From e0e778d01df43c583721e644b79b88d815f3f7fd Mon Sep 17 00:00:00 2001
From: MomIsBestFriend <>
Date: Mon, 9 Dec 2019 22:40:13 +0200
Subject: [PATCH 1/3] STY: Underscores for long numbers

---
 pandas/_libs/testing.pyx                |  16 ++--
 pandas/core/algorithms.py               |  27 ++++---
 pandas/core/arrays/categorical.py       |   7 +-
 pandas/core/arrays/timedeltas.py        |   2 +-
 pandas/core/base.py                     |   2 +-
 pandas/core/computation/align.py        |  10 ++-
 pandas/core/computation/common.py       |  16 ++--
 pandas/core/computation/ops.py          |   4 +-
 pandas/tests/io/formats/test_format.py  | 103 ++++++++++++------------
 pandas/tests/io/parser/test_usecols.py  |  33 +++++---
 pandas/tests/io/pytables/test_compat.py |   9 ++-
 11 files changed, 128 insertions(+), 101 deletions(-)

diff --git a/pandas/_libs/testing.pyx b/pandas/_libs/testing.pyx
index 8b847350cb1ff..e41914f3aa9ad 100644
--- a/pandas/_libs/testing.pyx
+++ b/pandas/_libs/testing.pyx
@@ -66,7 +66,8 @@ cpdef assert_almost_equal(a, b,
                           check_less_precise=False,
                           bint check_dtype=True,
                           obj=None, lobj=None, robj=None):
-    """Check that left and right objects are almost equal.
+    """
+    Check that left and right objects are almost equal.
 
     Parameters
     ----------
@@ -89,7 +90,6 @@ cpdef assert_almost_equal(a, b,
         Specify right object name being compared, internally used to show
         appropriate assertion message
     """
-
     cdef:
         int decimal
         double diff = 0.0
@@ -127,9 +127,9 @@ cpdef assert_almost_equal(a, b,
             # classes can't be the same, to raise error
             assert_class_equal(a, b, obj=obj)
 
-        assert has_length(a) and has_length(b), (
-            f"Can't compare objects without length, one or both is invalid: "
-            f"({a}, {b})")
+        assert has_length(a) and has_length(b), ("Can't compare objects without "
+                                                 "length, one or both is invalid: "
+                                                 f"({a}, {b})")
 
         if a_is_ndarray and b_is_ndarray:
             na, nb = a.size, b.size
@@ -157,7 +157,7 @@ cpdef assert_almost_equal(a, b,
             else:
                 r = None
 
-            raise_assert_detail(obj, f'{obj} length are different', na, nb, r)
+            raise_assert_detail(obj, f"{obj} length are different", na, nb, r)
 
         for i in xrange(len(a)):
             try:
@@ -169,8 +169,8 @@ cpdef assert_almost_equal(a, b,
 
         if is_unequal:
             from pandas.util.testing import raise_assert_detail
-            msg = (f'{obj} values are different '
-                   f'({np.round(diff * 100.0 / na, 5)} %)')
+            msg = (f"{obj} values are different "
+                   f"({np.round(diff * 100.0 / na, 5)} %)")
             raise_assert_detail(obj, msg, lobj, robj)
 
         return True
diff --git a/pandas/core/algorithms.py b/pandas/core/algorithms.py
index 6ccd71a567b02..42cfd9d54ac19 100644
--- a/pandas/core/algorithms.py
+++ b/pandas/core/algorithms.py
@@ -391,16 +391,15 @@ def isin(comps, values) -> np.ndarray:
     ndarray[bool]
         Same length as `comps`.
     """
-
     if not is_list_like(comps):
         raise TypeError(
-            "only list-like objects are allowed to be passed"
-            f" to isin(), you passed a [{type(comps).__name__}]"
+            "only list-like objects are allowed to be passed "
+            f"to isin(), you passed a [{type(comps).__name__}]"
         )
     if not is_list_like(values):
         raise TypeError(
-            "only list-like objects are allowed to be passed"
-            f" to isin(), you passed a [{type(values).__name__}]"
+            "only list-like objects are allowed to be passed "
+            f"to isin(), you passed a [{type(values).__name__}]"
         )
 
     if not isinstance(values, (ABCIndex, ABCSeries, np.ndarray)):
@@ -421,7 +420,7 @@ def isin(comps, values) -> np.ndarray:
 
     # GH16012
     # Ensure np.in1d doesn't get object types or it *may* throw an exception
-    if len(comps) > 1000000 and not is_object_dtype(comps):
+    if len(comps) > 1_000_000 and not is_object_dtype(comps):
         f = np.in1d
     elif is_integer_dtype(comps):
         try:
@@ -833,8 +832,8 @@ def mode(values, dropna: bool = True) -> ABCSeries:
     result = f(values, dropna=dropna)
     try:
         result = np.sort(result)
-    except TypeError as e:
-        warn(f"Unable to sort modes: {e}")
+    except TypeError as err:
+        warn(f"Unable to sort modes: {err}")
 
     result = _reconstruct_data(result, original.dtype, original)
     return Series(result)
@@ -1019,7 +1018,8 @@ def quantile(x, q, interpolation_method="fraction"):
     values = np.sort(x)
 
     def _interpolate(a, b, fraction):
-        """Returns the point at the given fraction between a and b, where
+        """
+        Returns the point at the given fraction between a and b, where
         'fraction' must be between 0 and 1.
         """
         return a + (b - a) * fraction
@@ -1192,7 +1192,8 @@ def compute(self, method):
                 )
 
         def get_indexer(current_indexer, other_indexer):
-            """Helper function to concat `current_indexer` and `other_indexer`
+            """
+            Helper function to concat `current_indexer` and `other_indexer`
             depending on `method`
             """
             if method == "nsmallest":
@@ -1660,7 +1661,7 @@ def take_nd(
 
 def take_2d_multi(arr, indexer, fill_value=np.nan):
     """
-    Specialized Cython take which sets NaN values in one pass
+    Specialized Cython take which sets NaN values in one pass.
     """
     # This is only called from one place in DataFrame._reindex_multi,
     #  so we know indexer is well-behaved.
@@ -1988,8 +1989,8 @@ def sort_mixed(values):
 
     if not is_list_like(codes):
         raise TypeError(
-            "Only list-like objects or None are allowed to be"
-            "passed to safe_sort as codes"
+            "Only list-like objects or None are allowed to "
+            "be passed to safe_sort as codes"
         )
     codes = ensure_platform_int(np.asarray(codes))
 
diff --git a/pandas/core/arrays/categorical.py b/pandas/core/arrays/categorical.py
index 1e470e44ed933..439f36c960617 100644
--- a/pandas/core/arrays/categorical.py
+++ b/pandas/core/arrays/categorical.py
@@ -299,7 +299,7 @@ class Categorical(ExtensionArray, PandasObject):
 
     # For comparisons, so that numpy uses our implementation if the compare
     # ops, which raise
-    __array_priority__ = 1000
+    __array_priority__ = 1_000
     _dtype = CategoricalDtype(ordered=False)
     # tolist is not actually deprecated, just suppressed in the __dir__
     _deprecations = PandasObject._deprecations | frozenset(["tolist", "itemsize"])
@@ -494,14 +494,13 @@ def astype(self, dtype: Dtype, copy: bool = True) -> ArrayLike:
         if is_extension_array_dtype(dtype):
             return array(self, dtype=dtype, copy=copy)  # type: ignore # GH 28770
         if is_integer_dtype(dtype) and self.isna().any():
-            msg = "Cannot convert float NaN to integer"
-            raise ValueError(msg)
+            raise ValueError("Cannot convert float NaN to integer")
         return np.array(self, dtype=dtype, copy=copy)
 
