def setData(self, index, value, role=DTYPE_CHANGE_ROLE):
"""Updates the datatype of a column.
The model must be initated with a dataframe already, since valid
indexes are necessary. The `value` is a translated description of the
data type. The translations can be found at
`pandasqt.translation.DTypeTranslator`.
If a datatype can not be converted, e.g. datetime to integer, a
`NotImplementedError` will be raised.
Args:
index (QtCore.QModelIndex): The index of the column to be changed.
value (str): The description of the new datatype, e.g.
`positive kleine ganze Zahl (16 Bit)`.
role (Qt.ItemDataRole, optional): The role, which accesses and
changes data. Defaults to `DTYPE_CHANGE_ROLE`.
Raises:
NotImplementedError: If an error during conversion occured.
Returns:
bool: `True` if the datatype could be changed, `False` if not or if
the new datatype equals the old one.
"""
if role != DTYPE_CHANGE_ROLE or not index.isValid():
return False
if not self.editable():
return False
self.layoutAboutToBeChanged.emit()
dtype = SupportedDtypes.dtype(value)
currentDtype = np.dtype(index.data(role=DTYPE_ROLE))
if dtype is not None:
if dtype != currentDtype:
col = index.column()
#row = self._dataFrame.columns[index.column()]
columnName = self._dataFrame.columns[index.row()]
try:
if dtype == np.dtype('<M8[ns]'):
if currentDtype in SupportedDtypes.boolTypes():
raise Exception, u"Can't convert a boolean value into a datetime value."
self._dataFrame[columnName] = self._dataFrame[columnName].apply(pandas.to_datetime)
else:
self._dataFrame[columnName] = self._dataFrame[columnName].astype(dtype)
self.dtypeChanged.emit(index.row(), dtype)
self.layoutChanged.emit()
return True
except Exception, e:
message = 'Could not change datatype %s of column %s to datatype %s' % (currentDtype, columnName, dtype)
self.changeFailed.emit(message, index, dtype)
raise
def setData(self, index, value, role=DTYPE_CHANGE_ROLE):
"""Updates the datatype of a column.
The model must be initated with a dataframe already, since valid
indexes are necessary. The `value` is a translated description of the
data type. The translations can be found at
`pandasqt.translation.DTypeTranslator`.
If a datatype can not be converted, e.g. datetime to integer, a
`NotImplementedError` will be raised.
Args:
index (QtCore.QModelIndex): The index of the column to be changed.
value (str): The description of the new datatype, e.g.
`positive kleine ganze Zahl (16 Bit)`.
role (Qt.ItemDataRole, optional): The role, which accesses and
changes data. Defaults to `DTYPE_CHANGE_ROLE`.
Raises:
NotImplementedError: If an error during conversion occured.
Returns:
bool: `True` if the datatype could be changed, `False` if not or if
the new datatype equals the old one.
