def test_dataframemodel_sort():
df = DataFrame({'colA': [1, 3], 'colB': ['c', 'a']})
dfm = DataFrameModel(df)
dfm.sort(2)
assert data(dfm, 0, 0) == '1'
assert data(dfm, 0, 1) == '3'
assert data(dfm, 0, 2) == 'a'
assert data(dfm, 1, 0) == '0'
assert data(dfm, 1, 1) == '1'
assert data(dfm, 1, 2) == 'c'
def test_dataframemodel_basic():
df = DataFrame({'colA': [1, 3], 'colB': ['c', 'a']})
dfm = DataFrameModel(df)
assert dfm.rowCount() == 2
assert dfm.columnCount() == 3
assert data(dfm, 0, 0) == '0'
assert data(dfm, 0, 1) == '1'
assert data(dfm, 0, 2) == 'c'
assert data(dfm, 1, 0) == '1'
assert data(dfm, 1, 1) == '3'
assert data(dfm, 1, 2) == 'a'
def test_dataframemodel_sort_is_stable(): # cf. issue 3010
df = DataFrame([[2, 14], [2, 13], [2, 16], [1, 3], [2, 9], [1, 15],
[1, 17], [2, 2], [2, 10], [1, 6], [2, 5], [2, 8], [1, 11],
[1, 1], [1, 12], [1, 4], [2, 7]])
dfm = DataFrameModel(df)
dfm.sort(2)
dfm.sort(1)
col2 = [data(dfm, i, 2) for i in range(len(df))]
assert col2 == [
str(x)
for x in [1, 3, 4, 6, 11, 12, 15, 17, 2, 5, 7, 8, 9, 10, 13, 14, 16]
]
def test_dataframemodel_get_bgcolor_with_numbers_using_global_max():
df = DataFrame([[0, 10], [1, 20], [2, 40]])
dfm = DataFrameModel(df)
dfm.colum_avg(0)
h0 = dataframeeditor.BACKGROUND_NUMBER_MINHUE
dh = dataframeeditor.BACKGROUND_NUMBER_HUERANGE
s = dataframeeditor.BACKGROUND_NUMBER_SATURATION
v = dataframeeditor.BACKGROUND_NUMBER_VALUE
a = dataframeeditor.BACKGROUND_NUMBER_ALPHA
assert colorclose(bgcolor(dfm, 0, 1), (h0 + dh, s, v, a))
assert colorclose(bgcolor(dfm, 1, 1), (h0 + 39 / 40 * dh, s, v, a))
assert colorclose(bgcolor(dfm, 2, 1), (h0 + 38 / 40 * dh, s, v, a))
assert colorclose(bgcolor(dfm, 0, 2), (h0 + 30 / 40 * dh, s, v, a))
assert colorclose(bgcolor(dfm, 1, 2), (h0 + 20 / 40 * dh, s, v, a))
assert colorclose(bgcolor(dfm, 2, 2), (h0, s, v, a))
def test_dataframemodel_get_bgcolor_with_object():
df = DataFrame([[None]])
dfm = DataFrameModel(df)
h, s, v, dummy = QColor(
dataframeeditor.BACKGROUND_NONNUMBER_COLOR).getHsvF()
a = dataframeeditor.BACKGROUND_MISC_ALPHA
assert colorclose(bgcolor(dfm, 0, 1), (h, s, v, a))
def test_dataframemodel_get_bgcolor_with_string():
df = DataFrame([['xxx']])
dfm = DataFrameModel(df)
h, s, v, dummy = QColor(
dataframeeditor.BACKGROUND_NONNUMBER_COLOR).getHsvF()
a = dataframeeditor.BACKGROUND_STRING_ALPHA
assert colorclose(bgcolor(dfm, 0, 1), (h, s, v, a))
def test_dataframemodel_get_bgcolor_for_index():
df = DataFrame([[0]])
dfm = DataFrameModel(df)
h, s, v, dummy = QColor(
dataframeeditor.BACKGROUND_NONNUMBER_COLOR).getHsvF()
a = dataframeeditor.BACKGROUND_INDEX_ALPHA
assert colorclose(bgcolor(dfm, 0, 0), (h, s, v, a))
def test_dataframemodel_with_categories(): # cf. issue 3308
df = DataFrame({
"id": [1, 2, 3, 4, 5, 6],
"raw_grade": ['a', 'b', 'b', 'a', 'a', 'e']
})
df["grade"] = df["raw_grade"].astype("category")
dfm = DataFrameModel(df)
assert dfm.max_min_col == [[6, 1], None, None]
def test_dataframemodel_with_format_percent_d_and_nan():
"""
Test DataFrameModel with format `%d` and dataframe containing NaN
Regression test for issue 4139.
"""
np_array = numpy.zeros(2)
np_array[1] = numpy.nan
dataframe = DataFrame(np_array)
dfm = DataFrameModel(dataframe, format='%d')
assert data(dfm, 0, 1) == '0'
assert data(dfm, 1, 1) == 'nan'
def test_dataframemodel_get_bgcolor_with_numbers():
df = DataFrame([[0, 10], [1, 20], [2, 40]])
dfm = DataFrameModel(df)
h0 = dataframeeditor.BACKGROUND_NUMBER_MINHUE
dh = dataframeeditor.BACKGROUND_NUMBER_HUERANGE
s = dataframeeditor.BACKGROUND_NUMBER_SATURATION
v = dataframeeditor.BACKGROUND_NUMBER_VALUE
a = dataframeeditor.BACKGROUND_NUMBER_ALPHA
assert colorclose(bgcolor(dfm, 0, 1), (h0 + dh, s, v, a))
assert colorclose(bgcolor(dfm, 1, 1), (h0 + 1 / 2 * dh, s, v, a))
assert colorclose(bgcolor(dfm, 2, 1), (h0, s, v, a))
assert colorclose(bgcolor(dfm, 0, 2), (h0 + dh, s, v, a))
assert colorclose(bgcolor(dfm, 1, 2), (h0 + 2 / 3 * dh, s, v, a))
assert colorclose(bgcolor(dfm, 2, 2), (h0, s, v, a))
def test_dataframemodel_max_min_col_update_constant():
df = DataFrame([[1, 2.0], [1, 2.0], [1, 2.0]])
dfm = DataFrameModel(df)
assert dfm.max_min_col == [[1, 0], [2.0, 1.0]]
def test_dataframemodel_max_min_col_update():
df = DataFrame([[1, 2.0], [2, 2.5], [3, 9.0]])
dfm = DataFrameModel(df)
assert dfm.max_min_col == [[3, 1], [9.0, 2.0]]
def test_dataframemodel_with_timezone_aware_timestamps(): # cf. issue 2940
df = DataFrame([x] for x in date_range('20150101', periods=5, tz='UTC'))
dfm = DataFrameModel(df)
assert dfm.max_min_col == [None]