def test_idadf_onecolumn_numeric_numeric_stats_one_column(self, idadf_onecolumn_numeric):
column = idadf_onecolumn_numeric.columns.tolist()
assert isinstance(_numeric_stats(idadf_onecolumn_numeric, "count", column), numpy.float64)
assert isinstance(_numeric_stats(idadf_onecolumn_numeric, "mean", column), numpy.float64)
assert isinstance(_numeric_stats(idadf_onecolumn_numeric, "median", column), numpy.ndarray)
assert isinstance(_numeric_stats(idadf_onecolumn_numeric, "std", column), numpy.float64)
assert isinstance(_numeric_stats(idadf_onecolumn_numeric, "var", column), numpy.float64)
assert isinstance(_numeric_stats(idadf_onecolumn_numeric, "min", column), numpy.float64)
assert isinstance(_numeric_stats(idadf_onecolumn_numeric, "max", column), numpy.float64)
def test_idadf_numeric_stats_default(self, idadf):
data = idadf._table_def() # We necessarly have to put the test under this condition
columns = list(data.loc[data['VALTYPE'] == "NUMERIC"].index)
assert isinstance(_numeric_stats(idadf, "count", columns), numpy.ndarray)
assert isinstance(_numeric_stats(idadf, "mean", columns), numpy.ndarray)
assert isinstance(_numeric_stats(idadf, "median", columns), numpy.ndarray)
assert isinstance(_numeric_stats(idadf, "std", columns), numpy.ndarray)
assert isinstance(_numeric_stats(idadf, "var", columns), numpy.ndarray)
assert isinstance(_numeric_stats(idadf, "min", columns), numpy.ndarray)
assert isinstance(_numeric_stats(idadf, "max", columns), numpy.ndarray)
def test_idadf_numeric_stats_default(self, idadf):
data = idadf._table_def() # We necessarly have to put the test under this condition
columns = list(data.loc[data["VALTYPE"] == "NUMERIC"].index)
assert isinstance(_numeric_stats(idadf, "count", columns), numpy.ndarray)
assert isinstance(_numeric_stats(idadf, "mean", columns), numpy.ndarray)
assert isinstance(_numeric_stats(idadf, "median", columns), numpy.ndarray)
assert isinstance(_numeric_stats(idadf, "std", columns), numpy.ndarray)
assert isinstance(_numeric_stats(idadf, "var", columns), numpy.ndarray)
assert isinstance(_numeric_stats(idadf, "min", columns), numpy.ndarray)
assert isinstance(_numeric_stats(idadf, "max", columns), numpy.ndarray)