"""
if role != DTYPE_CHANGE_ROLE or not index.isValid():
return False
if not self.editable():
return False
self.layoutAboutToBeChanged.emit()
dtype = SupportedDtypes.dtype(value)
currentDtype = np.dtype(index.data(role=DTYPE_ROLE))
if dtype is not None:
if dtype != currentDtype:
col = index.column()
#row = self._dataFrame.columns[index.column()]
columnName = self._dataFrame.columns[index.row()]
try:
if dtype == np.dtype('<M8[ns]'):
self._dataFrame[columnName] = self._dataFrame[columnName].apply(pandas.to_datetime)
else:
self._dataFrame[columnName] = self._dataFrame[columnName].astype(dtype)
self.dtypeChanged.emit(index.row(), dtype)
self.layoutChanged.emit()
return True
except Exception as e:
message = 'Could not change datatype %s of column %s to datatype %s' % (currentDtype, columnName, dtype)
self.changeFailed.emit(message)
# self._dataFrame[columnName] = self._dataFrame[columnName].astype(currentDtype)
# self.layoutChanged.emit()
# self.dtypeChanged.emit(columnName)
#raise NotImplementedError, "dtype changing not fully working, original error:\n{}".format(e)
return False
def validate(self, s, pos):
if not s:
# s is emtpy
return (QtGui.QValidator.Acceptable, s, pos)
if self.dtype in SupportedDtypes.strTypes():
return (QtGui.QValidator.Acceptable, s, pos)
elif self.dtype in SupportedDtypes.boolTypes():
match = re.match(self.boolPattern, s)
if match:
return (QtGui.QValidator.Acceptable, s, pos)
else:
return (QtGui.QValidator.Invalid, s, pos)
elif self.dtype in SupportedDtypes.datetimeTypes():
try:
ts = Timestamp(s)
except ValueError, e:
return (QtGui.QValidator.Intermediate, s, pos)
return (QtGui.QValidator.Acceptable, s, pos)
def validate(self, s, pos):
if not s:
# s is emtpy
return (QtGui.QValidator.Acceptable, s, pos)
if self.dtype in SupportedDtypes.strTypes():
return (QtGui.QValidator.Acceptable, s, pos)
elif self.dtype in SupportedDtypes.boolTypes():
match = re.match(self.boolPattern, s)
if match:
return (QtGui.QValidator.Acceptable, s, pos)
else:
return (QtGui.QValidator.Invalid, s, pos)
elif self.dtype in SupportedDtypes.datetimeTypes():
try:
ts = Timestamp(s)
except ValueError, e:
return (QtGui.QValidator.Intermediate, s, pos)
return (QtGui.QValidator.Acceptable, s, pos)
def initUi(self):
self.setModal(True)
self.resize(303, 168)
sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding,
QtWidgets.QSizePolicy.Fixed)
self.setSizePolicy(sizePolicy)
self.verticalLayout = QtWidgets.QVBoxLayout(self)
self.dialogHeading = QtWidgets.QLabel(
self.tr('Add a new attribute column'), self)
self.gridLayout = QtWidgets.QGridLayout()
self.columnNameLineEdit = QtWidgets.QLineEdit(self)
self.columnNameLabel = QtWidgets.QLabel(self.tr('Name'), self)
self.dataTypeComboBox = QtWidgets.QComboBox(self)
self.dataTypeComboBox.addItems(SupportedDtypes.names())
self.columnTypeLabel = QtWidgets.QLabel(self.tr('Type'), self)
self.defaultValueLineEdit = QtWidgets.QLineEdit(self)
self.lineEditValidator = DefaultValueValidator(self)
self.defaultValueLineEdit.setValidator(self.lineEditValidator)
self.defaultValueLabel = QtWidgets.QLabel(self.tr('Inital Value(s)'),
self)
self.gridLayout.addWidget(self.columnNameLabel, 0, 0, 1, 1)
self.gridLayout.addWidget(self.columnNameLineEdit, 0, 1, 1, 1)
self.gridLayout.addWidget(self.columnTypeLabel, 1, 0, 1, 1)
self.gridLayout.addWidget(self.dataTypeComboBox, 1, 1, 1, 1)
self.gridLayout.addWidget(self.defaultValueLabel, 2, 0, 1, 1)
self.gridLayout.addWidget(self.defaultValueLineEdit, 2, 1, 1, 1)
self.buttonBox = QtWidgets.QDialogButtonBox(self)
self.buttonBox.setOrientation(QtCore.Qt.Horizontal)
self.buttonBox.setStandardButtons(QtWidgets.QDialogButtonBox.Cancel
| QtWidgets.QDialogButtonBox.Ok)
self.verticalLayout.addWidget(self.dialogHeading)
self.verticalLayout.addLayout(self.gridLayout)
self.verticalLayout.addWidget(self.buttonBox)
self.buttonBox.accepted.connect(self.accept)
self.buttonBox.rejected.connect(self.reject)
self.dataTypeComboBox.currentIndexChanged.connect(
self.updateValidatorDtype)
self.updateValidatorDtype(self.dataTypeComboBox.currentIndex())
def addDataFrameColumn(self, columnName, dtype, defaultValue):
if not self.editable or dtype not in SupportedDtypes.allTypes():
return False
elements = self.rowCount()
columnPosition = self.columnCount()
newColumn = pandas.Series([defaultValue]*elements, index=self._dataFrame.index, dtype=dtype)
self.beginInsertColumns(QtCore.QModelIndex(), columnPosition - 1, columnPosition - 1)
try:
self._dataFrame.insert(columnPosition, columnName, newColumn, allow_duplicates=False)
except ValueError, e:
# columnName does already exist
return False
def data(self, index, role=Qt.DisplayRole):
"""Retrieve the data stored in the model at the given `index`.
