code: def load_leaves():
      """Load data from data/leaves/leaves.xlsx.
  
      Returns
      -------
      beta_param : array-like, shape=[172, 2]
          Beta parameters of the beta distributions fitted to each
          leaf orientation angle sample of 172 species of plants.
      distrib_type: array-like, shape=[172, ]
          Leaf orientation angle distribution type for each of the 172 species.
      """
      data = pd.read_csv(LEAVES_PATH, sep=";")
      beta_param = gs.array(data[["nu", "mu"]])
      distrib_type = gs.squeeze(gs.array(data["Distribution"]))
      return beta_param, distrib_type
  
imports: import csv
  import json
  import os
  import zipfile
  import numpy
  import pandas
  import geomstats.backend
  from geomstats.datasets._base import RemoteFileMetadata, _fetch_remote
  from geomstats.datasets.prepare_graph_data import Graph
  from geomstats.geometry.hypersphere import Hypersphere
  from geomstats.geometry.skew_symmetric_matrices import SkewSymmetricMatrices
  from geomstats.geometry.special_orthogonal import SpecialOrthogonal
label_desc: Use image node_id 6 for calling a global function with example usage: load_leaves() and returns: beta_param,  distrib_type