     @cache_readonly
     def size(self) -> int:
         """
-        return the len of myself
+        Return the len of myself.
         """
         return self._codes.size
 
diff --git a/pandas/core/arrays/timedeltas.py b/pandas/core/arrays/timedeltas.py
index 56c4a1a201eeb..03699398fddf5 100644
--- a/pandas/core/arrays/timedeltas.py
+++ b/pandas/core/arrays/timedeltas.py
@@ -157,7 +157,7 @@ class TimedeltaArray(dtl.DatetimeLikeArrayMixin, dtl.TimelikeOps):
 
     _typ = "timedeltaarray"
     _scalar_type = Timedelta
-    __array_priority__ = 1000
+    __array_priority__ = 1_000
     # define my properties & methods for delegation
     _other_ops: List[str] = []
     _bool_ops: List[str] = []
diff --git a/pandas/core/base.py b/pandas/core/base.py
index 88b8fe405c8e4..e52e66a07eb6d 100644
--- a/pandas/core/base.py
+++ b/pandas/core/base.py
@@ -618,7 +618,7 @@ class IndexOpsMixin:
     """
 
     # ndarray compatibility
-    __array_priority__ = 1000
+    __array_priority__ = 1_000
     _deprecations: FrozenSet[str] = frozenset(
         ["tolist", "item"]  # tolist is not deprecated, just suppressed in the __dir__
     )
diff --git a/pandas/core/computation/align.py b/pandas/core/computation/align.py
index 9390eb47d07ee..bf340783098c5 100644
--- a/pandas/core/computation/align.py
+++ b/pandas/core/computation/align.py
@@ -35,7 +35,9 @@ def _zip_axes_from_type(typ, new_axes):
 
 
 def _any_pandas_objects(terms) -> bool:
-    """Check a sequence of terms for instances of PandasObject."""
+    """
+    Check a sequence of terms for instances of PandasObject.
+    """
     return any(isinstance(term.value, PandasObject) for term in terms)
 
 
@@ -98,7 +100,7 @@ def _align_core(terms):
                 reindexer_size = len(reindexer)
 
                 ordm = np.log10(max(1, abs(reindexer_size - term_axis_size)))
-                if ordm >= 1 and reindexer_size >= 10000:
+                if ordm >= 1 and reindexer_size >= 10_000:
                     w = (
                         f"Alignment difference on axis {axis} is larger "
                         f"than an order of magnitude on term {repr(terms[i].name)}, "
@@ -116,7 +118,9 @@ def _align_core(terms):
 
 
 def align_terms(terms):
-    """Align a set of terms"""
+    """
+    Align a set of terms.
+    """
     try:
         # flatten the parse tree (a nested list, really)
         terms = list(com.flatten(terms))
diff --git a/pandas/core/computation/common.py b/pandas/core/computation/common.py
index da47449d5e62e..994f470942cd1 100644
--- a/pandas/core/computation/common.py
+++ b/pandas/core/computation/common.py
@@ -9,15 +9,19 @@
 
 
 def _ensure_decoded(s):
-    """ if we have bytes, decode them to unicode """
+    """
+    If we have bytes, decode them to unicode.
+    """
     if isinstance(s, (np.bytes_, bytes)):
         s = s.decode(get_option("display.encoding"))
     return s
 
 
 def result_type_many(*arrays_and_dtypes):
-    """ wrapper around numpy.result_type which overcomes the NPY_MAXARGS (32)
-    argument limit """
+    """
+    Wrapper around numpy.result_type which overcomes the NPY_MAXARGS (32)
+    argument limit.
+    """
     try:
         return np.result_type(*arrays_and_dtypes)
     except ValueError:
@@ -26,8 +30,10 @@ def result_type_many(*arrays_and_dtypes):
 
 
 def _remove_spaces_column_name(name):
-    """Check if name contains any spaces, if it contains any spaces
-    the spaces will be removed and an underscore suffix is added."""
+    """
+    Check if name contains any spaces, if it contains any spaces
+    the spaces will be removed and an underscore suffix is added.
+    """
     if not isinstance(name, str) or " " not in name:
         return name
 
diff --git a/pandas/core/computation/ops.py b/pandas/core/computation/ops.py
index 2215629ec0717..cb166ba65152b 100644
--- a/pandas/core/computation/ops.py
+++ b/pandas/core/computation/ops.py
@@ -506,8 +506,8 @@ def __init__(self, lhs, rhs, **kwargs):
 
         if not isnumeric(lhs.return_type) or not isnumeric(rhs.return_type):
             raise TypeError(
-                f"unsupported operand type(s) for {self.op}:"
-                f" '{lhs.return_type}' and '{rhs.return_type}'"
+                f"unsupported operand type(s) for {self.op}: "
+                f"'{lhs.return_type}' and '{rhs.return_type}'"
             )
 
         # do not upcast float32s to float64 un-necessarily
diff --git a/pandas/tests/io/formats/test_format.py b/pandas/tests/io/formats/test_format.py
index e875a6f137d80..de0fcb2b06960 100644
--- a/pandas/tests/io/formats/test_format.py
+++ b/pandas/tests/io/formats/test_format.py
@@ -233,7 +233,7 @@ def test_repr_truncation(self):
                 else:
                     assert "..." not in line
 
-        with option_context("display.max_colwidth", 999999):
+        with option_context("display.max_colwidth", 999_999):
             assert "..." not in repr(df)
 
         with option_context("display.max_colwidth", max_len + 2):
@@ -286,11 +286,11 @@ def test_repr_chop_threshold_column_below(self):
             )
 
     def test_repr_obeys_max_seq_limit(self):
-        with option_context("display.max_seq_items", 2000):
-            assert len(printing.pprint_thing(list(range(1000)))) > 1000
+        with option_context("display.max_seq_items", 2_000):
+            assert len(printing.pprint_thing(list(range(1_000)))) > 1_000
 
         with option_context("display.max_seq_items", 5):
-            assert len(printing.pprint_thing(list(range(1000)))) < 100
+            assert len(printing.pprint_thing(list(range(1_000)))) < 100
 
     def test_repr_set(self):
         assert printing.pprint_thing({1}) == "{1}"
@@ -354,10 +354,10 @@ def test_expand_frame_repr(self):
     def test_repr_non_interactive(self):
         # in non interactive mode, there can be no dependency on the
         # result of terminal auto size detection
-        df = DataFrame("hello", index=range(1000), columns=range(5))
+        df = DataFrame("hello", index=range(1_000), columns=range(5))
 
         with option_context(
-            "mode.sim_interactive", False, "display.width", 0, "display.max_rows", 5000
+            "mode.sim_interactive", False, "display.width", 0, "display.max_rows", 5_000
         ):
             assert not has_truncated_repr(df)
             assert not has_expanded_repr(df)
@@ -408,10 +408,10 @@ def test_repr_truncation_column_size(self):
         # determine size of truncation (...) column
         df = pd.DataFrame(
             {
-                "a": [108480, 30830],
-                "b": [12345, 12345],
-                "c": [12345, 12345],
-                "d": [12345, 12345],
+                "a": [108_480, 30_830],
+                "b": [12_345, 12_345],
+                "c": [12_345, 12_345],
+                "d": [12_345, 12_345],
                 "e": ["a" * 50] * 2,
             }
         )
@@ -719,7 +719,7 @@ def test_east_asian_unicode_false(self):
 
