code: def test_dup_across_dtypes(self):
      # dup across dtypes
      df = DataFrame(
          [[1, 1, 1.0, 5], [1, 1, 2.0, 5], [2, 1, 3.0, 5]],
          columns=["foo", "bar", "foo", "hello"],
      )
  
      df["foo2"] = 7.0
      expected = DataFrame(
          [
              [1, 1, 1.0, 5, 7.0],
              [1, 1, 2.0, 5, 7.0],
              [2, 1, 3.0, 5, 7.0],
          ],
          columns=["foo", "bar", "foo", "hello", "foo2"],
      )
      tm.assert_frame_equal(df, expected)
  
      result = df["foo"]
      expected = DataFrame(
          [[1, 1.0], [1, 2.0], [2, 3.0]], columns=["foo", "foo"]
      )
      tm.assert_frame_equal(result, expected)
  
      # multiple replacements
      df["foo"] = "string"
      expected = DataFrame(
          [
              ["string", 1, "string", 5, 7.0],
              ["string", 1, "string", 5, 7.0],
              ["string", 1, "string", 5, 7.0],
          ],
          columns=["foo", "bar", "foo", "hello", "foo2"],
      )
      tm.assert_frame_equal(df, expected)
  
      del df["foo"]
      expected = DataFrame(
          [[1, 5, 7.0], [1, 5, 7.0], [1, 5, 7.0]],
          columns=["bar", "hello", "foo2"],
      )
      tm.assert_frame_equal(df, expected)
  
imports: import numpy
  import pytest
  import pandas
  from pandas import DataFrame, Series, date_range
  import pandas._testing
label_desc: Use image node_id 4 for calling the TestDataFrameNonuniqueIndexes obj's underlying member method code with example usage: obj.test_dup_across_dtypes() without return types