def test_default_formats(self):
B = float("-1,250,500,880.76".replace(",", ""))
M = B / 1000.0
k = M / 1000.0
p = k / 1000000.0
tests = [
(B, "$(1.3B)", fmt.BillionDollarsFormatter),
(B, "(1.3B)", fmt.BillionsFormatter),
(M, "$(1.3M)", fmt.MillionDollarsFormatter),
(M, "(1.3M)", fmt.MillionsFormatter),
(k, "$(1.3k)", fmt.ThousandDollarsFormatter),
(k, "(1.3k)", fmt.ThousandsFormatter),
(k, "(1,250.50)", fmt.FloatFormatter),
(k, "(1,251)", fmt.IntFormatter),
# Floats
(k, "-1,251", fmt.new_int_formatter(commas=1, parens=False)),
(k, "-1251", fmt.new_int_formatter(commas=0, parens=False)),
(abs(k), "1251", fmt.new_int_formatter(commas=0, parens=False)),
(abs(k), "1,251", fmt.new_int_formatter(commas=1)),
(str(k), "-1,251",
fmt.new_int_formatter(commas=1, coerce=True, parens=0)),
# Ints
(k, "-1,251", fmt.new_int_formatter(commas=1, parens=False)),
(k, "-1251", fmt.new_int_formatter(commas=0, parens=False)),
(abs(k), "1251", fmt.new_int_formatter(commas=0, parens=False)),
(abs(k), "1,251", fmt.new_int_formatter(commas=1)),
# Percents
(0.12433, "12.4%", fmt.new_percent_formatter(commas=1,
precision=1)),
(0.12433, "12.433%",
fmt.new_percent_formatter(commas=1, precision=3)),
(
-0.12433,
"-12.4%",
fmt.new_percent_formatter(commas=1, parens=0, precision=1),
),
(
-0.12433,
"(12.4%)",
fmt.new_percent_formatter(commas=1, parens=1, precision=1),
),
]
for val, expected, fct in tests:
actual = fct(val)
self.assertEqual(expected, actual)
# Test if it were a list
actual = fct([val] * 5)
self.assertEqual([expected] * 5, actual)
# Test if it were a series
actual = fct(pd.Series([val] * 5))
pt.assert_series_equal(pd.Series([expected] * 5), actual)
# Test if it were a DataFrame
actual = fct(pd.DataFrame({"a": [val] * 5, "b": [val] * 5}))
pt.assert_frame_equal(
pd.DataFrame({
"a": [expected] * 5,
"b": [expected] * 5
}), actual)
def test_default_formats(self):
B = float('-1,250,500,880.76'.replace(',', ''))
M = B / 1000.
k = M / 1000.
p = k / 1000000.
tests = [
(B, '$(1.3B)', fmt.BillionDollarsFormatter),
(B, '(1.3B)', fmt.BillionsFormatter),
(M, '$(1.3M)', fmt.MillionDollarsFormatter),
(M, '(1.3M)', fmt.MillionsFormatter),
(k, '$(1.3k)', fmt.ThousandDollarsFormatter),
(k, '(1.3k)', fmt.ThousandsFormatter),
(k, '(1,250.50)', fmt.FloatFormatter),
(k, '(1,251)', fmt.IntFormatter),
# Floats
(k, '-1,251', fmt.new_int_formatter(commas=1, parens=False)),
(k, '-1251', fmt.new_int_formatter(commas=0, parens=False)),
(abs(k), '1251', fmt.new_int_formatter(commas=0, parens=False)),
(abs(k), '1,251', fmt.new_int_formatter(commas=1)),
(str(k), '-1,251',
fmt.new_int_formatter(commas=1, coerce=True, parens=0)),
# Ints
(k, '-1,251', fmt.new_int_formatter(commas=1, parens=False)),
(k, '-1251', fmt.new_int_formatter(commas=0, parens=False)),
(abs(k), '1251', fmt.new_int_formatter(commas=0, parens=False)),
