code: def test_select(self):
      import pandas as pd
  
      df1 = {
          "id": [1, 2, 3, 4, 5],
          "created_at": [
              "2020-02-01",
              "2020-02-02",
              "2020-02-02",
              "2020-02-02",
              "2020-02-03",
          ],
          "type": ["red", None, "blue", "blue", "yellow"],
      }
      df1 = pd.DataFrame(df1, columns=["id", "created_at", "type"])
      df2 = {
          "id": [6, 7, 8, 9, 10],
          "created_at": [
              "2020-02-01",
              "2020-02-02",
              "2020-02-02",
              "2020-02-02",
              "2020-02-03",
          ],
          "type": ["red", None, "blue", "blue", "yellow"],
      }
      df2 = pd.DataFrame(df2, columns=["id", "created_at", "type"])
      sc = get_spark_context()
      shard = SparkXShards(sc.parallelize([df1, df2]))
      selected = shard.select("id").collect()[0]
      assert list(selected.columns) == ["id"]
  
imports: import os.path
  import pytest
  from unittest import TestCase
  import bigdl.orca.data
  import bigdl.orca.data.pandas
  from bigdl.orca.data import SharedValue
  from bigdl.dllib.nncontext import *
  from bigdl.orca.data.transformer import *
  from bigdl.orca import init_orca_context
label_desc: Use image node_id 24 for calling the TestSparkXShards obj's underlying member method code with example usage: obj.test_select() without return types