Args:
index (QtCore.QModelIndex): The model index, which points at a
data object.
role (Qt.ItemDataRole, optional): Defaults to `Qt.DisplayRole`. You
have to use different roles to retrieve different data for an
`index`. Accepted roles are `Qt.DisplayRole`, `Qt.EditRole` and
`DTYPE_ROLE`.
Returns:
None if an invalid index is given, the role is not accepted by the
model or the column is greater than `1`.
The column name will be returned if the given column number equals `0`
and the role is either `Qt.DisplayRole` or `Qt.EditRole`.
The datatype will be returned, if the column number equals `1`. The
`Qt.DisplayRole` or `Qt.EditRole` return a human readable, translated
string, whereas the `DTYPE_ROLE` returns the raw data type.
"""
# an index is invalid, if a row or column does not exist or extends
# the bounds of self.columnCount() or self.rowCount()
# therefor a check for col>1 is unnecessary.
if not index.isValid():
return None
col = index.column()
#row = self._dataFrame.columns[index.column()]
columnName = self._dataFrame.columns[index.row()]
columnDtype = self._dataFrame[columnName].dtype
if role == Qt.DisplayRole or role == Qt.EditRole:
if col == 0:
if columnName == index.row():
return index.row()
return columnName
elif col == 1:
return SupportedDtypes.description(columnDtype)
elif role == DTYPE_ROLE:
if col == 1:
return columnDtype
else:
return None
def initUi(self):
self.setModal(True)
self.resize(303, 168)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Expanding, QtGui.QSizePolicy.Fixed)
self.setSizePolicy(sizePolicy)
self.verticalLayout = QtGui.QVBoxLayout(self)
self.dialogHeading = QtGui.QLabel(self.tr('Add a new attribute column'), self)
self.gridLayout = QtGui.QGridLayout()
self.columnNameLineEdit = QtGui.QLineEdit(self)
self.columnNameLabel = QtGui.QLabel(self.tr('Name'), self)
self.dataTypeComboBox = QtGui.QComboBox(self)
self.dataTypeComboBox.addItems(SupportedDtypes.names())
self.columnTypeLabel = QtGui.QLabel(self.tr('Type'), self)
self.defaultValueLineEdit = QtGui.QLineEdit(self)
self.lineEditValidator = DefaultValueValidator(self)
self.defaultValueLineEdit.setValidator(self.lineEditValidator)
self.defaultValueLabel = QtGui.QLabel(self.tr('Inital Value(s)'), self)
self.gridLayout.addWidget(self.columnNameLabel, 0, 0, 1, 1)
self.gridLayout.addWidget(self.columnNameLineEdit, 0, 1, 1, 1)
self.gridLayout.addWidget(self.columnTypeLabel, 1, 0, 1, 1)
self.gridLayout.addWidget(self.dataTypeComboBox, 1, 1, 1, 1)
self.gridLayout.addWidget(self.defaultValueLabel, 2, 0, 1, 1)
self.gridLayout.addWidget(self.defaultValueLineEdit, 2, 1, 1, 1)
self.buttonBox = QtGui.QDialogButtonBox(self)
self.buttonBox.setOrientation(QtCore.Qt.Horizontal)
self.buttonBox.setStandardButtons(QtGui.QDialogButtonBox.Cancel | QtGui.QDialogButtonBox.Ok)
self.verticalLayout.addWidget(self.dialogHeading)
self.verticalLayout.addLayout(self.gridLayout)
self.verticalLayout.addWidget(self.buttonBox)
self.buttonBox.accepted.connect(self.accept)
self.buttonBox.rejected.connect(self.reject)
self.dataTypeComboBox.currentIndexChanged.connect(self.updateValidatorDtype)
self.updateValidatorDtype(self.dataTypeComboBox.currentIndex())
def data(self, index, role=Qt.DisplayRole):
"""Retrieve the data stored in the model at the given `index`.
