本文整理匯總了Python中pandas.core.sparse.api.SparseDataFrame.count方法的典型用法代碼示例。如果您正苦於以下問題：Python SparseDataFrame.count方法的具體用法？Python SparseDataFrame.count怎麽用？Python SparseDataFrame.count使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類pandas.core.sparse.api.SparseDataFrame的用法示例。
在下文中一共展示了SparseDataFrame.count方法的1個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: TestSparseDataFrame
# 需要導入模塊: from pandas.core.sparse.api import SparseDataFrame [as 別名]
# 或者: from pandas.core.sparse.api.SparseDataFrame import count [as 別名]
#.........這裏部分代碼省略.........
def test_constructor_nan_dataframe(self):
# GH 10079
trains = np.arange(100)
thresholds = [10, 20, 30, 40, 50, 60]
tuples = [(i, j) for i in trains for j in thresholds]
index = pd.MultiIndex.from_tuples(tuples,
names=['trains', 'thresholds'])
matrix = np.empty((len(index), len(trains)))
matrix.fill(np.nan)
df = pd.DataFrame(matrix, index=index, columns=trains, dtype=float)
result = df.to_sparse()
expected = pd.SparseDataFrame(matrix, index=index, columns=trains,
dtype=float)
tm.assert_sp_frame_equal(result, expected)
def test_type_coercion_at_construction(self):
# GH 15682
result = pd.SparseDataFrame(
{'a': [1, 0, 0], 'b': [0, 1, 0], 'c': [0, 0, 1]}, dtype='uint8',
default_fill_value=0)
expected = pd.SparseDataFrame(
{'a': pd.SparseSeries([1, 0, 0], dtype='uint8'),
'b': pd.SparseSeries([0, 1, 0], dtype='uint8'),
'c': pd.SparseSeries([0, 0, 1], dtype='uint8')},
default_fill_value=0)
tm.assert_sp_frame_equal(result, expected)
def test_dtypes(self):
df = DataFrame(np.random.randn(10000, 4))
df.loc[:9998] = np.nan
sdf = df.to_sparse()
result = sdf.get_dtype_counts()
expected = Series({'float64': 4})
tm.assert_series_equal(result, expected)
def test_shape(self):
# see gh-10452
assert self.frame.shape == (10, 4)
assert self.iframe.shape == (10, 4)
assert self.zframe.shape == (10, 4)
assert self.fill_frame.shape == (10, 4)
def test_str(self):
df = DataFrame(np.random.randn(10000, 4))
df.loc[:9998] = np.nan
sdf = df.to_sparse()
str(sdf)
def test_array_interface(self):
res = np.sqrt(self.frame)
dres = np.sqrt(self.frame.to_dense())
tm.assert_frame_equal(res.to_dense(), dres)
def test_pickle(self):
def _test_roundtrip(frame, orig):
result = tm.round_trip_pickle(frame)
tm.assert_sp_frame_equal(frame, result)
tm.assert_frame_equal(result.to_dense(), orig, check_dtype=False)
_test_roundtrip(SparseDataFrame(), DataFrame())
self._check_all(_test_roundtrip)