code: def make_table(cluster_ranges, clfs, times):
      columns = ["cluster_ranges", "errors", "clustering_time"]
  
      data = list(zip(cluster_ranges, clfs, times))
  
      table = wandb.Table(columns=columns, data=data)
  
      return table
  
file_path: wandb/wandb/sklearn/calculate/elbow_curve.py
imports: import time
  from warnings import simplefilter
  import numpy
  from joblib import Parallel, delayed
  from sklearn.base import clone
  import wandb
label_desc: Use image node_id 2 for calling a global function with example usage: make_table(cluster_ranges, clfs, times) and returns: table