本文整理汇总了Python中pandas.io.common._NA_VALUES属性的典型用法代码示例。如果您正苦于以下问题：Python common._NA_VALUES属性的具体用法？Python common._NA_VALUES怎么用？Python common._NA_VALUES使用的例子？那么恭喜您, 这里精选的属性代码示例或许可以为您提供帮助。您也可以进一步了解该属性所在类pandas.io.common的用法示例。
在下文中一共展示了common._NA_VALUES属性的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_default_na_values
# 需要导入模块: from pandas.io import common [as 别名]
# 或者: from pandas.io.common import _NA_VALUES [as 别名]
def test_default_na_values(self):
_NA_VALUES = set(['-1.#IND', '1.#QNAN', '1.#IND', '-1.#QNAN',
'#N/A', 'N/A', 'n/a', 'NA', '#NA', 'NULL', 'null',
'NaN', 'nan', '-NaN', '-nan', '#N/A N/A', ''])
assert _NA_VALUES == com._NA_VALUES
nv = len(_NA_VALUES)
def f(i, v):
if i == 0:
buf = ''
elif i > 0:
buf = ''.join([','] * i)
buf = "{0}{1}".format(buf, v)
if i < nv - 1:
buf = "{0}{1}".format(buf, ''.join([','] * (nv - i - 1)))
return buf
data = StringIO('\n'.join(f(i, v) for i, v in enumerate(_NA_VALUES)))
expected = DataFrame(np.nan, columns=range(nv), index=range(nv))
df = self.read_csv(data, header=None)
tm.assert_frame_equal(df, expected) 示例2: test_default_na_values
# 需要导入模块: from pandas.io import common [as 别名]
# 或者: from pandas.io.common import _NA_VALUES [as 别名]
def test_default_na_values(self):
_NA_VALUES = set(['-1.#IND', '1.#QNAN', '1.#IND', '-1.#QNAN',
'#N/A', 'N/A', 'n/a', 'NA', '#NA', 'NULL', 'null',
'NaN', 'nan', '-NaN', '-nan', '#N/A N/A', ''])
assert _NA_VALUES == com._NA_VALUES
nv = len(_NA_VALUES)
def f(i, v):
if i == 0:
buf = ''
elif i > 0:
buf = ''.join([','] * i)
buf = "{0}{1}".format(buf, v)
if i < nv - 1:
buf = "{0}{1}".format(buf, ''.join([','] * (nv - i - 1)))
return buf
data = StringIO('\n'.join([f(i, v) for i, v in enumerate(_NA_VALUES)]))
expected = DataFrame(np.nan, columns=range(nv), index=range(nv))
df = self.read_csv(data, header=None)
tm.assert_frame_equal(df, expected) 示例3: test_default_na_values
# 需要导入模块: from pandas.io import common [as 别名]
# 或者: from pandas.io.common import _NA_VALUES [as 别名]
def test_default_na_values(all_parsers):
_NA_VALUES = {"-1.#IND", "1.#QNAN", "1.#IND", "-1.#QNAN", "#N/A",
"N/A", "n/a", "NA", "#NA", "NULL", "null", "NaN", "nan",
"-NaN", "-nan", "#N/A N/A", ""}
assert _NA_VALUES == com._NA_VALUES
parser = all_parsers
nv = len(_NA_VALUES)
def f(i, v):
if i == 0:
buf = ""
elif i > 0:
buf = "".join([","] * i)
buf = "{0}{1}".format(buf, v)
if i < nv - 1:
buf = "{0}{1}".format(buf, "".join([","] * (nv - i - 1)))
return buf
data = StringIO("\n".join(f(i, v) for i, v in enumerate(_NA_VALUES)))
expected = DataFrame(np.nan, columns=range(nv), index=range(nv))
result = parser.read_csv(data, header=None)
tm.assert_frame_equal(result, expected)