code: def load_sao_paulo(dirname=None):
      """Load data from data/sao_paulo/jam_count.csv and data/sao_paulo/jam_table.csv.
  
      Load the dataset of traffic jams in Sao Paulo from 2001 to 2019.
  
      jam_count.csv lists the number of traffic jams for each road in Sao Paulo in that
      time span.
      jam_table.csv lists the dates, roads, and durations of all these traffic jams.
  
      The dataset is accessible here:
      https://www.kaggle.com/datasets/danlessa/sao-paulo-traffic-jams-since-2001
  
      Returns
      -------
      jam_table : pandas.DataFrame
          Columns : name (of the road), date (of traffic jam), duration.
      jam_count : dictionary
          Keys : name of the road
          Values : count of traffic jams between 2001 and 2019.
      """
      file_path = _fetch_remote(
          SAO_PAULO_ARCHIVE.url,
          SAO_PAULO_ARCHIVE.filename,
          dirname=dirname,
      )
  
      with zipfile.ZipFile(file_path, "r") as folder:
          with folder.open(SAO_PAULO_TABLE, "r") as table_file:
              jam_table = pd.read_csv(table_file)
  
          with folder.open(SAO_PAULO_COUNT, "r") as count_file:
              jam_count = pd.read_csv(count_file)
  
      jam_table = jam_table.drop("Unnamed: 0", axis=1)
  
      del jam_count["Unnamed: 0"]
      jam_count_df = pd.DataFrame(jam_count, index=[0])
      jam_count = dict(
          zip(list(jam_count_df.columns), list(jam_count_df.values[0]))
      )
  
      return jam_table, jam_count
  
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 11 for calling a global function with example usage: load_sao_paulo(dirname) and returns: jam_table,  jam_count