Args:
index (QtCore.QModelIndex): The model index, which points at a
data object.
role (Qt.ItemDataRole, optional): Defaults to `Qt.DisplayRole`. You
have to use different roles to retrieve different data for an
`index`. Accepted roles are `Qt.DisplayRole`, `Qt.EditRole` and
`DTYPE_ROLE`.
Returns:
None if an invalid index is given, the role is not accepted by the
model or the column is greater than `1`.
The column name will be returned if the given column number equals `0`
and the role is either `Qt.DisplayRole` or `Qt.EditRole`.
The datatype will be returned, if the column number equals `1`. The
`Qt.DisplayRole` or `Qt.EditRole` return a human readable, translated
string, whereas the `DTYPE_ROLE` returns the raw data type.
"""
# an index is invalid, if a row or column does not exist or extends
# the bounds of self.columnCount() or self.rowCount()
# therefor a check for col>1 is unnecessary.
if not index.isValid():
return None
col = index.column()
#row = self._dataFrame.columns[index.column()]
columnName = self._dataFrame.columns[index.row()]
columnDtype = self._dataFrame[columnName].dtype
if role == Qt.DisplayRole or role == Qt.EditRole:
if col == 0:
if columnName == index.row():
return index.row()
return columnName
elif col == 1:
return SupportedDtypes.description(columnDtype)
elif role == DTYPE_ROLE:
if col == 1:
return columnDtype
else:
return None
class PandasCellPayload(MimeDataPayload):
_allowedDtypes = SupportedDtypes.allTypes()
def __init__(self, dfindex, column, value, dtype, parentId):
"""store dataframe information in a pickable object
Args:
dfindex (pandas.index): index of the dragged data.
column (str): name of column to be dragged.
value (object): value on according position.
dtype (pandas dtype): data type of column.
parentId (str): hex(id(...)) of according DataFrameModel.
"""
super(PandasCellPayload, self).__init__()
self.dfindex = dfindex
self.column = column
self.value = value
self.dtype = dtype
self.parentId = parentId
def setAllowedDtypes(self, dtypes):
"""set the allowed dtypes used by the dropped widget to determin if we accept or decline the data.
Defaults to allTypes.
Args:
dtypes(SupportedDtypes type): combination of SupportedDtypes types.
e.x. SupportedDtypes.intTypes() + SupportedDtypes.floatTypes()
"""
self._allowedDtypes = dtypes
def allowedDtypes(self):
"""return allowedDtypes"""
return self._allowedDtypes
def isValid(self):
"""check if the dtype is in allowedDtypes. Used to accept or decline a drop in the view."""
if self.dtype in self._allowedDtypes:
return True
else:
return False
def addDataFrameColumn(self, columnName, dtype, defaultValue):
if not self.editable or dtype not in SupportedDtypes.allTypes():
return False
elements = self.rowCount()
columnPosition = self.columnCount()
newColumn = pandas.Series([defaultValue] * elements,
index=self._dataFrame.index,
dtype=dtype)
self.beginInsertColumns(QtCore.QModelIndex(), columnPosition - 1,
columnPosition - 1)
try:
self._dataFrame.insert(columnPosition,
columnName,
newColumn,
allow_duplicates=False)
except ValueError, e:
# columnName does already exist
return False
def createEditor(self, parent, option, index):
"""Creates an Editor Widget for the given index.
