code: def continuous_or_categorical():
      # connect to h2o
  
      aa = {
          "h1": [1, 8, 4, 3, 6],
          "h2": ["fish", "cat", "fish", "dog", "bird"],
          "h3": [0, 1, 0, 0, 1],
      }
  
      df_hex = h2o.H2OFrame(aa)
  
      df_hex.show()
      df_hex.summary()
  
      assert not df_hex["h1"].isfactor()[0]
      assert df_hex["h2"].isfactor()[0]
      assert not df_hex["h3"].isfactor()[0]
  
      df_hex["h1"] = df_hex["h1"].asfactor()
      df_hex["h2"] = df_hex["h2"].asfactor()
      df_hex["h3"] = df_hex["h3"].asfactor()
  
      df_hex.show()
      df_hex.summary()
  
      assert df_hex["h1"].isfactor()[0]
      assert df_hex["h2"].isfactor()[0]
      assert df_hex["h3"].isfactor()[0]
  
      df_hex["h1"] = df_hex["h1"].asnumeric()
      df_hex["h2"] = df_hex["h2"].asnumeric()
      df_hex["h3"] = df_hex["h3"].asnumeric()
  
      df_hex.show()
      df_hex.summary()
  
      assert not df_hex["h1"].isfactor()[0]
      assert not df_hex["h2"].isfactor()[0]
      assert not df_hex["h3"].isfactor()[0]
  
label_desc: Use image node_id 1 for calling a global function with example usage: continuous_or_categorical() without return types