         # mid col
         df = DataFrame(
-            {"a": ["あ", "いいい", "う", "ええええええ"], "b": [1, 222, 33333, 4]},
+            {"a": ["あ", "いいい", "う", "ええええええ"], "b": [1, 222, 33_333, 4]},
             index=["a", "bb", "c", "ddd"],
         )
         expected = (
@@ -755,7 +755,7 @@ def test_east_asian_unicode_false(self):
 
         # column name
         df = DataFrame(
-            {"b": ["あ", "いいい", "う", "ええええええ"], "あああああ": [1, 222, 33333, 4]},
+            {"b": ["あ", "いいい", "う", "ええええええ"], "あああああ": [1, 222, 33_333, 4]},
             index=["a", "bb", "c", "ddd"],
         )
         expected = (
@@ -857,7 +857,7 @@ def test_east_asian_unicode_true(self):
 
             # mid col
             df = DataFrame(
-                {"a": ["あ", "いいい", "う", "ええええええ"], "b": [1, 222, 33333, 4]},
+                {"a": ["あ", "いいい", "う", "ええええええ"], "b": [1, 222, 33_333, 4]},
                 index=["a", "bb", "c", "ddd"],
             )
             expected = (
@@ -869,7 +869,7 @@ def test_east_asian_unicode_true(self):
 
             # last col
             df = DataFrame(
-                {"a": [1, 222, 33333, 4], "b": ["あ", "いいい", "う", "ええええええ"]},
+                {"a": [1, 222, 33_333, 4], "b": ["あ", "いいい", "う", "ええええええ"]},
                 index=["a", "bb", "c", "ddd"],
             )
             expected = (
@@ -895,7 +895,7 @@ def test_east_asian_unicode_true(self):
 
             # column name
             df = DataFrame(
-                {"b": ["あ", "いいい", "う", "ええええええ"], "あああああ": [1, 222, 33333, 4]},
+                {"b": ["あ", "いいい", "う", "ええええええ"], "あああああ": [1, 222, 33_333, 4]},
                 index=["a", "bb", "c", "ddd"],
             )
             expected = (
@@ -1002,7 +1002,7 @@ def test_east_asian_unicode_true(self):
 
             # ambiguous unicode
             df = DataFrame(
-                {"b": ["あ", "いいい", "¡¡", "ええええええ"], "あああああ": [1, 222, 33333, 4]},
+                {"b": ["あ", "いいい", "¡¡", "ええええええ"], "あああああ": [1, 222, 33_333, 4]},
                 index=["a", "bb", "c", "¡¡¡"],
             )
             expected = (
@@ -1339,7 +1339,7 @@ def test_wide_repr_wide_long_columns(self):
             assert "ddddd" in result
 
     def test_long_series(self):
-        n = 1000
+        n = 1_000
         s = Series(
             np.random.randint(-50, 50, n),
             index=["s{x:04d}".format(x=x) for x in range(n)],
@@ -1545,7 +1545,7 @@ def test_to_string_float_formatting(self):
         )
 
         df = DataFrame(
-            {"x": [0, 0.25, 3456.000, 12e45, 1.64e6, 1.7e8, 1.253456, np.pi, -1e6]}
+            {"x": [0, 0.25, 3_456.000, 12e45, 1.64e6, 1.7e8, 1.253_456, np.pi, -1e6]}
         )
 
         df_s = df.to_string()
@@ -1566,7 +1566,7 @@ def test_to_string_float_formatting(self):
             )
         assert df_s == expected
 
-        df = DataFrame({"x": [3234, 0.253]})
+        df = DataFrame({"x": [3_234, 0.253]})
         df_s = df.to_string()
 
         expected = "          x\n0  3234.000\n1     0.253"
@@ -1587,7 +1587,7 @@ def test_to_string_float_formatting(self):
     def test_to_string_float_format_no_fixed_width(self):
 
         # GH 21625
-        df = DataFrame({"x": [0.19999]})
+        df = DataFrame({"x": [0.19_999]})
         expected = "      x\n0 0.200"
         assert df.to_string(float_format="%.3f") == expected
 
@@ -1636,9 +1636,9 @@ def test_to_string_complex_float_formatting(self):
             df = DataFrame(
                 {
                     "x": [
-                        (0.4467846931321966 + 0.0715185102060818j),
-                        (0.2739442392974528 + 0.23515228785438969j),
-                        (0.26974928742135185 + 0.3250604054898979j),
+                        (0.4_467_846_931_321_966 + 0.0_715_185_102_060_818j),
+                        (0.2_739_442_392_974_528 + 0.23_515_228_785_438_969j),
+                        (0.26_974_928_742_135_185 + 0.3_250_604_054_898_979j),
                         (-1j),
                     ]
                 }
@@ -1690,7 +1690,7 @@ def test_to_string_index_formatter(self):
 
     def test_to_string_left_justify_cols(self):
         tm.reset_display_options()
-        df = DataFrame({"x": [3234, 0.253]})
+        df = DataFrame({"x": [3_234, 0.253]})
         df_s = df.to_string(justify="left")
         expected = "   x       \n0  3234.000\n1     0.253"
         assert df_s == expected
@@ -1699,7 +1699,7 @@ def test_to_string_format_na(self):
         tm.reset_display_options()
         df = DataFrame(
             {
-                "A": [np.nan, -1, -2.1234, 3, 4],
+                "A": [np.nan, -1, -2.1_234, 3, 4],
                 "B": [np.nan, "foo", "foooo", "fooooo", "bar"],
             }
         )
@@ -1738,7 +1738,7 @@ def test_to_string_format_inf(self):
         tm.reset_display_options()
         df = DataFrame(
             {
-                "A": [-np.inf, np.inf, -1, -2.1234, 3, 4],
+                "A": [-np.inf, np.inf, -1, -2.1_234, 3, 4],
                 "B": [-np.inf, np.inf, "foo", "foooo", "fooooo", "bar"],
             }
         )
@@ -2076,11 +2076,11 @@ def __getitem__(self, key):
 
     def test_float_trim_zeros(self):
         vals = [
-            2.08430917305e10,
-            3.52205017305e10,
-            2.30674817305e10,
-            2.03954217305e10,
-            5.59897817305e10,
+            2.08_430_917_305e10,
+            3.52_205_017_305e10,
+            2.30_674_817_305e10,
+            2.03_954_217_305e10,
+            5.59_897_817_305e10,
         ]
         skip = True
         for line in repr(DataFrame({"A": vals})).split("\n")[:-2]:
@@ -2140,7 +2140,7 @@ def test_repr_unicode(self):
         s = Series(["\u03c3"] * 10)
         repr(s)
 
-        a = Series(["\u05d0"] * 1000)
+        a = Series(["\u05d0"] * 1_000)
         a.name = "title1"
         repr(a)
 
@@ -2202,7 +2202,7 @@ def test_to_string_mixed(self):
         assert result == expected
 
     def test_to_string_float_na_spacing(self):
-        s = Series([0.0, 1.5678, 2.0, -3.0, 4.0])
+        s = Series([0.0, 1.5_678, 2.0, -3.0, 4.0])
         s[::2] = np.nan
 
         result = s.to_string()
@@ -2261,7 +2261,7 @@ def test_east_asian_unicode_series(self):
         idx = pd.MultiIndex.from_tuples(
             [("あ", "いい"), ("う", "え"), ("おおお", "かかかか"), ("き", "くく")]
         )
-        s = Series([1, 22, 3333, 44444], index=idx)
+        s = Series([1, 22, 3_333, 44_444], index=idx)
         expected = (
             "あ    いい          1\n"
             "う    え          22\n"
@@ -2271,7 +2271,7 @@ def test_east_asian_unicode_series(self):
         assert repr(s) == expected
 
