies.yearID
BETWEEN 1987 AND 1988
AND frequencies.nameID = 1
Furthermore, doing away with the "Begins" column would mean you can structure a query to use "LIKE"
SELECT * FROM names WHERE name LIKE "A%"
My examples are perhaps a bit contrived but hopefully they illustrate what I'm getting at.
One thing I haven't touched upon is how you might go about physically entering the data. What happens when a new name is added? Does a corresponding entry get made in the frequencies table automatically? Is a check performed in the frequencies table first and, if an entry exists, does it automatically increment the number?
These are important problems to consider but probably best left until after a schema is settled upon.