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import threading
import textwrap
import numpy as np
from Orange.widgets import widget, gui
from Orange.widgets.utils.localization import pl
from Orange.widgets.utils.widgetpreview import WidgetPreview
from Orange.widgets.widget import Input
from Orange.data import \
Table, StringVariable, DiscreteVariable, ContinuousVariable
try:
from Orange.data.sql.table import SqlTable
except ImportError:
def is_sql(_):
return False
else:
def is_sql(data):
return isinstance(data, SqlTable)
class OWDataInfo(widget.OWWidget):
name = "Data Info"
id = "orange.widgets.data.info"
description = "Display basic information about the data set"
icon = "icons/DataInfo.svg"
priority = 80
category = "Data"
keywords = "data info, information, inspect"
class Inputs:
data = Input("Data", Table)
want_main_area = False
buttons_area_orientation = None
resizing_enabled = False
def __init__(self):
super().__init__()
self.data_desc = {}
self.data_attrs = {}
self.description = gui.widgetLabel(
gui.vBox(self.controlArea, box="Data table properties"))
self.attributes = gui.widgetLabel(
gui.vBox(self.controlArea, box="Additional attributes"))
@Inputs.data
def data(self, data):
if data is None:
self.data_desc = self.data_attrs = {}
self.update_info()
else:
self.data_desc = {
label: value
for label, func in (("Name", self._p_name),
("Location", self._p_location),
("Size", self._p_size),
("Features", self._p_features),
("Targets", self._p_targets),
("Metas", self._p_metas),
("Missing data", self._p_missing))
if bool(value := func(data))}
self.data_attrs = data.attributes
self.update_info()
if is_sql(data):
def set_exact_length():
self.data_desc["Size"] = self._p_size(data, exact=True)
self.update_info()
threading.Thread(target=set_exact_length).start()
def update_info(self):
style = """<style>
th { text-align: right; vertical-align: top; }
th, td { padding-top: 4px; line-height: 125%}
</style>"""
def dict_as_table(d):
return "<table>" + \
"".join(f"<tr><th>{label}: </th><td>" + \
'<br/>'.join(textwrap.wrap(value, width=60)) + \
"</td></tr>"
for label, value in d.items()) + \
"</table>"
if not self.data_desc:
self.description.setText("No data.")
else:
self.description.setText(style + dict_as_table(self.data_desc))
self.attributes.setHidden(not self.data_attrs)
if self.data_attrs:
self.attributes.setText(
style + dict_as_table({k: str(v)
for k, v in self.data_attrs.items()}))
def send_report(self):
if self.data_desc:
self.report_items("Data table properties", self.data_desc)
if self.data_attrs:
self.report_items("Additional attributes", self.data_attrs)
@staticmethod
def _p_name(data):
return getattr(data, "name", "-")
@staticmethod
def _p_location(data):
if not is_sql(data):
return None
connection_string = ' '.join(
f'{key}={value}'
for key, value in data.connection_params.items()
if value is not None and key != 'password')
return f"SQL Table using connection:<br/>{connection_string}"
@staticmethod
def _p_size(data, exact=False):
exact = exact or is_sql(data)
if exact:
n = len(data)
desc = f"{n} {pl(n, 'row')}"
else:
n = data.approx_len()
desc = f"~{n} {pl(n, 'row')}"
ncols = len(data.domain.variables) + len(data.domain.metas)
desc += f", {ncols} {pl(ncols, 'column')}"
sparseness = [s for s, m in (("features", data.X_density),
("meta attributes", data.metas_density),
("targets", data.Y_density)) if m() > 1]
if sparseness:
desc += "; sparse {', '.join(sparseness)}"
return desc
@classmethod
def _p_features(cls, data):
return cls._pack_var_counts(data.domain.attributes)
def _p_targets(self, data):
if class_var := data.domain.class_var:
if class_var.is_continuous:
return "numeric target variable"
else:
nclasses = len(class_var.values)
return "categorical outcome with " \
f"{nclasses} {pl(nclasses, 'class|classes')}"
if class_vars := data.domain.class_vars:
disc_class = self._count(class_vars, DiscreteVariable)
cont_class = self._count(class_vars, ContinuousVariable)
if not cont_class:
return f"{disc_class} categorical {pl(disc_class, 'target')}"
elif not disc_class:
return f"{cont_class} numeric {pl(cont_class, 'target')}"
return "multi-target data,<br/>" + self._pack_var_counts(class_vars)
@classmethod
def _p_metas(cls, data):
return cls._pack_var_counts(data.domain.metas)
@staticmethod
def _p_missing(data: Table):
if is_sql(data):
return "(not checked for SQL data)"
counts = []
for name, part, n_miss in ((pl(len(data.domain.attributes), "feature"),
data.X, data.get_nan_count_attribute()),
(pl(len(data.domain.class_vars), "targets"),
data.Y, data.get_nan_count_class()),
(pl(len(data.domain.metas), "meta variable"),
data.metas, data.get_nan_count_metas())):
if n_miss:
counts.append(
f"{n_miss} ({n_miss / np.prod(part.shape):.1%}) in {name}")
if not counts:
return "none"
return ", ".join(counts)
@staticmethod
def _count(s, tpe):
return sum(isinstance(x, tpe) for x in s)
@classmethod
def _pack_var_counts(cls, s):
counts = (
(name, cls._count(s, type_))
for name, type_ in (("categorical", DiscreteVariable),
("numeric", ContinuousVariable),
("text", StringVariable)))
return ", ".join(f"{count} {name}" for name, count in counts if count)
if __name__ == "__main__": # pragma: no cover
WidgetPreview(OWDataInfo).run(Table("heart_disease"))
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