Slip 22

1

<?php

$queue = array();

while (true) {

    echo "\n====== Queue Operations ======\n";

    echo "1. Insert an element in Queue\n";

    echo "2. Delete an element from Queue\n";

    echo "3. Display Queue\n";

    echo "4. Exit\n";

    echo "Enter your choice: ";

    $choice = trim(fgets(STDIN));

    switch ($choice) {

        case 1:

            echo "Enter element to insert: ";

            $element = trim(fgets(STDIN));

            array_push($queue, $element);

            echo "Inserted: $element\n";

            break;

        case 2:

            if (empty($queue)) {

                echo "Queue is empty. Cannot delete.\n";

            } else {

                $deleted = array_shift($queue);

                echo "Deleted element: $deleted\n";

            }

            break;

        case 3:

            if (empty($queue)) {

                echo "Queue is empty.\n";

            } else {

                echo "Queue contents: ";

                foreach ($queue as $item) {

                    echo $item . " ";

                }

                echo "\n";

            }

            break;

        case 4:

            echo "Exiting program...\n";

            exit(0);

        default:

            echo "Invalid choice. Try again.\n";

    }

}

?>

2 

import pandas as pd

from sklearn import preprocessing

data = pd.read_csv('winequality-red.csv')

df = pd.DataFrame(data)

ffrom sklearn.preprocessing import MinMaxScaler

scaler = MinMaxScaler()

scaled = scaler.fit_transform(df)

print(scaled)

standard = preprocessing.scale(df)

print("\n*** Standardized Data ***\n", standard)

normalized = preprocessing.normalize(df)

print("\n*** Normalized Data ***\n", normalized)