def test_repr_unsortable(self):
# columns are not sortable
import warnings
warn_filters = warnings.filters
warnings.filterwarnings('ignore',
category=FutureWarning,
module=".*format")
unsortable = DataFrame(
{
'foo': [1] * 50,
datetime.today(): [1] * 50,
'bar': ['bar'] * 50,
datetime.today() + timedelta(1): ['bar'] * 50
},
index=np.arange(50))
repr(unsortable)
fmt.set_option('display.precision', 3, 'display.column_space', 10)
repr(self.frame)
fmt.set_option('display.max_rows', 10, 'display.max_columns', 2)
repr(self.frame)
fmt.set_option('display.max_rows', 1000, 'display.max_columns', 1000)
repr(self.frame)
tm.reset_display_options()
warnings.filters = warn_filters
def test_eng_float_formatter(self):
df = DataFrame({'A': [1.41, 141., 14100, 1410000.]})
fmt.set_eng_float_format()
result = df.to_string()
expected = (' A\n'
'0 1.410E+00\n'
'1 141.000E+00\n'
'2 14.100E+03\n'
'3 1.410E+06')
assert result == expected
fmt.set_eng_float_format(use_eng_prefix=True)
result = df.to_string()
expected = (' A\n'
'0 1.410\n'
'1 141.000\n'
'2 14.100k\n'
'3 1.410M')
assert result == expected
fmt.set_eng_float_format(accuracy=0)
result = df.to_string()
expected = (' A\n'
'0 1E+00\n'
'1 141E+00\n'
'2 14E+03\n'
'3 1E+06')
assert result == expected
tm.reset_display_options()
def test_eng_float_formatter(self):
df = DataFrame({"A": [1.41, 141.0, 14100, 1410000.0]})
fmt.set_eng_float_format()
result = df.to_string()
expected = (
" A\n"
"0 1.410E+00\n"
"1 141.000E+00\n"
"2 14.100E+03\n"
"3 1.410E+06"
)
assert result == expected
fmt.set_eng_float_format(use_eng_prefix=True)
result = df.to_string()
expected = (
" A\n" "0 1.410\n" "1 141.000\n" "2 14.100k\n" "3 1.410M"
)
assert result == expected
fmt.set_eng_float_format(accuracy=0)
result = df.to_string()
expected = (
" A\n" "0 1E+00\n" "1 141E+00\n" "2 14E+03\n" "3 1E+06"
)
assert result == expected
tm.reset_display_options()
def test_repr_unsortable(self):
# columns are not sortable
import warnings
warn_filters = warnings.filters
warnings.filterwarnings('ignore',
category=FutureWarning,
module=".*format")
unsortable = DataFrame({'foo': [1] * 50,
datetime.today(): [1] * 50,
'bar': ['bar'] * 50,
datetime.today() + timedelta(1): ['bar'] * 50},
index=np.arange(50))
repr(unsortable)
fmt.set_option('display.precision', 3, 'display.column_space', 10)
repr(self.frame)
fmt.set_option('display.max_rows', 10, 'display.max_columns', 2)
repr(self.frame)
fmt.set_option('display.max_rows', 1000, 'display.max_columns', 1000)
repr(self.frame)
tm.reset_display_options()
warnings.filters = warn_filters
def test_eng_float_formatter(self):
df = DataFrame({'A': [1.41, 141., 14100, 1410000.]})
fmt.set_eng_float_format()
result = df.to_string()
expected = (' A\n'
'0 1.410E+00\n'
'1 141.000E+00\n'
'2 14.100E+03\n'
'3 1.410E+06')
assert result == expected
fmt.set_eng_float_format(use_eng_prefix=True)
result = df.to_string()
expected = (' A\n'
'0 1.410\n'
'1 141.000\n'
'2 14.100k\n'
'3 1.410M')
assert result == expected
fmt.set_eng_float_format(accuracy=0)
result = df.to_string()
expected = (' A\n'
'0 1E+00\n'
'1 141E+00\n'
'2 14E+03\n'
'3 1E+06')
assert result == expected
tm.reset_display_options()
def test_repr_unsortable(self):
# columns are not sortable
import warnings
warn_filters = warnings.filters
warnings.filterwarnings("ignore",
category=FutureWarning,
module=".*format")
unsortable = DataFrame(
{
"foo": [1] * 50,
datetime.today(): [1] * 50,
"bar": ["bar"] * 50,
datetime.today() + timedelta(1): ["bar"] * 50,
},
index=np.arange(50),
)
repr(unsortable)
fmt.set_option("display.precision", 3, "display.column_space", 10)
repr(self.frame)
fmt.set_option("display.max_rows", 10, "display.max_columns", 2)
repr(self.frame)
fmt.set_option("display.max_rows", 1000, "display.max_columns", 1000)
repr(self.frame)
tm.reset_display_options()
warnings.filters = warn_filters
def test_format_sparse_config(idx):
warn_filters = warnings.filters
warnings.filterwarnings('ignore', category=FutureWarning,
module=".*format")
# GH1538
pd.set_option('display.multi_sparse', False)
result = idx.format()
assert result[1] == 'foo two'
tm.reset_display_options()
warnings.filters = warn_filters
def test_format_sparse_config(idx):
warn_filters = warnings.filters
warnings.filterwarnings('ignore', category=FutureWarning,
module=".*format")
# GH1538
pd.set_option('display.multi_sparse', False)
result = idx.format()
assert result[1] == 'foo two'
tm.reset_display_options()
warnings.filters = warn_filters
def test_nan(self):
# Issue #11981
formatter = fmt.EngFormatter(accuracy=1, use_eng_prefix=True)
result = formatter(np.nan)
assert result == 'NaN'
df = pd.DataFrame({'a': [1.5, 10.3, 20.5],
'b': [50.3, 60.67, 70.12],
'c': [100.2, 101.33, 120.33]})
pt = df.pivot_table(values='a', index='b', columns='c')
fmt.set_eng_float_format(accuracy=1)
result = pt.to_string()
assert 'NaN' in result
tm.reset_display_options()
def test_nan(self):
# Issue #11981
formatter = fmt.EngFormatter(accuracy=1, use_eng_prefix=True)
result = formatter(np.nan)
assert result == u('NaN')
df = pd.DataFrame({'a': [1.5, 10.3, 20.5],
'b': [50.3, 60.67, 70.12],
'c': [100.2, 101.33, 120.33]})
pt = df.pivot_table(values='a', index='b', columns='c')
fmt.set_eng_float_format(accuracy=1)
result = pt.to_string()
assert 'NaN' in result
tm.reset_display_options()
def test_nan(self):
# Issue #11981
formatter = fmt.EngFormatter(accuracy=1, use_eng_prefix=True)
result = formatter(np.nan)
assert result == "NaN"
df = pd.DataFrame({
"a": [1.5, 10.3, 20.5],
"b": [50.3, 60.67, 70.12],
"c": [100.2, 101.33, 120.33],
})
pt = df.pivot_table(values="a", index="b", columns="c")
fmt.set_eng_float_format(accuracy=1)
result = pt.to_string()
assert "NaN" in result
tm.reset_display_options()
