For the code (from the chapter on Cluster Analysis ML) shown…

Fоr the cоde (frоm the chаpter on Cluster Anаlysis ML) shown below, there will be а number of questions presented. Please refer to this code for those questions. def createCentroids(d, dataDict):    centroids=[]    centroidCount = 0    centroidKeys = []              while centroidCount < d:       rKey = random.randint(1, len(dataDict))       if rKey not in centroidKeys:               centroids.append(dataDict[rKey])             centroidKeys.append(rKey)  #add key to selected keys           centroidCount = centroidCount + 1     return centroids def createClusters(d, centroids, dataDict, repeats):    for aPass in range(repeats):        print("****PASS", aPass + 1, "****")        clusters = []                    for i in range(d):           clusters.append([])         for aKey in dataDict:              distances = []           for clusterIndex in range(d):                dtoC = euclidD(dataDict[aKey], centroids[clusterIndex])                #dtoC = math.dist( tuple(dataDict[aKey]), tuple(centroids[clusterIndex]))                distances.append(dtoC)            minDist = min(distances)              index = distances.index(minDist)            clusters[index].append(aKey)           dimensions = len(dataDict[1])           for clusterIndex in range(d):           sums = [0] * dimensions                 for aKey in clusters[clusterIndex]:               dataPoints = dataDict[aKey]               for ind in range(len(dataPoints)):                     sums[ind] = sums[ind] + dataPoints[ind]           for ind in range(len(sums)):                  clusterLen = len(clusters[clusterIndex])               if clusterLen != 0:                          sums[ind] = sums[ind] / clusterLen            centroids[clusterIndex] = sums           for c in clusters:                print("CLUSTER")           for key in c:               print(dataDict[key], end = " ")           print()     return clusters In the createClusters function, What is the first inner loop doing