avoid some upcasting when its not the purpose of the test

Author: MarcoGorelli

pandas/tests/frame/test_query_eval.py

@@ -448,7 +448,7 @@ def test_date_index_query(self):
  def test_date_index_query_with_NaT(self):
  engine, parser = self.engine, self.parser
  n = 10
- df = DataFrame(np.random.randn(n, 3))
+ df = DataFrame(np.random.randn(n, 3)).astype({0: object})
  df["dates1"] = date_range("1/1/2012", periods=n)
  df["dates3"] = date_range("1/1/2014", periods=n)
  df.iloc[0, 0] = pd.NaT
@@ -809,7 +809,7 @@ def test_date_index_query_with_NaT(self):
  engine, parser = self.engine, self.parser
  n = 10
  df = DataFrame(np.random.randn(n, 3))
- df["dates1"] = date_range("1/1/2012", periods=n)
+ df["dates1"] = date_range("1/1/2012", periods=n).astype({0: object})
  df["dates3"] = date_range("1/1/2014", periods=n)
  df.iloc[0, 0] = pd.NaT
  return_value = df.set_index("dates1", inplace=True, drop=True)

pandas/tests/frame/test_reductions.py

@@ -448,11 +448,15 @@ def test_var_std(self, datetime_frame):
  @pytest.mark.parametrize("meth", ["sem", "var", "std"])
  def test_numeric_only_flag(self, meth):
  # GH 9201
- df1 = DataFrame(np.random.randn(5, 3), columns=["foo", "bar", "baz"])
+ df1 = DataFrame(np.random.randn(5, 3), columns=["foo", "bar", "baz"]).astype(
+ {"foo": object}
+ )
  # set one entry to a number in str format
  df1.loc[0, "foo"] = "100"
 
- df2 = DataFrame(np.random.randn(5, 3), columns=["foo", "bar", "baz"])
+ df2 = DataFrame(np.random.randn(5, 3), columns=["foo", "bar", "baz"]).astype(
+ {"foo": object}
+ )
  # set one entry to a non-number str
  df2.loc[0, "foo"] = "a"
 

pandas/tests/groupby/test_timegrouper.py

@@ -102,7 +102,7 @@ def test_groupby_with_timegrouper(self):
  index=date_range(
  "20130901", "20131205", freq="5D", name="Date", inclusive="left"
  ),
- )
+ ).astype({"Buyer": object})
  expected.iloc[0, 0] = "CarlCarlCarl"
  expected.iloc[6, 0] = "CarlCarl"
  expected.iloc[18, 0] = "Joe"

pandas/tests/series/methods/test_replace.py

@@ -16,7 +16,7 @@ def test_replace_explicit_none(self):
  expected = pd.Series([0, 0, None], dtype=object)
  tm.assert_series_equal(result, expected)
 
- df = pd.DataFrame(np.zeros((3, 3)))
+ df = pd.DataFrame(np.zeros((3, 3))).astype({2: object})
  df.iloc[2, 2] = ""
  result = df.replace("", None)
  expected = pd.DataFrame(