         # object dtype, shorter than unicode repr
-        s = Series([1, 22, 3333, 44444], index=[1, "AB", np.nan, "あああ"])
+        s = Series([1, 22, 3_333, 44_444], index=[1, "AB", np.nan, "あああ"])
         expected = (
             "1          1\nAB        22\nNaN     3333\nあああ    44444\ndtype: int64"
         )
@@ -2279,7 +2279,7 @@ def test_east_asian_unicode_series(self):
 
         # object dtype, longer than unicode repr
         s = Series(
-            [1, 22, 3333, 44444], index=[1, "AB", pd.Timestamp("2011-01-01"), "あああ"]
+            [1, 22, 3_333, 44_444], index=[1, "AB", pd.Timestamp("2011-01-01"), "あああ"]
         )
         expected = (
             "1                          1\n"
@@ -2356,7 +2356,7 @@ def test_east_asian_unicode_series(self):
             idx = pd.MultiIndex.from_tuples(
                 [("あ", "いい"), ("う", "え"), ("おおお", "かかかか"), ("き", "くく")]
             )
-            s = Series([1, 22, 3333, 44444], index=idx)
+            s = Series([1, 22, 3_333, 44_444], index=idx)
             expected = (
                 "あ      いい            1\n"
                 "う      え             22\n"
@@ -2367,7 +2367,7 @@ def test_east_asian_unicode_series(self):
             assert repr(s) == expected
 
             # object dtype, shorter than unicode repr
-            s = Series([1, 22, 3333, 44444], index=[1, "AB", np.nan, "あああ"])
+            s = Series([1, 22, 3_333, 44_444], index=[1, "AB", np.nan, "あああ"])
             expected = (
                 "1             1\nAB           22\nNaN        3333\n"
                 "あああ    44444\ndtype: int64"
@@ -2376,7 +2376,8 @@ def test_east_asian_unicode_series(self):
 
             # object dtype, longer than unicode repr
             s = Series(
-                [1, 22, 3333, 44444], index=[1, "AB", pd.Timestamp("2011-01-01"), "あああ"]
+                [1, 22, 3_333, 44_444],
+                index=[1, "AB", pd.Timestamp("2011-01-01"), "あああ"],
             )
             expected = (
                 "1                          1\n"
@@ -2419,11 +2420,11 @@ def test_east_asian_unicode_series(self):
 
     def test_float_trim_zeros(self):
         vals = [
-            2.08430917305e10,
-            3.52205017305e10,
-            2.30674817305e10,
-            2.03954217305e10,
-            5.59897817305e10,
+            2.08_430_917_305e10,
+            3.52_205_017_305e10,
+            2.30_674_817_305e10,
+            2.03_954_217_305e10,
+            5.59_897_817_305e10,
         ]
         for line in repr(Series(vals)).split("\n"):
             if line.startswith("dtype:"):
@@ -2478,7 +2479,7 @@ def test_timedelta64(self):
 
         from datetime import datetime, timedelta
 
-        Series(np.array([1100, 20], dtype="timedelta64[ns]")).to_string()
+        Series(np.array([11_00, 20], dtype="timedelta64[ns]")).to_string()
 
         s = Series(date_range("2012-1-1", periods=3, freq="D"))
 
@@ -2623,7 +2624,7 @@ def test_max_multi_index_display(self):
 
     # Make sure #8532 is fixed
     def test_consistent_format(self):
-        s = pd.Series([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.9999, 1, 1] * 10)
+        s = pd.Series([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.9_999, 1, 1] * 10)
         with option_context("display.max_rows", 10, "display.show_dimensions", False):
             res = repr(s)
         exp = (
@@ -2823,19 +2824,19 @@ def test_output_significant_digits(self):
                     "col1": [
                         9.999e-8,
                         1e-7,
-                        1.0001e-7,
+                        1.0_001e-7,
                         2e-7,
                         4.999e-7,
                         5e-7,
-                        5.0001e-7,
+                        5.0_001e-7,
                         6e-7,
                         9.999e-7,
                         1e-6,
-                        1.0001e-6,
+                        1.0_001e-6,
                         2e-6,
                         4.999e-6,
                         5e-6,
-                        5.0001e-6,
+                        5.0_001e-6,
                         6e-6,
                     ]
                 }
@@ -2890,7 +2891,7 @@ def test_too_long(self):
         with pd.option_context("display.precision", 4):
             # need both a number > 1e6 and something that normally formats to
             # having length > display.precision + 6
-            df = pd.DataFrame(dict(x=[12345.6789]))
+            df = pd.DataFrame(dict(x=[12_345.6_789]))
             assert str(df) == "            x\n0  12345.6789"
             df = pd.DataFrame(dict(x=[2e6]))
             assert str(df) == "           x\n0  2000000.0"
diff --git a/pandas/tests/io/parser/test_usecols.py b/pandas/tests/io/parser/test_usecols.py
index afe19608ea5c6..741ef90cb3153 100644
--- a/pandas/tests/io/parser/test_usecols.py
+++ b/pandas/tests/io/parser/test_usecols.py
@@ -197,9 +197,12 @@ def test_usecols_with_whitespace(all_parsers):
     "usecols,expected",
     [
         # Column selection by index.
-        ([0, 1], DataFrame(data=[[1000, 2000], [4000, 5000]], columns=["2", "0"])),
+        ([0, 1], DataFrame(data=[[1_000, 2_000], [4_000, 5_000]], columns=["2", "0"])),
         # Column selection by name.
-        (["0", "1"], DataFrame(data=[[2000, 3000], [5000, 6000]], columns=["0", "1"])),
+        (
+            ["0", "1"],
+            DataFrame(data=[[2_000, 3_000], [5_000, 6_000]], columns=["0", "1"]),
+        ),
     ],
 )
 def test_usecols_with_integer_like_header(all_parsers, usecols, expected):
@@ -249,7 +252,7 @@ def test_usecols_with_parse_dates2(all_parsers):
         ],
         name="date",
     )
-    cols = {"values": [1032.43, 1042.54, 1051.65]}
+    cols = {"values": [1_032.43, 1_042.54, 1_051.65]}
     expected = DataFrame(cols, index=index)
 
     result = parser.read_csv(
@@ -349,7 +352,11 @@ def test_usecols_with_unicode_strings(all_parsers):
     parser = all_parsers
 
     exp_data = {
-        "AAA": {0: 0.056674972999999997, 1: 2.6132309819999997, 2: 3.5689350380000002},
+        "AAA": {
+            0: 0.056_674_972_999_999_997,
+            1: 2.6_132_309_819_999_997,
+            2: 3.5_689_350_380_000_002,
+        },
         "BBB": {0: 8, 1: 2, 2: 7},
     }
     expected = DataFrame(exp_data)
@@ -367,7 +374,11 @@ def test_usecols_with_single_byte_unicode_strings(all_parsers):
     parser = all_parsers
 
     exp_data = {
-        "A": {0: 0.056674972999999997, 1: 2.6132309819999997, 2: 3.5689350380000002},
+        "A": {
+            0: 0.056_674_972_999_999_997,
+            1: 2.6_132_309_819_999_997,
+            2: 3.5_689_350_380_000_002,
+        },
         "B": {0: 8, 1: 2, 2: 7},
     }
     expected = DataFrame(exp_data)
@@ -397,7 +408,11 @@ def test_usecols_with_multi_byte_characters(all_parsers, usecols):
     parser = all_parsers
 
