code: def checkCorrectSkipAndNameTypes(
      originalFullFrame,
      csvfile,
      skipped_columns,
      all_column_names,
      all_column_types,
      modes,
      headerValue,
  ):
      colnames = []
      coltypes = dict()
      coltypelist = []
  
      for ind in range(len(all_column_names)):
          if ind not in skipped_columns:
              colnames.append(all_column_names[ind])
              coltypes[all_column_names[ind]] = all_column_types[
                  all_column_names[ind]
              ]
              coltypelist.append(
                  all_column_types[all_column_names[ind]]
              )
  
      if modes == 0:  # include both names and types
          skippedFrameUF = h2o.upload_file(
              csvfile,
              skipped_columns=skipped_columns,
              col_names=colnames,
              col_types=coltypes,
              header=headerValue,
          )
          skippedFrameIF = h2o.import_file(
              csvfile,
              skipped_columns=skipped_columns,
              col_names=colnames,
              col_types=coltypes,
              header=headerValue,
          )
      elif modes == 1:  # includes only names
          skippedFrameUF = h2o.upload_file(
              csvfile,
              skipped_columns=skipped_columns,
              col_names=colnames,
              header=headerValue,
          )
          skippedFrameIF = h2o.import_file(
              csvfile,
              skipped_columns=skipped_columns,
              col_names=colnames,
              header=headerValue,
          )
      else:  # includes only types
          skippedFrameUF = h2o.upload_file(
              csvfile,
              skipped_columns=skipped_columns,
              col_types=coltypelist,
              header=headerValue,
          )
          skippedFrameIF = h2o.import_file(
              csvfile,
              skipped_columns=skipped_columns,
              col_types=coltypelist,
              header=headerValue,
          )
      pyunit_utils.compare_frames_local(
          skippedFrameUF, skippedFrameIF, prob=0.5
      )
  
      skipCounter = 0
      typeDict = originalFullFrame.types
      frameNames = originalFullFrame.names
      for cindex in range(len(frameNames)):
          if cindex not in skipped_columns:
              print("Checking column {0}...".format(cindex))
              if typeDict[frameNames[cindex]] == "enum":
                  pyunit_utils.compare_frames_local_onecolumn_NA_enum(
                      originalFullFrame[cindex],
                      skippedFrameIF[skipCounter],
                      prob=1,
                      tol=1e-10,
                      returnResult=False,
                  )
              elif typeDict[frameNames[cindex]] == "string":
                  pyunit_utils.compare_frames_local_onecolumn_NA_string(
                      originalFullFrame[cindex],
                      skippedFrameIF[skipCounter],
                      prob=1,
                      returnResult=False,
                  )
              else:
                  pyunit_utils.compare_frames_local_onecolumn_NA(
                      originalFullFrame[cindex],
                      skippedFrameIF[skipCounter],
                      prob=1,
                      tol=1e-10,
                      returnResult=False,
                  )
              skipCounter = skipCounter + 1
  
imports: import sys
  import h2o
  from tests import pyunit_utils
  import random
label_desc: Use image node_id 2 for calling a global function with example usage: checkCorrectSkipAndNameTypes(originalFullFrame, csvfile, skipped_columns, all_column_names, all_column_types, modes, headerValue) without return types