text: import pandas as pd
  from typing import List, Mapping, Tuple
  
  
  def single_linkage(matches: pd.DataFrame,
                     min_similarity: float = 0.8) -> Tuple[Mapping[int, List[str]],
                                                           Mapping[str, int],
                                                           Mapping[str, str]]:
      """ Single linkage clustering from column 'From' to column 'To'
  
      `matches` contains three columns: *From*, *To*, and *Similarity* where
      *Similarity* is already the minimum similarity score and thus no checking
      for minimum similarity is necessary.
  
      Arguments:
          matches: contains the columns *From*, *To*, and *Similarity* used for creating groups
          min_similarity: minimum similarity between strings before they can be merged into a group
  
      Returns:
          clusters: The populated clusters
          cluster_mapping: The mapping from a string to a cluster
          cluster_name_map: The mapping from a string to the representative string
                            in its respective cluster
      """
      matches = matches.loc[matches.Similarity > min_similarity, :]
  
      cluster_mapping = {}
      cluster_id = 0
  
      for row in matches.itertuples():
  
          # If from string has not already been mapped
          if not cluster_mapping.get(row.From):
  
              # If the to string has not already been mapped
              if not cluster_mapping.get(row.To):
                  cluster_mapping[row.To] = cluster_id
                  cluster_mapping[row.From] = cluster_id
                  cluster_id += 1
  
              # If the to string has already been mapped
              else:
                  cluster_mapping[row.From] = cluster_mapping.get(row.To)
  
      # Populate the clusters
      clusters = {}
      for key, value in cluster_mapping.items():
          clusters.setdefault(value, [])
          clusters[value].append(key)
  
      cluster_name_map = {key: clusters.get(value)[0] for key, value in cluster_mapping.items()}
  
      return clusters, cluster_mapping, cluster_name_map
  