     exp_data = {
-        "あああ": {0: 0.056674972999999997, 1: 2.6132309819999997, 2: 3.5689350380000002},
+        "あああ": {
+            0: 0.056_674_972_999_999_997,
+            1: 2.6_132_309_819_999_997,
+            2: 3.5_689_350_380_000_002,
+        },
         "いい": {0: 8, 1: 2, 2: 7},
     }
     expected = DataFrame(exp_data)
@@ -434,9 +449,9 @@ def test_np_array_usecols(all_parsers):
             DataFrame(
                 {
                     "AaA": {
-                        0: 0.056674972999999997,
-                        1: 2.6132309819999997,
-                        2: 3.5689350380000002,
+                        0: 0.056_674_972_999_999_997,
+                        1: 2.6_132_309_819_999_997,
+                        2: 3.5_689_350_380_000_002,
                     },
                     "bBb": {0: 8, 1: 2, 2: 7},
                     "ddd": {0: "a", 1: "b", 2: "a"},
diff --git a/pandas/tests/io/pytables/test_compat.py b/pandas/tests/io/pytables/test_compat.py
index 1e320e12a4a53..a82e21532eddb 100644
--- a/pandas/tests/io/pytables/test_compat.py
+++ b/pandas/tests/io/pytables/test_compat.py
@@ -9,21 +9,22 @@
 
 @pytest.fixture
 def pytables_hdf5_file():
-    """Use PyTables to create a simple HDF5 file."""
-
+    """
+    Use PyTables to create a simple HDF5 file.
+    """
     table_schema = {
         "c0": tables.Time64Col(pos=0),
         "c1": tables.StringCol(5, pos=1),
         "c2": tables.Int64Col(pos=2),
     }
 
-    t0 = 1561105000.0
+    t0 = 1_561_105_000.0
 
     testsamples = [
         {"c0": t0, "c1": "aaaaa", "c2": 1},
         {"c0": t0 + 1, "c1": "bbbbb", "c2": 2},
         {"c0": t0 + 2, "c1": "ccccc", "c2": 10 ** 5},
-        {"c0": t0 + 3, "c1": "ddddd", "c2": 4294967295},
+        {"c0": t0 + 3, "c1": "ddddd", "c2": 4_294_967_295},
     ]
 
     objname = "pandas_test_timeseries"

From eddfb8f1c521769176359364bbfedaf937361b6d Mon Sep 17 00:00:00 2001
From: MomIsBestFriend <>
Date: Tue, 10 Dec 2019 13:28:59 +0200
Subject: [PATCH 2/3] Decimal

---
 pandas/core/arrays/categorical.py      |  2 +-
 pandas/core/arrays/timedeltas.py       |  2 +-
 pandas/core/base.py                    |  2 +-
 pandas/tests/io/formats/test_format.py | 76 +++++++++++++-------------
 pandas/tests/io/parser/test_usecols.py | 33 +++--------
 5 files changed, 50 insertions(+), 65 deletions(-)

diff --git a/pandas/core/arrays/categorical.py b/pandas/core/arrays/categorical.py
index 439f36c960617..7170aec3820a8 100644
--- a/pandas/core/arrays/categorical.py
+++ b/pandas/core/arrays/categorical.py
@@ -299,7 +299,7 @@ class Categorical(ExtensionArray, PandasObject):
 
     # For comparisons, so that numpy uses our implementation if the compare
     # ops, which raise
-    __array_priority__ = 1_000
+    __array_priority__ = 1000
     _dtype = CategoricalDtype(ordered=False)
     # tolist is not actually deprecated, just suppressed in the __dir__
     _deprecations = PandasObject._deprecations | frozenset(["tolist", "itemsize"])
diff --git a/pandas/core/arrays/timedeltas.py b/pandas/core/arrays/timedeltas.py
index 03699398fddf5..56c4a1a201eeb 100644
--- a/pandas/core/arrays/timedeltas.py
+++ b/pandas/core/arrays/timedeltas.py
@@ -157,7 +157,7 @@ class TimedeltaArray(dtl.DatetimeLikeArrayMixin, dtl.TimelikeOps):
 
     _typ = "timedeltaarray"
     _scalar_type = Timedelta
-    __array_priority__ = 1_000
+    __array_priority__ = 1000
     # define my properties & methods for delegation
     _other_ops: List[str] = []
     _bool_ops: List[str] = []
diff --git a/pandas/core/base.py b/pandas/core/base.py
index e52e66a07eb6d..88b8fe405c8e4 100644
--- a/pandas/core/base.py
+++ b/pandas/core/base.py
@@ -618,7 +618,7 @@ class IndexOpsMixin:
     """
 
     # ndarray compatibility
-    __array_priority__ = 1_000
+    __array_priority__ = 1000
     _deprecations: FrozenSet[str] = frozenset(
         ["tolist", "item"]  # tolist is not deprecated, just suppressed in the __dir__
     )
diff --git a/pandas/tests/io/formats/test_format.py b/pandas/tests/io/formats/test_format.py
index de0fcb2b06960..defa99313d73a 100644
--- a/pandas/tests/io/formats/test_format.py
+++ b/pandas/tests/io/formats/test_format.py
@@ -286,11 +286,11 @@ def test_repr_chop_threshold_column_below(self):
             )
 
     def test_repr_obeys_max_seq_limit(self):
-        with option_context("display.max_seq_items", 2_000):
-            assert len(printing.pprint_thing(list(range(1_000)))) > 1_000
+        with option_context("display.max_seq_items", 2000):
+            assert len(printing.pprint_thing(list(range(1000)))) > 1000
 
         with option_context("display.max_seq_items", 5):
-            assert len(printing.pprint_thing(list(range(1_000)))) < 100
+            assert len(printing.pprint_thing(list(range(1000)))) < 100
 
     def test_repr_set(self):
         assert printing.pprint_thing({1}) == "{1}"
@@ -354,10 +354,10 @@ def test_expand_frame_repr(self):
     def test_repr_non_interactive(self):
         # in non interactive mode, there can be no dependency on the
         # result of terminal auto size detection
-        df = DataFrame("hello", index=range(1_000), columns=range(5))
+        df = DataFrame("hello", index=range(1000), columns=range(5))
 
         with option_context(
-            "mode.sim_interactive", False, "display.width", 0, "display.max_rows", 5_000
+            "mode.sim_interactive", False, "display.width", 0, "display.max_rows", 5000
         ):
             assert not has_truncated_repr(df)
             assert not has_expanded_repr(df)
@@ -1339,7 +1339,7 @@ def test_wide_repr_wide_long_columns(self):
             assert "ddddd" in result
 
     def test_long_series(self):
-        n = 1_000
+        n = 1000
         s = Series(
             np.random.randint(-50, 50, n),
             index=["s{x:04d}".format(x=x) for x in range(n)],
@@ -1545,7 +1545,7 @@ def test_to_string_float_formatting(self):
         )
 
         df = DataFrame(
-            {"x": [0, 0.25, 3_456.000, 12e45, 1.64e6, 1.7e8, 1.253_456, np.pi, -1e6]}
+            {"x": [0, 0.25, 3456.000, 12e45, 1.64e6, 1.7e8, 1.253_456, np.pi, -1e6]}
         )
 
         df_s = df.to_string()
@@ -1566,7 +1566,7 @@ def test_to_string_float_formatting(self):
             )
         assert df_s == expected
 
