code: def make_table(class_column, dataset_column, count_column):
      columns = ["class", "dataset", "count"]
      data = list(zip(class_column, dataset_column, count_column))
  
      return wandb.Table(data=data, columns=columns)
  
file_path: wandb/wandb/sklearn/calculate/class_proportions.py
imports: from warnings import simplefilter
  import numpy
  from sklearn.utils.multiclass import unique_labels
  import wandb
  from wandb.sklearn import utils
label_desc: Use image node_id 2 for calling a global function with example usage: make_table(class_column, dataset_column, count_column) and returns: wandb