Enables the user to manipulate the displayed data in place. An editor
is created, which performs the change.
The widget used will be a `QComboBox` with all available datatypes in the
`pandas` project.
Args:
parent (QtCore.QWidget): Defines the parent for the created editor.
option (QtGui.QStyleOptionViewItem): contains all the information
that QStyle functions need to draw the items.
index (QtCore.QModelIndex): The item/index which shall be edited.
Returns:
QtGui.QWidget: he widget used to edit the item specified by index
for editing.
"""
combo = QtGui.QComboBox(parent)
combo.addItems(SupportedDtypes.names())
combo.currentIndexChanged.connect(self.currentIndexChanged)
return combo
def createEditor(self, parent, option, index):
"""Creates an Editor Widget for the given index.
Enables the user to manipulate the displayed data in place. An editor
is created, which performs the change.
The widget used will be a `QComboBox` with all available datatypes in the
`pandas` project.
Args:
parent (QtCore.QWidget): Defines the parent for the created editor.
option (QtGui.QStyleOptionViewItem): contains all the information
that QStyle functions need to draw the items.
index (QtCore.QModelIndex): The item/index which shall be edited.
Returns:
QtGui.QWidget: he widget used to edit the item specified by index
for editing.
"""
combo = QtGui.QComboBox(parent)
combo.addItems(SupportedDtypes.names())
combo.currentIndexChanged.connect(self.currentIndexChanged)
return combo
def test_data(self, dataframe):
model = ColumnDtypeModel(dataFrame=dataframe)
index = model.index(0, 0)
# get data for display role
ret = index.data()
assert ret == 'Foo'
# edit role does the same as display role
ret = index.data(Qt.EditRole)
assert ret == 'Foo'
# datatype only defined for column 1
ret = index.data(DTYPE_ROLE)
assert ret == None
# datatype column
index = index.sibling(0, 1)
ret = index.data(DTYPE_ROLE)
assert ret == numpy.dtype(numpy.int64)
# check translation / display text
assert index.data(
) == 'integer (64 bit)' == SupportedDtypes.description(ret)
# column not defined
index = index.sibling(0, 2)
assert index.data(DTYPE_ROLE) == None
# invalid index
index = QtCore.QModelIndex()
assert model.data(index) == None
index = model.index(2, 0)
# get data for display role
ret = index.data()
assert ret == 'Spam'
def test_data(self, dataframe):
model = ColumnDtypeModel(dataFrame=dataframe)
index = model.index(0, 0)
# get data for display role
ret = index.data()
assert ret == 'Foo'
# edit role does the same as display role
ret = index.data(Qt.EditRole)
assert ret == 'Foo'
# datatype only defined for column 1
ret = index.data(DTYPE_ROLE)
assert ret == None
# datatype column
index = index.sibling(0, 1)
ret = index.data(DTYPE_ROLE)
assert ret == numpy.dtype(numpy.int64)
# check translation / display text
assert index.data() == 'integer (64 bit)' == SupportedDtypes.description(ret)
# column not defined
index = index.sibling(0, 2)
assert index.data(DTYPE_ROLE) == None
# invalid index
index = QtCore.QModelIndex()
assert model.data(index) == None
index = model.index(2, 0)
# get data for display role
ret = index.data()
assert ret == 'Spam'
def accept(self):
super(AddAttributesDialog, self).accept()
newColumn = self.columnNameLineEdit.text()