(abs(k), '1,251', fmt.new_int_formatter(commas=1)),
# Percents
(.12433, '12.4%', fmt.new_percent_formatter(commas=1,
precision=1)),
(.12433, '12.433%', fmt.new_percent_formatter(commas=1,
precision=3)),
(-.12433, '-12.4%',
fmt.new_percent_formatter(commas=1, parens=0, precision=1)),
(-.12433, '(12.4%)',
fmt.new_percent_formatter(commas=1, parens=1, precision=1)),
]
for val, expected, fct in tests:
actual = fct(val)
self.assertEquals(expected, actual)
# Test if it were a list
actual = fct([val] * 5)
self.assertEquals([expected] * 5, actual)
# Test if it were a series
actual = fct(pd.Series([val] * 5))
pt.assert_series_equal(pd.Series([expected] * 5), actual)
# Test if it were a DataFrame
actual = fct(pd.DataFrame({'a': [val] * 5, 'b': [val] * 5}))
pt.assert_frame_equal(
pd.DataFrame({
'a': [expected] * 5,
'b': [expected] * 5
}), actual)
def test_default_formats(self):
B = float("-1,250,500,880.76".replace(",", ""))
M = B / 1000.0
k = M / 1000.0
p = k / 1000000.0
tests = [
(B, "$(1.3B)", fmt.BillionDollarsFormatter),
(B, "(1.3B)", fmt.BillionsFormatter),
(M, "$(1.3M)", fmt.MillionDollarsFormatter),
(M, "(1.3M)", fmt.MillionsFormatter),
(k, "$(1.3k)", fmt.ThousandDollarsFormatter),
(k, "(1.3k)", fmt.ThousandsFormatter),
(k, "(1,250.50)", fmt.FloatFormatter),
(k, "(1,251)", fmt.IntFormatter),
# Floats
(k, "-1,251", fmt.new_int_formatter(commas=1, parens=False)),
(k, "-1251", fmt.new_int_formatter(commas=0, parens=False)),
(abs(k), "1251", fmt.new_int_formatter(commas=0, parens=False)),
(abs(k), "1,251", fmt.new_int_formatter(commas=1)),
(str(k), "-1,251", fmt.new_int_formatter(commas=1, coerce=True, parens=0)),
# Ints
(k, "-1,251", fmt.new_int_formatter(commas=1, parens=False)),
(k, "-1251", fmt.new_int_formatter(commas=0, parens=False)),
(abs(k), "1251", fmt.new_int_formatter(commas=0, parens=False)),
(abs(k), "1,251", fmt.new_int_formatter(commas=1)),
# Percents
(0.12433, "12.4%", fmt.new_percent_formatter(commas=1, precision=1)),
(0.12433, "12.433%", fmt.new_percent_formatter(commas=1, precision=3)),
(-0.12433, "-12.4%", fmt.new_percent_formatter(commas=1, parens=0, precision=1)),
(-0.12433, "(12.4%)", fmt.new_percent_formatter(commas=1, parens=1, precision=1)),
]
for val, expected, fct in tests:
actual = fct(val)
self.assertEquals(expected, actual)
# Test if it were a list
actual = fct([val] * 5)
self.assertEquals([expected] * 5, actual)
# Test if it were a series
actual = fct(pd.Series([val] * 5))
pt.assert_series_equal(pd.Series([expected] * 5), actual)
# Test if it were a DataFrame
actual = fct(pd.DataFrame({"a": [val] * 5, "b": [val] * 5}))
pt.assert_frame_equal(pd.DataFrame({"a": [expected] * 5, "b": [expected] * 5}), actual)
def test_default_formats(self):
B = float('-1,250,500,880.76'.replace(',', ''))
M = B / 1000.
k = M / 1000.
p = k / 1000000.
