STYLE: inconsistent namespace (io)

Author: AA-Turner

pandas/tests/io/excel/test_writers.py

@@ -275,7 +275,7 @@ def test_read_excel_parse_dates(self, ext):
 
     def test_multiindex_interval_datetimes(self, ext):
         # GH 30986
-        midx = pd.MultiIndex.from_arrays(
+        midx = MultiIndex.from_arrays(
             [
                 range(4),
                 pd.interval_range(
@@ -289,7 +289,7 @@ def test_multiindex_interval_datetimes(self, ext):
             result = pd.read_excel(pth, index_col=[0, 1])
         expected = DataFrame(
             range(4),
-            pd.MultiIndex.from_arrays(
+            MultiIndex.from_arrays(
                 [
                     range(4),
                     [

pandas/tests/io/formats/test_format.py

@@ -249,7 +249,7 @@ def test_repr_deprecation_negative_int(self):
 
     def test_repr_chop_threshold(self):
         df = DataFrame([[0.1, 0.5], [0.5, -0.1]])
-        pd.reset_option("display.chop_threshold")  # default None
+        reset_option("display.chop_threshold")  # default None
         assert repr(df) == "     0    1\n0  0.1  0.5\n1  0.5 -0.1"
 
         with option_context("display.chop_threshold", 0.2):
@@ -382,7 +382,7 @@ def test_repr_truncates_terminal_size(self, monkeypatch):
         )
 
         index = range(5)
-        columns = pd.MultiIndex.from_tuples(
+        columns = MultiIndex.from_tuples(
             [
                 ("This is a long title with > 37 chars.", "cat"),
                 ("This is a loooooonger title with > 43 chars.", "dog"),
@@ -689,7 +689,7 @@ def test_east_asian_unicode_false(self):
         assert repr(df) == expected
 
         # MultiIndex
-        idx = pd.MultiIndex.from_tuples(
+        idx = MultiIndex.from_tuples(
             [("あ", "いい"), ("う", "え"), ("おおお", "かかかか"), ("き", "くく")]
         )
         df = DataFrame(
@@ -833,7 +833,7 @@ def test_east_asian_unicode_true(self):
             assert repr(df) == expected
 
             # MultiIndex
-            idx = pd.MultiIndex.from_tuples(
+            idx = MultiIndex.from_tuples(
                 [("あ", "いい"), ("う", "え"), ("おおお", "かかかか"), ("き", "くく")]
             )
             df = DataFrame(
@@ -1002,14 +1002,14 @@ def test_truncate_with_different_dtypes(self):
             + [datetime.datetime(2012, 1, 3)] * 10
         )
 
-        with pd.option_context("display.max_rows", 8):
+        with option_context("display.max_rows", 8):
             result = str(s)
             assert "object" in result
 
         # 12045
         df = DataFrame({"text": ["some words"] + [None] * 9})
 
-        with pd.option_context("display.max_rows", 8, "display.max_columns", 3):
+        with option_context("display.max_rows", 8, "display.max_columns", 3):
             result = str(df)
             assert "None" in result
             assert "NaN" not in result
@@ -1026,9 +1026,7 @@ def test_truncate_with_different_dtypes_multiindex(self):
     def test_datetimelike_frame(self):
 
         # GH 12211
-        df = DataFrame(
-            {"date": [Timestamp("20130101").tz_localize("UTC")] + [pd.NaT] * 5}
-        )
+        df = DataFrame({"date": [Timestamp("20130101").tz_localize("UTC")] + [NaT] * 5})
 
         with option_context("display.max_rows", 5):
             result = str(df)
@@ -1037,7 +1035,7 @@ def test_datetimelike_frame(self):
             assert "..." in result
             assert "[6 rows x 1 columns]" in result
 
-        dts = [Timestamp("2011-01-01", tz="US/Eastern")] * 5 + [pd.NaT] * 5
+        dts = [Timestamp("2011-01-01", tz="US/Eastern")] * 5 + [NaT] * 5
         df = DataFrame({"dt": dts, "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]})
         with option_context("display.max_rows", 5):
             expected = (
@@ -1051,7 +1049,7 @@ def test_datetimelike_frame(self):
             )
             assert repr(df) == expected
 
-        dts = [pd.NaT] * 5 + [Timestamp("2011-01-01", tz="US/Eastern")] * 5
+        dts = [NaT] * 5 + [Timestamp("2011-01-01", tz="US/Eastern")] * 5
         df = DataFrame({"dt": dts, "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]})
         with option_context("display.max_rows", 5):
             expected = (
@@ -1117,7 +1115,7 @@ def test_unicode_problem_decoding_as_ascii(self):
 
     def test_string_repr_encoding(self, datapath):
         filepath = datapath("io", "parser", "data", "unicode_series.csv")
-        df = pd.read_csv(filepath, header=None, encoding="latin1")
+        df = read_csv(filepath, header=None, encoding="latin1")
         repr(df)
         repr(df[1])
 