dtype = SupportedDtypes.dtype(self.dataTypeComboBox.currentText())
defaultValue = self.defaultValueLineEdit.text()
try:
if dtype in SupportedDtypes.intTypes() + SupportedDtypes.uintTypes():
defaultValue = int(defaultValue)
elif dtype in SupportedDtypes.floatTypes():
defaultValue = float(defaultValue)
elif dtype in SupportedDtypes.boolTypes():
defaultValue = defaultValue.lower() in ['t', '1']
elif dtype in SupportedDtypes.datetimeTypes():
defaultValue = Timestamp(defaultValue)
if isinstance(defaultValue, NaTType):
defaultValue = Timestamp('')
else:
defaultValue = dtype.type()
except ValueError, e:
defaultValue = dtype.type()
def accept(self):
super(AddAttributesDialog, self).accept()
newColumn = self.columnNameLineEdit.text()
dtype = SupportedDtypes.dtype(self.dataTypeComboBox.currentText())
defaultValue = self.defaultValueLineEdit.text()
try:
if dtype in SupportedDtypes.intTypes() + SupportedDtypes.uintTypes(
):
defaultValue = int(defaultValue)
elif dtype in SupportedDtypes.floatTypes():
defaultValue = float(defaultValue)
elif dtype in SupportedDtypes.boolTypes():
defaultValue = defaultValue.lower() in ['t', '1']
elif dtype in SupportedDtypes.datetimeTypes():
defaultValue = Timestamp(defaultValue)
if isinstance(defaultValue, NaTType):
defaultValue = Timestamp('')
else:
defaultValue = dtype.type()
except ValueError, e:
defaultValue = dtype.type()
def validate(self, s, pos):
if not s:
# s is emtpy
return (QtGui.QValidator.Acceptable, s, pos)
if self.dtype in SupportedDtypes.strTypes():
return (QtGui.QValidator.Acceptable, s, pos)
elif self.dtype in SupportedDtypes.boolTypes():
match = re.match(self.boolPattern, s)
if match:
return (QtGui.QValidator.Acceptable, s, pos)
else:
return (QtGui.QValidator.Invalid, s, pos)
elif self.dtype in SupportedDtypes.datetimeTypes():
try:
ts = Timestamp(s)
except ValueError as e:
return (QtGui.QValidator.Intermediate, s, pos)
return (QtGui.QValidator.Acceptable, s, pos)
else:
dtypeInfo = None
if self.dtype in SupportedDtypes.intTypes():
match = re.search(self.intPattern, s)
if match:
try:
value = int(match.string)
except ValueError as e:
return (QtGui.QValidator.Invalid, s, pos)
dtypeInfo = numpy.iinfo(self.dtype)
elif self.dtype in SupportedDtypes.uintTypes():
match = re.search(self.uintPattern, s)
if match:
try:
value = int(match.string)
except ValueError as e:
return (QtGui.QValidator.Invalid, s, pos)
dtypeInfo = numpy.iinfo(self.dtype)
elif self.dtype in SupportedDtypes.floatTypes():
match = re.search(self.floatPattern, s)
print(match)
if match:
try:
value = float(match.string)
except ValueError as e:
return (QtGui.QValidator.Invalid, s, pos)
dtypeInfo = numpy.finfo(self.dtype)
if dtypeInfo is not None:
if value >= dtypeInfo.min and value <= dtypeInfo.max:
return (QtGui.QValidator.Acceptable, s, pos)
else:
return (QtGui.QValidator.Invalid, s, pos)
else:
return (QtGui.QValidator.Invalid, s, pos)
return (QtGui.QValidator.Invalid, s, pos)
def updateValidatorDtype(self, index):
(dtype, name) = SupportedDtypes.tupleAt(index)
self.defaultValueLineEdit.clear()
self.lineEditValidator.validateType(dtype)
class DataFrameModel(QtCore.QAbstractTableModel):
"""data model for use in QTableView, QListView, QComboBox, etc.
Attributes:
timestampFormat (unicode): formatting string for conversion of timestamps to QtCore.QDateTime.
