code: def load_data(input_file: str) -> list:
      df = pd.read_csv(input_file)
      df.rename(
          inplace=True,
          columns={
              "VisitorId": "user_id",
              "Time entered": "enter_time",
              "Time spent (minutes)": "spent_minutes",
              "Money spent (euros)": "spent_money",
              "Day": "day",
          },
      )
      # Double the inputs so we have twice as many contributions per partition
      df_double = pd.concat([df, df])
      df_double.columns = df.columns
      return [index_row[1] for index_row in df_double.iterrows()]
  
file_path: pipelinedp/examples/restaurant_visits/run_without_frameworks_tuning.py
imports: from absl import app
  from absl import flags
  import pipeline_dp
  import pandas
  import analysis
  from analysis import parameter_tuning
  from pipeline_dp.dataset_histograms import computing_histograms
label_desc: Use image node_id 2 for calling a global function with example usage: load_data(input_file) and returns: unknown