CLN: remove more uses of compat.lrange

Author: topper-123

pandas/io/excel/_util.py

@@ -1,7 +1,5 @@
 import warnings
 
-from pandas.compat import lrange
-
 from pandas.core.dtypes.common import is_integer, is_list_like
 
 _writers = {}
@@ -112,7 +110,7 @@ def _range2cols(areas):
     for rng in areas.split(","):
         if ":" in rng:
             rng = rng.split(":")
-            cols.extend(lrange(_excel2num(rng[0]), _excel2num(rng[1]) + 1))
+            cols.extend(range(_excel2num(rng[0]), _excel2num(rng[1]) + 1))
         else:
             cols.append(_excel2num(rng))
 
@@ -141,7 +139,7 @@ def _maybe_convert_usecols(usecols):
                        "deprecated. Please pass in a list of int from "
                        "0 to `usecols` inclusive instead."),
                       FutureWarning, stacklevel=2)
-        return lrange(usecols + 1)
+        return list(range(usecols + 1))
 
     if isinstance(usecols, str):
         return _range2cols(usecols)

pandas/io/html.py

@@ -9,7 +9,7 @@
 import os
 import re
 
-from pandas.compat import lmap, lrange, raise_with_traceback
+from pandas.compat import lmap, raise_with_traceback
 from pandas.errors import AbstractMethodError, EmptyDataError
 
 from pandas.core.dtypes.common import is_list_like
@@ -101,7 +101,8 @@ def _get_skiprows(skiprows):
         A proper iterator to use to skip rows of a DataFrame.
     """
     if isinstance(skiprows, slice):
-        return lrange(skiprows.start or 0, skiprows.stop, skiprows.step or 1)
+        start, step = skiprows.start or 0, skiprows.step or 1
+        return list(range(start, skiprows.stop, step))
     elif isinstance(skiprows, numbers.Integral) or is_list_like(skiprows):
         return skiprows
     elif skiprows is None:

pandas/io/stata.py

@@ -23,7 +23,7 @@
 
 from pandas._libs.lib import infer_dtype
 from pandas._libs.writers import max_len_string_array
-from pandas.compat import lmap, lrange, lzip
+from pandas.compat import lmap, lzip
 from pandas.util._decorators import Appender, deprecate_kwarg
 
 from pandas.core.dtypes.common import (
@@ -874,7 +874,7 @@ def __init__(self):
                     (65530, np.int8)
                 ]
             )
-        self.TYPE_MAP = lrange(251) + list('bhlfd')
+        self.TYPE_MAP = list(range(251)) + list('bhlfd')
         self.TYPE_MAP_XML = \
             dict(
                 [

pandas/tests/groupby/test_apply.py

@@ -5,7 +5,7 @@
 import pytest
 
 import pandas as pd
-from pandas import DataFrame, Index, MultiIndex, Series, bdate_range, compat
+from pandas import DataFrame, Index, MultiIndex, Series, bdate_range
 from pandas.util import testing as tm
 
 
@@ -340,7 +340,7 @@ def f(group):
 def test_apply_chunk_view():
     # Low level tinkering could be unsafe, make sure not
     df = DataFrame({'key': [1, 1, 1, 2, 2, 2, 3, 3, 3],
-                    'value': compat.lrange(9)})
+                    'value': range(9)})
 
     result = df.groupby('key', group_keys=False).apply(lambda x: x[:2])
     expected = df.take([0, 1, 3, 4, 6, 7])
@@ -350,7 +350,7 @@ def test_apply_chunk_view():
 def test_apply_no_name_column_conflict():
     df = DataFrame({'name': [1, 1, 1, 1, 1, 1, 2, 2, 2, 2],
                     'name2': [0, 0, 0, 1, 1, 1, 0, 0, 1, 1],
-                    'value': compat.lrange(10)[::-1]})
+                    'value': list(range(10))[::-1]})
 
     # it works! #2605
     grouped = df.groupby(['name', 'name2'])

pandas/tests/groupby/test_grouping.py

@@ -3,8 +3,6 @@
 import numpy as np
 import pytest
 
-from pandas.compat import lrange
-
 import pandas as pd
 from pandas import (
     CategoricalIndex, DataFrame, Index, MultiIndex, Series, Timestamp,
@@ -481,7 +479,7 @@ def test_groupby_level(self, sort, mframe, df):
     def test_groupby_level_index_names(self):
         # GH4014 this used to raise ValueError since 'exp'>1 (in py2)
         df = DataFrame({'exp': ['A'] * 3 + ['B'] * 3,
-                        'var1': lrange(6), }).set_index('exp')
+                        'var1': range(6), }).set_index('exp')
         df.groupby(level='exp')
         msg = "level name foo is not the name of the index"
         with pytest.raises(ValueError, match=msg):

pandas/tests/groupby/test_nth.py

@@ -1,8 +1,6 @@
 import numpy as np
 import pytest
 
-from pandas.compat import lrange
-
 import pandas as pd
 from pandas import DataFrame, Index, MultiIndex, Series, Timestamp, isna
 from pandas.util.testing import (
@@ -84,9 +82,9 @@ def test_first_last_nth_dtypes(df_mixed_floats):
     assert_frame_equal(nth, expected)
 
