Agglomerative Clustering Algorithm

1. Read Data:

   Read the input data points from the standard input (stdin).

2. Preprocess Data:

   Parse the input data points and store them in a list.

3. Initialize Clusters:

   Initialize the clusters using the first n data points.

4. Define Euclidean Distance Function:

   Define a function to calculate the Euclidean distance between data points.

5. Main Loop:

   Iterate until the number of clusters reaches the desired value (k).

6. Update Clusters:

   Calculate the pairwise distances between clusters and merge the two closest clusters.