The dataset contains personal information such as Record ID, First Name, Last Name, Full Name, Street, City, State, and Zip. To determine the number of clusters in this dataset, we need to perform clustering analysis.

Since the dataset contains categorical data, we can use clustering algorithms like K-Means after encoding the categorical variables. Let's proceed with the clustering analysis.

The elbow method graph has been displayed. The optimal number of clusters is typically at the point where the graph starts to bend, which is known as the 'elbow'.

From the graph, you can determine the optimal number of clusters for your dataset.

It seems there was an issue loading the spaCy model even after attempting to download it. This might require a restart of the Python kernel to properly load the dependencies.

It seems there was an issue loading the spaCy model even after attempting to download it. This might require a restart of the Python kernel to properly load the dependencies.