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Feb 26, 2021
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STYLE: inconsistent namespace (io, reshape) #40069

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4 changes: 2 additions & 2 deletions pandas/tests/io/excel/test_writers.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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(
Expand All @@ -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),
[
Expand Down
64 changes: 31 additions & 33 deletions pandas/tests/io/formats/test_format.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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):
Expand Down Expand Up @@ -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"),
Expand Down Expand Up @@ -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(
Expand Down Expand Up @@ -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(
Expand Down Expand Up @@ -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
Expand All @@ -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)
Expand All @@ -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 = (
Expand All @@ -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 = (
Expand Down Expand Up @@ -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])

Expand Down Expand Up @@ -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": [
Expand Down Expand Up @@ -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):
Expand Down Expand Up @@ -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)
Expand Down Expand Up @@ -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)
Expand Down Expand Up @@ -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
Expand All @@ -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(
{
Expand Down Expand Up @@ -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]})
Expand Down Expand Up @@ -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'"
Expand All @@ -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'"

Expand All @@ -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"
Expand Down Expand Up @@ -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"
Expand Down Expand Up @@ -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():
Expand Down
2 changes: 1 addition & 1 deletion pandas/tests/io/formats/test_to_csv.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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(
Expand Down
4 changes: 2 additions & 2 deletions pandas/tests/io/formats/test_to_html.py
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Expand Up @@ -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
Expand All @@ -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
Expand Down
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