-        df = DataFrame({"x": [3_234, 0.253]})
+        df = DataFrame({"x": [3234, 0.253]})
         df_s = df.to_string()
 
         expected = "          x\n0  3234.000\n1     0.253"
@@ -1636,9 +1636,9 @@ def test_to_string_complex_float_formatting(self):
             df = DataFrame(
                 {
                     "x": [
-                        (0.4_467_846_931_321_966 + 0.0_715_185_102_060_818j),
-                        (0.2_739_442_392_974_528 + 0.23_515_228_785_438_969j),
-                        (0.26_974_928_742_135_185 + 0.3_250_604_054_898_979j),
+                        (0.4467846931321966 + 0.0715185102060818j),
+                        (0.2739442392974528 + 0.23515228785438969j),
+                        (0.26974928742135185 + 0.3250604054898979j),
                         (-1j),
                     ]
                 }
@@ -1690,7 +1690,7 @@ def test_to_string_index_formatter(self):
 
     def test_to_string_left_justify_cols(self):
         tm.reset_display_options()
-        df = DataFrame({"x": [3_234, 0.253]})
+        df = DataFrame({"x": [3234, 0.253]})
         df_s = df.to_string(justify="left")
         expected = "   x       \n0  3234.000\n1     0.253"
         assert df_s == expected
@@ -1699,7 +1699,7 @@ def test_to_string_format_na(self):
         tm.reset_display_options()
         df = DataFrame(
             {
-                "A": [np.nan, -1, -2.1_234, 3, 4],
+                "A": [np.nan, -1, -2.1234, 3, 4],
                 "B": [np.nan, "foo", "foooo", "fooooo", "bar"],
             }
         )
@@ -1738,7 +1738,7 @@ def test_to_string_format_inf(self):
         tm.reset_display_options()
         df = DataFrame(
             {
-                "A": [-np.inf, np.inf, -1, -2.1_234, 3, 4],
+                "A": [-np.inf, np.inf, -1, -2.1234, 3, 4],
                 "B": [-np.inf, np.inf, "foo", "foooo", "fooooo", "bar"],
             }
         )
@@ -2076,11 +2076,11 @@ def __getitem__(self, key):
 
     def test_float_trim_zeros(self):
         vals = [
-            2.08_430_917_305e10,
-            3.52_205_017_305e10,
-            2.30_674_817_305e10,
-            2.03_954_217_305e10,
-            5.59_897_817_305e10,
+            2.08430917305e10,
+            3.52205017305e10,
+            2.30674817305e10,
+            2.03954217305e10,
+            5.59897817305e10,
         ]
         skip = True
         for line in repr(DataFrame({"A": vals})).split("\n")[:-2]:
@@ -2140,7 +2140,7 @@ def test_repr_unicode(self):
         s = Series(["\u03c3"] * 10)
         repr(s)
 
-        a = Series(["\u05d0"] * 1_000)
+        a = Series(["\u05d0"] * 1000)
         a.name = "title1"
         repr(a)
 
@@ -2202,7 +2202,7 @@ def test_to_string_mixed(self):
         assert result == expected
 
     def test_to_string_float_na_spacing(self):
-        s = Series([0.0, 1.5_678, 2.0, -3.0, 4.0])
+        s = Series([0.0, 1.5678, 2.0, -3.0, 4.0])
         s[::2] = np.nan
 
         result = s.to_string()
@@ -2261,7 +2261,7 @@ def test_east_asian_unicode_series(self):
         idx = pd.MultiIndex.from_tuples(
             [("あ", "いい"), ("う", "え"), ("おおお", "かかかか"), ("き", "くく")]
         )
-        s = Series([1, 22, 3_333, 44_444], index=idx)
+        s = Series([1, 22, 3333, 44_444], index=idx)
         expected = (
             "あ    いい          1\n"
             "う    え          22\n"
@@ -2271,7 +2271,7 @@ def test_east_asian_unicode_series(self):
         assert repr(s) == expected
 
         # object dtype, shorter than unicode repr
-        s = Series([1, 22, 3_333, 44_444], index=[1, "AB", np.nan, "あああ"])
+        s = Series([1, 22, 3333, 44_444], index=[1, "AB", np.nan, "あああ"])
         expected = (
             "1          1\nAB        22\nNaN     3333\nあああ    44444\ndtype: int64"
         )
@@ -2279,7 +2279,7 @@ def test_east_asian_unicode_series(self):
 
         # object dtype, longer than unicode repr
         s = Series(
-            [1, 22, 3_333, 44_444], index=[1, "AB", pd.Timestamp("2011-01-01"), "あああ"]
+            [1, 22, 3333, 44_444], index=[1, "AB", pd.Timestamp("2011-01-01"), "あああ"]
         )
         expected = (
             "1                          1\n"
@@ -2356,7 +2356,7 @@ def test_east_asian_unicode_series(self):
             idx = pd.MultiIndex.from_tuples(
                 [("あ", "いい"), ("う", "え"), ("おおお", "かかかか"), ("き", "くく")]
             )
-            s = Series([1, 22, 3_333, 44_444], index=idx)
+            s = Series([1, 22, 3333, 44_444], index=idx)
             expected = (
                 "あ      いい            1\n"
                 "う      え             22\n"
@@ -2367,7 +2367,7 @@ def test_east_asian_unicode_series(self):
             assert repr(s) == expected
 
             # object dtype, shorter than unicode repr
-            s = Series([1, 22, 3_333, 44_444], index=[1, "AB", np.nan, "あああ"])
+            s = Series([1, 22, 3333, 44_444], index=[1, "AB", np.nan, "あああ"])
             expected = (
                 "1             1\nAB           22\nNaN        3333\n"
                 "あああ    44444\ndtype: int64"
@@ -2376,7 +2376,7 @@ def test_east_asian_unicode_series(self):
 
             # object dtype, longer than unicode repr
             s = Series(
-                [1, 22, 3_333, 44_444],
+                [1, 22, 3333, 44_444],
                 index=[1, "AB", pd.Timestamp("2011-01-01"), "あああ"],
             )
             expected = (
@@ -2420,11 +2420,11 @@ def test_east_asian_unicode_series(self):
 
     def test_float_trim_zeros(self):
         vals = [
-            2.08_430_917_305e10,
-            3.52_205_017_305e10,
-            2.30_674_817_305e10,
-            2.03_954_217_305e10,
-            5.59_897_817_305e10,
+            2.08430917305e10,
+            3.52205017305e10,
+            2.30674817305e10,
+            2.03954217305e10,
+            5.59897817305e10,
         ]
         for line in repr(Series(vals)).split("\n"):
             if line.startswith("dtype:"):
@@ -2624,7 +2624,7 @@ def test_max_multi_index_display(self):
 