@@ -1548,7 +1546,7 @@ def test_to_string_float_index(self):
 
     def test_to_string_complex_float_formatting(self):
         # GH #25514, 25745
-        with pd.option_context("display.precision", 5):
+        with option_context("display.precision", 5):
             df = DataFrame(
                 {
                     "x": [
@@ -1785,7 +1783,7 @@ def test_repr_html_mathjax(self):
         df = DataFrame([[1, 2], [3, 4]])
         assert "tex2jax_ignore" not in df._repr_html_()
 
-        with pd.option_context("display.html.use_mathjax", False):
+        with option_context("display.html.use_mathjax", False):
             assert "tex2jax_ignore" in df._repr_html_()
 
     def test_repr_html_wide(self):
@@ -2229,7 +2227,7 @@ def test_east_asian_unicode_series(self):
         assert repr(s) == expected
 
         # MultiIndex
-        idx = pd.MultiIndex.from_tuples(
+        idx = 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)
@@ -2324,7 +2322,7 @@ def test_east_asian_unicode_series(self):
             assert repr(s) == expected
 
             # MultiIndex
-            idx = pd.MultiIndex.from_tuples(
+            idx = 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)
@@ -2853,7 +2851,7 @@ def test_output_display_precision_trailing_zeroes(self):
         # Issue #20359: trimming zeros while there is no decimal point
 
         # Happens when display precision is set to zero
-        with pd.option_context("display.precision", 0):
+        with option_context("display.precision", 0):
             s = Series([840.0, 4200.0])
             expected_output = "0     840\n1    4200\ndtype: float64"
             assert str(s) == expected_output
@@ -2862,7 +2860,7 @@ def test_output_significant_digits(self):
         # Issue #9764
 
         # In case default display precision changes:
-        with pd.option_context("display.precision", 6):
+        with option_context("display.precision", 6):
             # DataFrame example from issue #9764
             d = DataFrame(
                 {
@@ -2933,7 +2931,7 @@ def test_output_significant_digits(self):
 
     def test_too_long(self):
         # GH 10451
-        with pd.option_context("display.precision", 4):
+        with option_context("display.precision", 4):
             # need both a number > 1e6 and something that normally formats to
             # having length > display.precision + 6
             df = DataFrame({"x": [12345.6789]})
@@ -3011,7 +3009,7 @@ def test_all(self):
 
 class TestTimedelta64Formatter:
     def test_days(self):
-        x = pd.to_timedelta(list(range(5)) + [pd.NaT], unit="D")
+        x = pd.to_timedelta(list(range(5)) + [NaT], unit="D")
         result = fmt.Timedelta64Formatter(x, box=True).get_result()
         assert result[0].strip() == "'0 days'"
         assert result[1].strip() == "'1 days'"
@@ -3027,25 +3025,25 @@ def test_days(self):
         assert result[0].strip() == "1 days"
 
     def test_days_neg(self):
-        x = pd.to_timedelta(list(range(5)) + [pd.NaT], unit="D")
+        x = pd.to_timedelta(list(range(5)) + [NaT], unit="D")
         result = fmt.Timedelta64Formatter(-x, box=True).get_result()
         assert result[0].strip() == "'0 days'"
         assert result[1].strip() == "'-1 days'"
 
     def test_subdays(self):
-        y = pd.to_timedelta(list(range(5)) + [pd.NaT], unit="s")
+        y = pd.to_timedelta(list(range(5)) + [NaT], unit="s")
         result = fmt.Timedelta64Formatter(y, box=True).get_result()
         assert result[0].strip() == "'0 days 00:00:00'"
         assert result[1].strip() == "'0 days 00:00:01'"
 
     def test_subdays_neg(self):
-        y = pd.to_timedelta(list(range(5)) + [pd.NaT], unit="s")
+        y = pd.to_timedelta(list(range(5)) + [NaT], unit="s")
         result = fmt.Timedelta64Formatter(-y, box=True).get_result()
         assert result[0].strip() == "'0 days 00:00:00'"
         assert result[1].strip() == "'-1 days +23:59:59'"
 
     def test_zero(self):
-        x = pd.to_timedelta(list(range(1)) + [pd.NaT], unit="D")
+        x = pd.to_timedelta(list(range(1)) + [NaT], unit="D")
         result = fmt.Timedelta64Formatter(x, box=True).get_result()
         assert result[0].strip() == "'0 days'"
 