     # GH 2763, first/last shifting dtypes
-    idx = lrange(10)
+    idx = list(range(10))
     idx.append(9)
-    s = Series(data=lrange(11), index=idx, name='IntCol')
+    s = Series(data=range(11), index=idx, name='IntCol')
     assert s.dtype == 'int64'
     f = s.groupby(level=0).first()
     assert f.dtype == 'int64'

pandas/tests/indexes/multi/test_sorting.py

@@ -1,7 +1,6 @@
 import numpy as np
 import pytest
 
-from pandas.compat import lrange
 from pandas.errors import PerformanceWarning, UnsortedIndexError
 
 import pandas as pd
@@ -97,7 +96,7 @@ def test_unsortedindex():
     mi = pd.MultiIndex.from_tuples([('z', 'a'), ('x', 'a'), ('y', 'b'),
                                     ('x', 'b'), ('y', 'a'), ('z', 'b')],
                                    names=['one', 'two'])
-    df = pd.DataFrame([[i, 10 * i] for i in lrange(6)], index=mi,
+    df = pd.DataFrame([[i, 10 * i] for i in range(6)], index=mi,
                       columns=['one', 'two'])
 
     # GH 16734: not sorted, but no real slicing

pandas/tests/test_multilevel.py

@@ -9,7 +9,7 @@
 import pytest
 import pytz
 
-from pandas.compat import lrange, lzip
+from pandas.compat import lzip
 
 from pandas.core.dtypes.common import is_float_dtype, is_integer_dtype
 
@@ -127,8 +127,8 @@ def test_series_constructor(self):
         multi = Series(1., index=[['a', 'a', 'b', 'b'], ['x', 'y', 'x', 'y']])
         assert isinstance(multi.index, MultiIndex)
 
-        multi = Series(lrange(4), index=[['a', 'a', 'b', 'b'],
-                                         ['x', 'y', 'x', 'y']])
+        multi = Series(range(4), index=[['a', 'a', 'b', 'b'],
+                                        ['x', 'y', 'x', 'y']])
         assert isinstance(multi.index, MultiIndex)
 
     def test_reindex_level(self):
@@ -1317,7 +1317,7 @@ def test_unicode_repr_level_names(self):
         index = MultiIndex.from_tuples([(0, 0), (1, 1)],
                                        names=['\u0394', 'i1'])
 
-        s = Series(lrange(2), index=index)
+        s = Series(range(2), index=index)
         df = DataFrame(np.random.randn(2, 4), index=index)
         repr(s)
         repr(df)

pandas/util/testing.py

@@ -22,7 +22,7 @@
     can_set_locale, get_locales, set_locale)
 
 from pandas._libs import testing as _testing
-from pandas.compat import lmap, lrange, lzip, raise_with_traceback
+from pandas.compat import lmap, lzip, raise_with_traceback
 
 from pandas.core.dtypes.common import (
     is_bool, is_categorical_dtype, is_datetime64_dtype, is_datetime64tz_dtype,
@@ -364,7 +364,7 @@ def randbool(size=(), p=0.5):
 
 RANDS_CHARS = np.array(list(string.ascii_letters + string.digits),
                        dtype=(np.str_, 1))
-RANDU_CHARS = np.array(list("".join(map(chr, lrange(1488, 1488 + 26))) +
+RANDU_CHARS = np.array(list("".join(map(chr, range(1488, 1488 + 26))) +
                             string.digits), dtype=(np.unicode_, 1))
 
 
@@ -1592,11 +1592,11 @@ def makeBoolIndex(k=10, name=None):
 
 
 def makeIntIndex(k=10, name=None):
-    return Index(lrange(k), name=name)
+    return Index(list(range(k)), name=name)
 
 
 def makeUIntIndex(k=10, name=None):
-    return Index([2**63 + i for i in lrange(k)], name=name)
+    return Index([2**63 + i for i in range(k)], name=name)
 
 
 def makeRangeIndex(k=10, name=None, **kwargs):