code: def pubdev_drop_duplicates():
      # Test using column name
      insurance = h2o.import_file(
          pyunit_utils.locate("smalldata/glm_test/insurance.csv")
      )
      deduplicated_frame = insurance.drop_duplicates(
          columns=["District"], keep="first"
      )
  
      assert deduplicated_frame is not None
      assert deduplicated_frame.nrows == 4
      insurance.names == deduplicated_frame.names
  
      # Test using column index
      deduplicated_frame = insurance.drop_duplicates(
          columns=[0], keep="first"
      )
      assert deduplicated_frame is not None
      assert deduplicated_frame.nrows == 4
      insurance.names == deduplicated_frame.names
  
      # Test using two columns
      deduplicated_frame = insurance.drop_duplicates(
          columns=["District", "Group"], keep="first"
      )
      assert deduplicated_frame is not None
      assert deduplicated_frame.nrows == 16
      insurance.names == deduplicated_frame.names
  
      # Compare INSURANCE to pandas - keep first
      compare_dataset_deduplication(
          "smalldata/glm_test/insurance.csv",
          ["District", "Group"],
          "first",
      )
      compare_dataset_deduplication(
          "smalldata/glm_test/insurance.csv",
          ["District", "Group"],
          "last",
      )
  
      # Compare Airlines to PANDAS
      compare_dataset_deduplication(
          "smalldata/testng/airlines_train.csv",
          ["Origin", "Dest", "Distance"],
          "first",
      )
      compare_dataset_deduplication(
          "smalldata/testng/airlines_train.csv",
          ["Origin", "Dest", "Distance"],
          "last",
      )
  
      # Compare IRIS to PANDAS
      compare_dataset_deduplication(
          "smalldata/extdata/iris_wheader.csv",
          ["sepal_len", "class"],
          "first",
      )
      compare_dataset_deduplication(
          "smalldata/extdata/iris_wheader.csv",
          ["sepal_len", "class"],
          "last",
      )
  
      # Compare CREDIT CARD to PANDAS
      compare_dataset_deduplication(
          "smalldata/kaggle/CreditCard/creditcard_train_cat.csv",
          ["SEX", "EDUCATION", "MARRIAGE"],
          "first",
      )
      compare_dataset_deduplication(
          "smalldata/kaggle/CreditCard/creditcard_train_cat.csv",
          ["SEX", "EDUCATION", "MARRIAGE"],
          "last",
      )
  
      # Compare WEATHER - no duplicates (date column is used)
      compare_dataset_deduplication(
          "smalldata/junit/weather.csv", ["Date"], "first"
      )
      compare_dataset_deduplication(
          "smalldata/junit/weather.csv", ["Date"], "last"
      )
  
      # Compare CHESS - contains NAs
      compare_dataset_deduplication(
          "smalldata/parser/orc/orc2csv/chess_train_NA.csv",
          ["C2"],
          "first",
      )
      compare_dataset_deduplication(
          "smalldata/parser/orc/orc2csv/chess_train_NA.csv",
          ["C2"],
          "last",
      )
  
imports: import sys
  import h2o
  from tests import pyunit_utils
  from pandas.util.testing import assert_frame_equal
label_desc: Use image node_id 1 for calling a global function with example usage: pubdev_drop_duplicates() without return types