Used in data method.
sortingAboutToStart (QtCore.pyqtSignal): emitted directly before sorting starts.
sortingFinished (QtCore.pyqtSignal): emitted, when sorting finished.
dtypeChanged (Signal(columnName)): passed from related ColumnDtypeModel
if a columns dtype has changed.
changingDtypeFailed (Signal(columnName, index, dtype)):
passed from related ColumnDtypeModel.
emitted after a column has changed it's data type.
"""
_float_precisions = {
"float16": numpy.finfo(numpy.float16).precision - 2,
"float32": numpy.finfo(numpy.float32).precision - 1,
"float64": numpy.finfo(numpy.float64).precision - 1
}
"""list of int datatypes for easy checking in data() and setData()"""
_intDtypes = SupportedDtypes.intTypes() + SupportedDtypes.uintTypes()
"""list of float datatypes for easy checking in data() and setData()"""
_floatDtypes = SupportedDtypes.floatTypes()
"""list of bool datatypes for easy checking in data() and setData()"""
_boolDtypes = SupportedDtypes.boolTypes()
"""list of datetime datatypes for easy checking in data() and setData()"""
_dateDtypes = SupportedDtypes.datetimeTypes()
_timestampFormat = Qt.ISODate
sortingAboutToStart = Signal()
sortingFinished = Signal()
dtypeChanged = Signal(int, object)
changingDtypeFailed = Signal(object, QtCore.QModelIndex, object)
def __init__(self, dataFrame=None, copyDataFrame=False):
"""the __init__ method.
Args:
dataFrame (pandas.core.frame.DataFrame, optional): initializes the model with given DataFrame.
If none is given an empty DataFrame will be set. defaults to None.
copyDataFrame (bool, optional): create a copy of dataFrame or use it as is. defaults to False.
If you use it as is, you can change it from outside otherwise you have to reset the dataFrame
after external changes.
"""
super(DataFrameModel, self).__init__()
self._dataFrame = pandas.DataFrame()
if dataFrame is not None:
self.setDataFrame(dataFrame, copyDataFrame=copyDataFrame)
self._dataFrameOriginal = None
self._search = DataSearch("nothing", "")
self.editable = False
def dataFrame(self):
"""getter function to _dataFrame. Holds all data.
Note:
It's not implemented with python properties to keep Qt conventions.
"""
return self._dataFrame
def setDataFrame(self, dataFrame, copyDataFrame=False):
"""setter function to _dataFrame. Holds all data.
Note:
It's not implemented with python properties to keep Qt conventions.
Raises:
TypeError: if dataFrame is not of type pandas.core.frame.DataFrame.
Args:
dataFrame (pandas.core.frame.DataFrame): assign dataFrame to _dataFrame. Holds all the data displayed.
copyDataFrame (bool, optional): create a copy of dataFrame or use it as is. defaults to False.
If you use it as is, you can change it from outside otherwise you have to reset the dataFrame
after external changes.
"""
if not isinstance(dataFrame, pandas.core.frame.DataFrame):
raise TypeError("not of type pandas.core.frame.DataFrame")
self.layoutAboutToBeChanged.emit()
if copyDataFrame:
self._dataFrame = dataFrame.copy()
else:
self._dataFrame = dataFrame
self._columnDtypeModel = ColumnDtypeModel(dataFrame)
self._columnDtypeModel.dtypeChanged.connect(self.propagateDtypeChanges)
# self._columnDtypeModel.changingDtypeFailed.connect(
# lambda columnName, index, dtype: self.changingDtypeFailed.emit(columnName, index, dtype)
# )
self.layoutChanged.emit()
@Slot(int, object)
def propagateDtypeChanges(self, column, dtype):
self.dtypeChanged.emit(column, dtype)
@property
def timestampFormat(self):
"""getter to _timestampFormat"""
return self._timestampFormat
@timestampFormat.setter
def timestampFormat(self, timestampFormat):
"""setter to _timestampFormat. Formatting string for conversion of timestamps to QtCore.QDateTime
Raises:
AssertionError: if timestampFormat is not of type unicode.