@@ -3056,13 +3054,13 @@ def test_zero(self):
 
 class TestDatetime64Formatter:
     def test_mixed(self):
-        x = Series([datetime(2013, 1, 1), datetime(2013, 1, 1, 12), pd.NaT])
+        x = Series([datetime(2013, 1, 1), datetime(2013, 1, 1, 12), NaT])
         result = fmt.Datetime64Formatter(x).get_result()
         assert result[0].strip() == "2013-01-01 00:00:00"
         assert result[1].strip() == "2013-01-01 12:00:00"
 
     def test_dates(self):
-        x = Series([datetime(2013, 1, 1), datetime(2013, 1, 2), pd.NaT])
+        x = Series([datetime(2013, 1, 1), datetime(2013, 1, 2), NaT])
         result = fmt.Datetime64Formatter(x).get_result()
         assert result[0].strip() == "2013-01-01"
         assert result[1].strip() == "2013-01-02"
@@ -3137,32 +3135,32 @@ def format_func(x):
 
 class TestNaTFormatting:
     def test_repr(self):
-        assert repr(pd.NaT) == "NaT"
+        assert repr(NaT) == "NaT"
 
     def test_str(self):
-        assert str(pd.NaT) == "NaT"
+        assert str(NaT) == "NaT"
 
 
 class TestDatetimeIndexFormat:
     def test_datetime(self):
-        formatted = pd.to_datetime([datetime(2003, 1, 1, 12), pd.NaT]).format()
+        formatted = pd.to_datetime([datetime(2003, 1, 1, 12), NaT]).format()
         assert formatted[0] == "2003-01-01 12:00:00"
         assert formatted[1] == "NaT"
 
     def test_date(self):
-        formatted = pd.to_datetime([datetime(2003, 1, 1), pd.NaT]).format()
+        formatted = pd.to_datetime([datetime(2003, 1, 1), NaT]).format()
         assert formatted[0] == "2003-01-01"
         assert formatted[1] == "NaT"
 
     def test_date_tz(self):
         formatted = pd.to_datetime([datetime(2013, 1, 1)], utc=True).format()
         assert formatted[0] == "2013-01-01 00:00:00+00:00"
 
-        formatted = pd.to_datetime([datetime(2013, 1, 1), pd.NaT], utc=True).format()
+        formatted = pd.to_datetime([datetime(2013, 1, 1), NaT], utc=True).format()
         assert formatted[0] == "2013-01-01 00:00:00+00:00"
 
     def test_date_explicit_date_format(self):
-        formatted = pd.to_datetime([datetime(2003, 2, 1), pd.NaT]).format(
+        formatted = pd.to_datetime([datetime(2003, 2, 1), NaT]).format(
             date_format="%m-%d-%Y", na_rep="UT"
         )
         assert formatted[0] == "02-01-2003"
@@ -3226,7 +3224,7 @@ def test_tz_dateutil(self):
 
     def test_nat_representations(self):
         for f in (str, repr, methodcaller("isoformat")):
-            assert f(pd.NaT) == "NaT"
+            assert f(NaT) == "NaT"
 
 
 def test_format_percentiles():

pandas/tests/io/formats/test_to_csv.py

@@ -326,7 +326,7 @@ def test_to_csv_multi_index(self):
             ),
         ],
     )
-    @pytest.mark.parametrize("klass", [pd.DataFrame, pd.Series])
+    @pytest.mark.parametrize("klass", [DataFrame, pd.Series])
     def test_to_csv_single_level_multi_index(self, ind, expected, klass):
         # see gh-19589
         result = klass(pd.Series([1], ind, name="data")).to_csv(

pandas/tests/io/formats/test_to_html.py

@@ -763,7 +763,7 @@ def test_to_html_render_links(render_links, expected, datapath):
 def test_ignore_display_max_colwidth(method, expected, max_colwidth):
     # see gh-17004
     df = DataFrame([lorem_ipsum])
-    with pd.option_context("display.max_colwidth", max_colwidth):
+    with option_context("display.max_colwidth", max_colwidth):
         result = getattr(df, method)()
     expected = expected(max_colwidth)
     assert expected in result
@@ -782,7 +782,7 @@ def test_to_html_invalid_classes_type(classes):
 def test_to_html_round_column_headers():
     # GH 17280
     df = DataFrame([1], columns=[0.55555])
-    with pd.option_context("display.precision", 3):
+    with option_context("display.precision", 3):
         html = df.to_html(notebook=False)
         notebook = df.to_html(notebook=True)
     assert "0.55555" in html