tests = [
(B, '$(1.3B)', fmt.BillionDollarsFormatter),
(B, '(1.3B)', fmt.BillionsFormatter),
(M, '$(1.3M)', fmt.MillionDollarsFormatter),
(M, '(1.3M)', fmt.MillionsFormatter),
(k, '$(1.3k)', fmt.ThousandDollarsFormatter),
(k, '(1.3k)', fmt.ThousandsFormatter),
(k, '(1,250.50)', fmt.FloatFormatter),
(k, '(1,251)', fmt.IntFormatter),
# Floats
(k, '-1,251', fmt.new_int_formatter(commas=1, parens=False)),
(k, '-1251', fmt.new_int_formatter(commas=0, parens=False)),
(abs(k), '1251', fmt.new_int_formatter(commas=0, parens=False)),
(abs(k), '1,251', fmt.new_int_formatter(commas=1)),
(str(k), '-1,251', fmt.new_int_formatter(commas=1, coerce=True, parens=0)),
# Ints
(k, '-1,251', fmt.new_int_formatter(commas=1, parens=False)),
(k, '-1251', fmt.new_int_formatter(commas=0, parens=False)),
(abs(k), '1251', fmt.new_int_formatter(commas=0, parens=False)),
(abs(k), '1,251', fmt.new_int_formatter(commas=1)),
# Percents
(.12433, '12.4%', fmt.new_percent_formatter(commas=1, precision=1)),
(.12433, '12.433%', fmt.new_percent_formatter(commas=1, precision=3)),
(-.12433, '-12.4%', fmt.new_percent_formatter(commas=1, parens=0, precision=1)),
(-.12433, '(12.4%)', fmt.new_percent_formatter(commas=1, parens=1, precision=1)),
]
for val, expected, fct in tests:
actual = fct(val)
self.assertEqual(expected, actual)
# Test if it were a list
actual = fct([val]*5)
self.assertEqual([expected]*5, actual)
# Test if it were a series
actual = fct(pd.Series([val]*5))
pt.assert_series_equal(pd.Series([expected]*5), actual)
# Test if it were a DataFrame
actual = fct(pd.DataFrame({'a': [val]*5, 'b': [val]*5}))
pt.assert_frame_equal(pd.DataFrame({'a': [expected]*5, 'b': [expected]*5}), actual)
def pad_positive_wrapper(fmtfct):
"""Ensure that numbers are aligned in table by appending a blank space to postive values if 'parenthesis' are
used to denote negative numbers"""
def check_and_append(*args, **kwargs):
result = fmtfct(*args, **kwargs)
if fmtfct.parens and not result.endswith(')'):
result += ' '
return result
return check_and_append
IntFormatter = pad_positive_wrapper(fmt.new_int_formatter(nan='-'))
FloatFormatter = pad_positive_wrapper(fmt.new_float_formatter(nan='-'))
PercentFormatter = pad_positive_wrapper(fmt.new_percent_formatter(nan='-'))
ThousandsFormatter = pad_positive_wrapper(fmt.new_thousands_formatter(nan='-'))
MillionsFormatter = pad_positive_wrapper(fmt.new_millions_formatter(nan='-'))
BillionsFormatter = pad_positive_wrapper(fmt.new_billions_formatter(nan='-'))
# Don't attempt to pad
DynamicNumberFormatter = fmt.DynamicNumberFormat(nan='-', pcts=1, trunc_dot_zeros=1)
DollarCentsFormatter = pad_positive_wrapper(fmt.new_float_formatter(prefix='$', nan='-'))
DollarFormatter = pad_positive_wrapper(fmt.new_int_formatter(prefix='$', nan='-'))
ThousandDollarsFormatter = pad_positive_wrapper(fmt.new_thousands_formatter(prefix='$', nan='-'))
MillionDollarsFormatter = pad_positive_wrapper(fmt.new_millions_formatter(prefix='$', nan='-'))
BillionDollarsFormatter = pad_positive_wrapper(fmt.new_billions_formatter(prefix='$', nan='-'))
YmdFormatter = fmt.new_datetime_formatter('%Y%m%d', True)
Y_m_dFormatter = fmt.new_datetime_formatter('%Y_%m_%d', True)
ConditionalRedBlack = lambda x: x < 0 and dict(TEXTCOLOR=HexColor("#800000"))
def pad_positive_wrapper(fmtfct):
"""Ensure that numbers are aligned in table by appending a blank space to postive values if 'parenthesis' are
used to denote negative numbers"""
def check_and_append(*args, **kwargs):
result = fmtfct(*args, **kwargs)