     # Make sure #8532 is fixed
     def test_consistent_format(self):
-        s = pd.Series([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.9_999, 1, 1] * 10)
+        s = pd.Series([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.9999, 1, 1] * 10)
         with option_context("display.max_rows", 10, "display.show_dimensions", False):
             res = repr(s)
         exp = (
@@ -2824,19 +2824,19 @@ def test_output_significant_digits(self):
                     "col1": [
                         9.999e-8,
                         1e-7,
-                        1.0_001e-7,
+                        1.0001e-7,
                         2e-7,
                         4.999e-7,
                         5e-7,
-                        5.0_001e-7,
+                        5.0001e-7,
                         6e-7,
                         9.999e-7,
                         1e-6,
-                        1.0_001e-6,
+                        1.0001e-6,
                         2e-6,
                         4.999e-6,
                         5e-6,
-                        5.0_001e-6,
+                        5.0001e-6,
                         6e-6,
                     ]
                 }
@@ -2891,7 +2891,7 @@ def test_too_long(self):
         with pd.option_context("display.precision", 4):
             # need both a number > 1e6 and something that normally formats to
             # having length > display.precision + 6
-            df = pd.DataFrame(dict(x=[12_345.6_789]))
+            df = pd.DataFrame(dict(x=[12_345.6789]))
             assert str(df) == "            x\n0  12345.6789"
             df = pd.DataFrame(dict(x=[2e6]))
             assert str(df) == "           x\n0  2000000.0"
diff --git a/pandas/tests/io/parser/test_usecols.py b/pandas/tests/io/parser/test_usecols.py
index 741ef90cb3153..b6b370295bac7 100644
--- a/pandas/tests/io/parser/test_usecols.py
+++ b/pandas/tests/io/parser/test_usecols.py
@@ -197,12 +197,9 @@ def test_usecols_with_whitespace(all_parsers):
     "usecols,expected",
     [
         # Column selection by index.
-        ([0, 1], DataFrame(data=[[1_000, 2_000], [4_000, 5_000]], columns=["2", "0"])),
+        ([0, 1], DataFrame(data=[[1000, 2000], [4000, 5000]], columns=["2", "0"])),
         # Column selection by name.
-        (
-            ["0", "1"],
-            DataFrame(data=[[2_000, 3_000], [5_000, 6_000]], columns=["0", "1"]),
-        ),
+        (["0", "1"], DataFrame(data=[[2000, 3000], [5000, 6000]], columns=["0", "1"]),),
     ],
 )
 def test_usecols_with_integer_like_header(all_parsers, usecols, expected):
@@ -252,7 +249,7 @@ def test_usecols_with_parse_dates2(all_parsers):
         ],
         name="date",
     )
-    cols = {"values": [1_032.43, 1_042.54, 1_051.65]}
+    cols = {"values": [1032.43, 1042.54, 1051.65]}
     expected = DataFrame(cols, index=index)
 
     result = parser.read_csv(
@@ -352,11 +349,7 @@ def test_usecols_with_unicode_strings(all_parsers):
     parser = all_parsers
 
     exp_data = {
-        "AAA": {
-            0: 0.056_674_972_999_999_997,
-            1: 2.6_132_309_819_999_997,
-            2: 3.5_689_350_380_000_002,
-        },
+        "AAA": {0: 0.056674972999999997, 1: 2.6132309819999997, 2: 3.5689350380000002,},
         "BBB": {0: 8, 1: 2, 2: 7},
     }
     expected = DataFrame(exp_data)
@@ -374,11 +367,7 @@ def test_usecols_with_single_byte_unicode_strings(all_parsers):
     parser = all_parsers
 
     exp_data = {
-        "A": {
-            0: 0.056_674_972_999_999_997,
-            1: 2.6_132_309_819_999_997,
-            2: 3.5_689_350_380_000_002,
-        },
+        "A": {0: 0.056674972999999997, 1: 2.6132309819999997, 2: 3.5689350380000002,},
         "B": {0: 8, 1: 2, 2: 7},
     }
     expected = DataFrame(exp_data)
@@ -408,11 +397,7 @@ def test_usecols_with_multi_byte_characters(all_parsers, usecols):
     parser = all_parsers
 
     exp_data = {
-        "あああ": {
-            0: 0.056_674_972_999_999_997,
-            1: 2.6_132_309_819_999_997,
-            2: 3.5_689_350_380_000_002,
-        },
+        "あああ": {0: 0.056674972999999997, 1: 2.6132309819999997, 2: 3.5689350380000002,},
         "いい": {0: 8, 1: 2, 2: 7},
     }
     expected = DataFrame(exp_data)
@@ -449,9 +434,9 @@ def test_np_array_usecols(all_parsers):
             DataFrame(
                 {
                     "AaA": {
-                        0: 0.056_674_972_999_999_997,
-                        1: 2.6_132_309_819_999_997,
-                        2: 3.5_689_350_380_000_002,
+                        0: 0.056674972999999997,
+                        1: 2.6132309819999997,
+                        2: 3.5689350380000002,
                     },
                     "bBb": {0: 8, 1: 2, 2: 7},
                     "ddd": {0: "a", 1: "b", 2: "a"},

From 35a430109f96da0e99f177325253bb932f2937b1 Mon Sep 17 00:00:00 2001
From: MomIsBestFriend <>
Date: Tue, 10 Dec 2019 13:46:55 +0200
Subject: [PATCH 3/3] Less than 7 digits

---
 pandas/core/computation/align.py       |  2 +-
 pandas/tests/io/formats/test_format.py | 42 +++++++++++++-------------
 pandas/tests/io/parser/test_usecols.py |  6 ++--
 3 files changed, 25 insertions(+), 25 deletions(-)

diff --git a/pandas/core/computation/align.py b/pandas/core/computation/align.py
index bf340783098c5..57348ad3b81a0 100644
--- a/pandas/core/computation/align.py
+++ b/pandas/core/computation/align.py
@@ -100,7 +100,7 @@ def _align_core(terms):
                 reindexer_size = len(reindexer)
 
                 ordm = np.log10(max(1, abs(reindexer_size - term_axis_size)))
-                if ordm >= 1 and reindexer_size >= 10_000:
+                if ordm >= 1 and reindexer_size >= 10000:
                     w = (
                         f"Alignment difference on axis {axis} is larger "
                         f"than an order of magnitude on term {repr(terms[i].name)}, "
diff --git a/pandas/tests/io/formats/test_format.py b/pandas/tests/io/formats/test_format.py
index defa99313d73a..6fd813c086982 100644
--- a/pandas/tests/io/formats/test_format.py
+++ b/pandas/tests/io/formats/test_format.py
@@ -233,7 +233,7 @@ def test_repr_truncation(self):
                 else:
                     assert "..." not in line
 
-        with option_context("display.max_colwidth", 999_999):
+        with option_context("display.max_colwidth", 999999):
             assert "..." not in repr(df)
 
         with option_context("display.max_colwidth", max_len + 2):
@@ -408,10 +408,10 @@ def test_repr_truncation_column_size(self):
         # determine size of truncation (...) column
         df = pd.DataFrame(
             {
-                "a": [108_480, 30_830],
-                "b": [12_345, 12_345],
-                "c": [12_345, 12_345],
-                "d": [12_345, 12_345],
+                "a": [108480, 30830],
+                "b": [12345, 12345],
+                "c": [12345, 12345],
+                "d": [12345, 12345],
                 "e": ["a" * 50] * 2,
             }
         )
@@ -719,7 +719,7 @@ def test_east_asian_unicode_false(self):
 
         # mid col
         df = DataFrame(
-            {"a": ["あ", "いいい", "う", "ええええええ"], "b": [1, 222, 33_333, 4]},
+            {"a": ["あ", "いいい", "う", "ええええええ"], "b": [1, 222, 33333, 4]},
             index=["a", "bb", "c", "ddd"],
         )
         expected = (
@@ -755,7 +755,7 @@ def test_east_asian_unicode_false(self):
 
         # column name
         df = DataFrame(
-            {"b": ["あ", "いいい", "う", "ええええええ"], "あああああ": [1, 222, 33_333, 4]},
+            {"b": ["あ", "いいい", "う", "ええええええ"], "あああああ": [1, 222, 33333, 4]},
             index=["a", "bb", "c", "ddd"],
         )
         expected = (
@@ -857,7 +857,7 @@ def test_east_asian_unicode_true(self):
 
             # mid col
             df = DataFrame(
-                {"a": ["あ", "いいい", "う", "ええええええ"], "b": [1, 222, 33_333, 4]},
+                {"a": ["あ", "いいい", "う", "ええええええ"], "b": [1, 222, 33333, 4]},
                 index=["a", "bb", "c", "ddd"],
             )
             expected = (
@@ -869,7 +869,7 @@ def test_east_asian_unicode_true(self):
 
