code: def get_data_points(meta_data):
      x = meta_data
      y_avg = [meta_data[d]["mean"] for d in meta_data]
      y_mode = [meta_data[d]["mode"] for d in meta_data]
      y_median = [meta_data[d]["median"] for d in meta_data]
      y_std = [meta_data[d]["std"] for d in meta_data]
      y_num_samples = [len(meta_data[d]["data"]) for d in meta_data]
      return {
          "x": x,
          "y_avg": y_avg,
          "y_mode": y_mode,
          "y_median": y_median,
          "y_std": y_std,
          "y_num_samples": y_num_samples,
      }
  
file_path: TTS/notebooks/dataset_analysis/analyze.py
imports: import matplotlib.pyplot
  from statistics import stdev, mode, mean, median
  from statistics import StatisticsError
  import argparse
  import os
  import csv
  import seaborn
  import random
  from text.cmudict import CMUDict
label_desc: Use image node_id 4 for calling a global function with example usage: get_data_points(meta_data) and returns: dict