if fmtfct.parens and not result.endswith(')'):
result += ' '
return result
return check_and_append
IntFormatter = pad_positive_wrapper(fmt.new_int_formatter(nan='-'))
FloatFormatter = pad_positive_wrapper(fmt.new_float_formatter(nan='-'))
PercentFormatter = pad_positive_wrapper(fmt.new_percent_formatter(nan='-'))
ThousandsFormatter = pad_positive_wrapper(fmt.new_thousands_formatter(nan='-'))
MillionsFormatter = pad_positive_wrapper(fmt.new_millions_formatter(nan='-'))
BillionsFormatter = pad_positive_wrapper(fmt.new_billions_formatter(nan='-'))
# Don't attempt to pad
DynamicNumberFormatter = fmt.DynamicNumberFormat(method='col',
nan='-',
pcts=1,
trunc_dot_zeros=1)
DollarCentsFormatter = pad_positive_wrapper(
fmt.new_float_formatter(prefix='$', nan='-'))
DollarFormatter = pad_positive_wrapper(
fmt.new_int_formatter(prefix='$', nan='-'))
def pad_positive_wrapper(fmtfct):
"""Ensure that numbers are aligned in table by appending a blank space to postive values if 'parenthesis' are
used to denote negative numbers"""
def check_and_append(*args, **kwargs):
result = fmtfct(*args, **kwargs)
if fmtfct.parens and not result.endswith(")"):
result += " "
return result
return check_and_append
IntFormatter = pad_positive_wrapper(fmt.new_int_formatter(nan="-"))
FloatFormatter = pad_positive_wrapper(fmt.new_float_formatter(nan="-"))
PercentFormatter = pad_positive_wrapper(fmt.new_percent_formatter(nan="-"))
ThousandsFormatter = pad_positive_wrapper(fmt.new_thousands_formatter(nan="-"))
MillionsFormatter = pad_positive_wrapper(fmt.new_millions_formatter(nan="-"))
BillionsFormatter = pad_positive_wrapper(fmt.new_billions_formatter(nan="-"))
# Don't attempt to pad
DynamicNumberFormatter = fmt.DynamicNumberFormat(method="col", nan="-", pcts=1, trunc_dot_zeros=1)
DollarCentsFormatter = pad_positive_wrapper(fmt.new_float_formatter(prefix="$", nan="-"))
DollarFormatter = pad_positive_wrapper(fmt.new_int_formatter(prefix="$", nan="-"))
ThousandDollarsFormatter = pad_positive_wrapper(fmt.new_thousands_formatter(prefix="$", nan="-"))
MillionDollarsFormatter = pad_positive_wrapper(fmt.new_millions_formatter(prefix="$", nan="-"))
BillionDollarsFormatter = pad_positive_wrapper(fmt.new_billions_formatter(prefix="$", nan="-"))
YmdFormatter = fmt.new_datetime_formatter("%Y%m%d", True)
Y_m_dFormatter = fmt.new_datetime_formatter("%Y-%m-%d", True)
ConditionalRedBlack = lambda x: x < 0 and dict(TEXTCOLOR=HexColor("#800000"))
def pad_positive_wrapper(fmtfct):
"""Ensure that numbers are aligned in table by appending a blank space to postive values if 'parenthesis' are
used to denote negative numbers"""
def check_and_append(*args, **kwargs):
result = fmtfct(*args, **kwargs)
if fmtfct.parens and not result.endswith(")"):
result += " "
return result
return check_and_append
IntFormatter = pad_positive_wrapper(fmt.new_int_formatter(nan="-"))
FloatFormatter = pad_positive_wrapper(fmt.new_float_formatter(nan="-"))
PercentFormatter = pad_positive_wrapper(fmt.new_percent_formatter(nan="-"))
ThousandsFormatter = pad_positive_wrapper(fmt.new_thousands_formatter(nan="-"))
MillionsFormatter = pad_positive_wrapper(fmt.new_millions_formatter(nan="-"))
BillionsFormatter = pad_positive_wrapper(fmt.new_billions_formatter(nan="-"))
# Don't attempt to pad
DynamicNumberFormatter = fmt.DynamicNumberFormat(method="col",
nan="-",
pcts=1,
trunc_dot_zeros=1)
DollarCentsFormatter = pad_positive_wrapper(
fmt.new_float_formatter(prefix="$", nan="-"))
DollarFormatter = pad_positive_wrapper(
fmt.new_int_formatter(prefix="$", nan="-"))