             # last col
             df = DataFrame(
-                {"a": [1, 222, 33_333, 4], "b": ["あ", "いいい", "う", "ええええええ"]},
+                {"a": [1, 222, 33333, 4], "b": ["あ", "いいい", "う", "ええええええ"]},
                 index=["a", "bb", "c", "ddd"],
             )
             expected = (
@@ -895,7 +895,7 @@ def test_east_asian_unicode_true(self):
 
             # column name
             df = DataFrame(
-                {"b": ["あ", "いいい", "う", "ええええええ"], "あああああ": [1, 222, 33_333, 4]},
+                {"b": ["あ", "いいい", "う", "ええええええ"], "あああああ": [1, 222, 33333, 4]},
                 index=["a", "bb", "c", "ddd"],
             )
             expected = (
@@ -1002,7 +1002,7 @@ def test_east_asian_unicode_true(self):
 
             # ambiguous unicode
             df = DataFrame(
-                {"b": ["あ", "いいい", "¡¡", "ええええええ"], "あああああ": [1, 222, 33_333, 4]},
+                {"b": ["あ", "いいい", "¡¡", "ええええええ"], "あああああ": [1, 222, 33333, 4]},
                 index=["a", "bb", "c", "¡¡¡"],
             )
             expected = (
@@ -1545,7 +1545,7 @@ def test_to_string_float_formatting(self):
         )
 
         df = DataFrame(
-            {"x": [0, 0.25, 3456.000, 12e45, 1.64e6, 1.7e8, 1.253_456, np.pi, -1e6]}
+            {"x": [0, 0.25, 3456.000, 12e45, 1.64e6, 1.7e8, 1.253456, np.pi, -1e6]}
         )
 
         df_s = df.to_string()
@@ -1587,7 +1587,7 @@ def test_to_string_float_formatting(self):
     def test_to_string_float_format_no_fixed_width(self):
 
         # GH 21625
-        df = DataFrame({"x": [0.19_999]})
+        df = DataFrame({"x": [0.19999]})
         expected = "      x\n0 0.200"
         assert df.to_string(float_format="%.3f") == expected
 
@@ -2261,7 +2261,7 @@ def test_east_asian_unicode_series(self):
         idx = pd.MultiIndex.from_tuples(
             [("あ", "いい"), ("う", "え"), ("おおお", "かかかか"), ("き", "くく")]
         )
-        s = Series([1, 22, 3333, 44_444], index=idx)
+        s = Series([1, 22, 3333, 44444], index=idx)
         expected = (
             "あ    いい          1\n"
             "う    え          22\n"
@@ -2271,7 +2271,7 @@ def test_east_asian_unicode_series(self):
         assert repr(s) == expected
 
         # object dtype, shorter than unicode repr
-        s = Series([1, 22, 3333, 44_444], index=[1, "AB", np.nan, "あああ"])
+        s = Series([1, 22, 3333, 44444], index=[1, "AB", np.nan, "あああ"])
         expected = (
             "1          1\nAB        22\nNaN     3333\nあああ    44444\ndtype: int64"
         )
@@ -2279,7 +2279,7 @@ def test_east_asian_unicode_series(self):
 
         # object dtype, longer than unicode repr
         s = Series(
-            [1, 22, 3333, 44_444], index=[1, "AB", pd.Timestamp("2011-01-01"), "あああ"]
+            [1, 22, 3333, 44444], index=[1, "AB", pd.Timestamp("2011-01-01"), "あああ"]
         )
         expected = (
             "1                          1\n"
@@ -2356,7 +2356,7 @@ def test_east_asian_unicode_series(self):
             idx = pd.MultiIndex.from_tuples(
                 [("あ", "いい"), ("う", "え"), ("おおお", "かかかか"), ("き", "くく")]
             )
-            s = Series([1, 22, 3333, 44_444], index=idx)
+            s = Series([1, 22, 3333, 44444], index=idx)
             expected = (
                 "あ      いい            1\n"
                 "う      え             22\n"
@@ -2367,7 +2367,7 @@ def test_east_asian_unicode_series(self):
             assert repr(s) == expected
 
             # object dtype, shorter than unicode repr
-            s = Series([1, 22, 3333, 44_444], index=[1, "AB", np.nan, "あああ"])
+            s = Series([1, 22, 3333, 44444], index=[1, "AB", np.nan, "あああ"])
             expected = (
                 "1             1\nAB           22\nNaN        3333\n"
                 "あああ    44444\ndtype: int64"
@@ -2376,7 +2376,7 @@ def test_east_asian_unicode_series(self):
 
             # object dtype, longer than unicode repr
             s = Series(
-                [1, 22, 3333, 44_444],
+                [1, 22, 3333, 44444],
                 index=[1, "AB", pd.Timestamp("2011-01-01"), "あああ"],
             )
             expected = (
@@ -2479,7 +2479,7 @@ def test_timedelta64(self):
 
         from datetime import datetime, timedelta
 
-        Series(np.array([11_00, 20], dtype="timedelta64[ns]")).to_string()
+        Series(np.array([1100, 20], dtype="timedelta64[ns]")).to_string()
 
         s = Series(date_range("2012-1-1", periods=3, freq="D"))
 
@@ -2891,7 +2891,7 @@ def test_too_long(self):
         with pd.option_context("display.precision", 4):
             # need both a number > 1e6 and something that normally formats to
             # having length > display.precision + 6
-            df = pd.DataFrame(dict(x=[12_345.6789]))
+            df = pd.DataFrame(dict(x=[12345.6789]))
             assert str(df) == "            x\n0  12345.6789"
             df = pd.DataFrame(dict(x=[2e6]))
             assert str(df) == "           x\n0  2000000.0"
diff --git a/pandas/tests/io/parser/test_usecols.py b/pandas/tests/io/parser/test_usecols.py
index b6b370295bac7..539fdf2470c51 100644
--- a/pandas/tests/io/parser/test_usecols.py
+++ b/pandas/tests/io/parser/test_usecols.py
@@ -349,7 +349,7 @@ def test_usecols_with_unicode_strings(all_parsers):
     parser = all_parsers
 
     exp_data = {
-        "AAA": {0: 0.056674972999999997, 1: 2.6132309819999997, 2: 3.5689350380000002,},
+        "AAA": {0: 0.056674972999999997, 1: 2.6132309819999997, 2: 3.5689350380000002},
         "BBB": {0: 8, 1: 2, 2: 7},
     }
     expected = DataFrame(exp_data)
@@ -367,7 +367,7 @@ def test_usecols_with_single_byte_unicode_strings(all_parsers):
     parser = all_parsers
 
     exp_data = {
-        "A": {0: 0.056674972999999997, 1: 2.6132309819999997, 2: 3.5689350380000002,},
+        "A": {0: 0.056674972999999997, 1: 2.6132309819999997, 2: 3.5689350380000002},
         "B": {0: 8, 1: 2, 2: 7},
     }
     expected = DataFrame(exp_data)
@@ -397,7 +397,7 @@ def test_usecols_with_multi_byte_characters(all_parsers, usecols):
     parser = all_parsers
 
     exp_data = {
-        "あああ": {0: 0.056674972999999997, 1: 2.6132309819999997, 2: 3.5689350380000002,},
+        "あああ": {0: 0.056674972999999997, 1: 2.6132309819999997, 2: 3.5689350380000002},
         "いい": {0: 8, 1: 2, 2: 7},
     }
     expected = DataFrame(exp_data)