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PHP and PDO: How to group data and aggregate calculations

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2023-07-28 16:36:251298browse

PHP and PDO: How to perform data grouping and aggregation calculations

Introduction:
When developing web applications, we often encounter situations where we need to group and aggregate data in the database. It is a common practice in PHP to use the PDO (PHP Data Objects) extension to connect and operate databases. This article will introduce how to use PDO for data grouping and aggregation calculations, and provide corresponding code examples.

  1. Connect to the database
    First, we need to use PDO to connect to the database. The following is a sample code snippet that demonstrates how to use PDO to connect to a MySQL database:
$dsn = 'mysql:host=localhost;dbname=mydatabase;';
$user = 'username';
$password = 'password';

try {
    $pdo = new PDO($dsn, $user, $password);
    $pdo->setAttribute(PDO::ATTR_ERRMODE, PDO::ERRMODE_EXCEPTION);
    echo "成功连接到数据库!";
} catch (PDOException $e) {
    echo "连接数据库失败:" . $e->getMessage();
}

In the above code, we first define the host address, database name, username and password required to connect to the database. Then, use the PDO constructor to create a PDO object and set the error mode to ERRMODE_EXCEPTION so that an exception is thrown when an error occurs. Finally, we print a message that the connection to the database was successful, or a failure message if the connection failed.

  1. Data grouping
    Next, we will introduce how to use PDO for data grouping operations. Let's say we have a student table that contains students' names and the classes they belong to. We want to group students by classes and count the number of students in each class. The following is a sample code snippet that demonstrates how to use PDO for data grouping:
$sql = "SELECT class, COUNT(*) as student_count FROM students GROUP BY class";

try {
    $stmt = $pdo->prepare($sql);
    $stmt->execute();

    $result = $stmt->fetchAll(PDO::FETCH_ASSOC);

    foreach ($result as $row) {
        echo "班级:" . $row['class'] . ",学生人数:" . $row['student_count'] . "<br>";
    }
} catch (PDOException $e) {
    echo "查询数据失败:" . $e->getMessage();
}

In the above code, we use PDO's prepared statement prepare() method to prepare the query statement. Then, use the execute() method to execute the query and the fetchAll() method to fetch all result rows. Next, we iterate through the result set and output each class and its corresponding number of students.

  1. Aggregation calculation
    In addition to data grouping, we often need to perform aggregate calculations, such as calculating the sum, average, maximum or minimum value of a column, etc. The following is a sample code snippet that demonstrates how to use PDO for aggregate calculations:
$sql = "SELECT COUNT(*) as student_count, AVG(score) as avg_score, MAX(score) as max_score, MIN(score) as min_score FROM students";

try {
    $stmt = $pdo->prepare($sql);
    $stmt->execute();

    $result = $stmt->fetch(PDO::FETCH_ASSOC);

    echo "学生总数:" . $result['student_count'] . "<br>";
    echo "平均分数:" . $result['avg_score'] . "<br>";
    echo "最高分数:" . $result['max_score'] . "<br>";
    echo "最低分数:" . $result['min_score'] . "<br>";
} catch (PDOException $e) {
    echo "查询数据失败:" . $e->getMessage();
}

In the above code, we use the same process to prepare the query statement and execute the query. However, this time we use the fetch() method to get a single row of results and store the results in an associative array. Then, we output the total number of students, the average score, the highest score, and the lowest score.

Conclusion:
In this article, we learned how to use PDO to connect to the database, and use PDO to perform data grouping and aggregation calculation operations. Through the reasonable use of PDO and SQL statements, we can easily process data in the database and perform various data operations flexibly. I hope the content of this article can help readers better understand and apply the related functions of PDO.

The above is an article about how PHP and PDO perform data grouping and aggregation calculations. I hope it will be helpful to you.

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