Identifying and Printing Negative Values in a DataFrame Using Nested Loops

### Problem Statement:

You have a DataFrame with several columns, each containing a mix of positive and negative values. The task is to loop through every element in the DataFrame and identify any negative values. When a negative value is found, it should be printed out along with a message indicating that a negative value was found.

1. **DataFrame Setup**:

   - The DataFrame consists of multiple columns (`A`, `B`, `C`), each with both positive and negative integer values. The goal is to systematically inspect each value in the DataFrame to check if it is negative.

2. **Looping Through Columns**:

   - The solution starts by looping through each column in the DataFrame. This is done by iterating over the column names.

3. **Looping Through Values in Each Column**:

   - For each column, the solution further loops through every value within that column. This nested loop allows the solution to access each individual element in the DataFrame.

4. **Checking for Negative Values**:

   - Inside the inner loop, each value is checked to see if it is less than zero (i.e., negative). 

5. **Printing Negative Values**:

   - If a value is found to be negative, a message is printed that includes the negative value. This provides immediate feedback on which negative values exist in the DataFrame.

### Summary:

This approach methodically examines each element in the DataFrame to identify negative values. It uses a nested loop structure—first looping through each column and then through each value within that column—to ensure every element is checked. When a negative value is found, it is reported through a print statement, making it easy to track which values are negative. This method is useful for tasks where you need to inspect and act on specific types of values, such as negative numbers, within a dataset.