def pytest_generate_tests(metafunc):
_test_suite = get_series()
_test_suite.update(get_geometry_series())
if metafunc.function.__name__ in ["test_consistency", "test_traversal_mutex"]:
argsvalues = []
for name, series in _test_suite.items():
args = {"id": name}
argsvalues.append(pytest.param(name, series, **args))
metafunc.parametrize(argnames=["name", "series"], argvalues=argsvalues)
get_convert_cases,
get_inference_cases,
infers,
)
from pandas_profiling.config import config
from pandas_profiling.model.typeset import (
Boolean,
Categorical,
DateTime,
Numeric,
ProfilingTypeSet,
Unsupported,
)
series = get_series()
typeset = ProfilingTypeSet()
contains_map = {
Numeric: {
"int_series",
"Int64_int_series",
"int_range",
"Int64_int_nan_series",
"int_series_boolean",
"np_uint32",
"pd_uint32",
"float_series",
"float_series2",
"float_series3",
DateTime,
Float,
Generic,
Integer,
Object,
String,
TimeDelta,
)
from visions.typesets.standard_set import StandardSet
def reload_series_to_numpy(s):
return np.array(s.tolist())
array = get_series()
array.update(get_geometry_series())
array = {k: v.to_numpy() for k, v in array.items()}
# Pandas doesn't correctly handle complex categoricals pending
# https://github.com/pandas-dev/pandas/pull/36482/
array.pop("categorical_complex_series")
# Some sequences don't round trip correctly from pandas (i.e. Series.to_numpy()
# is not equivalent to np.array(Series.tolist())
array["Int64_int_series"] = reload_series_to_numpy(array["Int64_int_series"])
array["pd_uint32"] = reload_series_to_numpy(array["pd_uint32"])
typeset = StandardSet() - Categorical
contains_map = {