How can I write a php code that only fetches data selected by a dropdown menu? (example: If I select "Student 1" from the dropdown menu, it needs to open a different page displaying all the details of Student 1.

Suppose that a mattress store has a TABLE1 with sales representatives with an attribute vcode as primary key. It also has a TABLE2 with every mattress sold, the table has an attribute vcode to indicate which sales representative made the sale, and a mt_code to indicate which mattress was sold. Which of the following returns all the sales representatives that haven't closed a sale?   a. SELECT * FROM TABLE1 LEFT JOIN TABLE2 ON TABLE1.vcode = TABLE2.vcode WHERE mt_code IS NULL.   b. SELECT * FROM TABLE1 JOIN TABLE2 ON TABLE1.vcode = TABLE2.vcode WHERE mt_code IS NULL.   c. SELECT * FROM TABLE1 RIGHT JOIN TABLE2 ON TABLE1.vcode = TABLE2.vcode WHERE mt_code IS NULL.   d. SELECT * FROM TABLE1 RIGHT JOIN TABLE2 ON TABLE1.vcode = TABLE2.vcode WHERE mt_code IS NOT NULL.

. Load the data into a pandas dataframe named data_firstname_df2 where first name is you name.2. Replace the ‘?’ mark in the ‘bare’ column by np.nan and change the type to ‘float’3. Drop the ID column4. Separate the features from the class.5. Split your data into train 80% train and 20% test use the last two digits of your student number for the seed. 6. Using the preprocessing library to define two transformer objects to transform your training data:a. Fill the missing values with the median (hint: checkout SimpleImputer)b. Scale the data (hint: checkout StandardScaler)7. Combine the two transformers into a pipeline name it num_pipe_firstname.8. Create a new Pipeline that has two steps the first is the num_pipe_firstname and the second is an SVM classifier with random state = last two digits of your student number. Name the pipelinepipe_svm_firstname. (make note of the labels)9. Take a screenshot showing your num_pipe_firstname object and add it to your written report.10. Define the…

The acclaimed _NumPy_ library, that `Simpy` is inspired by, allows you to use the subscription operator not just to select individual items, but also to filter with a mask. It adds a second usage to the operator, just like you have had two uses of many of the operators above, such as adding two `Simpy`s or a `Simpy` and a `float`. The big idea of the second usage of subscription notation is that if instead of giving an `int` inside the subscription brackets you give a `list[bool]`, the expression will return a new `Simpy` object containing only the _masked_, or filtered, `values`. For example: ~~~python a = Simpy([1.0, 2.0, 3.0, 4.0, 2.0, 1.0]) mask = a > 2.0 print(mask)  # Output: [False, False, True, True, False, False] b = a[mask] print(b) # Output: Simpy([3.0, 4.0])   ~~~ The above example did not need to establish a separate variable named `mask`, it only did so to make it obvious what the `mask` values were. More conventionally, the above example would be written in a…