Args:
timestampFormat (unicode): assign timestampFormat to _timestampFormat.
Formatting string for conversion of timestamps to QtCore.QDateTime. Used in data method.
"""
if not isinstance(timestampFormat, (unicode, )):
raise TypeError('not of type unicode')
#assert isinstance(timestampFormat, unicode) or timestampFormat.__class__.__name__ == "DateFormat", "not of type unicode"
self._timestampFormat = timestampFormat
def headerData(self, section, orientation, role=Qt.DisplayRole):
"""return the header depending on section, orientation and Qt::ItemDataRole
Args:
section (int): For horizontal headers, the section number corresponds to the column number.
Similarly, for vertical headers, the section number corresponds to the row number.
orientation (Qt::Orientations):
role (Qt::ItemDataRole):
Returns:
None if not Qt.DisplayRole
_dataFrame.columns.tolist()[section] if orientation == Qt.Horizontal
section if orientation == Qt.Vertical
None if horizontal orientation and section raises IndexError
"""
if role != Qt.DisplayRole:
return None
if orientation == Qt.Horizontal:
try:
label = self._dataFrame.columns.tolist()[section]
if label == section:
label = section
return label
except (IndexError, ):
return None
elif orientation == Qt.Vertical:
return section
def data(self, index, role=Qt.DisplayRole):
"""return data depending on index, Qt::ItemDataRole and data type of the column.
Args:
index (QtCore.QModelIndex): Index to define column and row you want to return
role (Qt::ItemDataRole): Define which data you want to return.
Returns:
None if index is invalid
None if role is none of: DisplayRole, EditRole, CheckStateRole, DATAFRAME_ROLE
if role DisplayRole:
unmodified _dataFrame value if column dtype is object (string or unicode).
_dataFrame value as int or long if column dtype is in _intDtypes.
_dataFrame value as float if column dtype is in _floatDtypes. Rounds to defined precision (look at: _float16_precision, _float32_precision).
None if column dtype is in _boolDtypes.
QDateTime if column dtype is numpy.timestamp64[ns]. Uses timestampFormat as conversion template.
if role EditRole:
unmodified _dataFrame value if column dtype is object (string or unicode).
_dataFrame value as int or long if column dtype is in _intDtypes.
_dataFrame value as float if column dtype is in _floatDtypes. Rounds to defined precision (look at: _float16_precision, _float32_precision).
_dataFrame value as bool if column dtype is in _boolDtypes.
QDateTime if column dtype is numpy.timestamp64[ns]. Uses timestampFormat as conversion template.
if role CheckStateRole:
Qt.Checked or Qt.Unchecked if dtype is numpy.bool_ otherwise None for all other dtypes.
if role DATAFRAME_ROLE:
unmodified _dataFrame value.
raises TypeError if an unhandled dtype is found in column.
"""
if not index.isValid():
return None
def convertValue(row, col, columnDtype):
value = None
if columnDtype == object:
value = self._dataFrame.ix[row, col]
elif columnDtype in self._floatDtypes:
value = round(float(self._dataFrame.ix[row, col]),
self._float_precisions[str(columnDtype)])
elif columnDtype in self._intDtypes:
value = int(self._dataFrame.ix[row, col])
elif columnDtype in self._boolDtypes:
# TODO this will most likely always be true
# See: http://stackoverflow.com/a/715455
# well no: I am mistaken here, the data is already in the dataframe
# so its already converted to a bool
value = bool(self._dataFrame.ix[row, col])
elif columnDtype in self._dateDtypes:
#print numpy.datetime64(self._dataFrame.ix[row, col])
value = pandas.Timestamp(self._dataFrame.ix[row, col])
value = QtCore.QDateTime.fromString(str(value),
self.timestampFormat)
#print value
# else:
# raise TypeError, "returning unhandled data type"
return value
row = self._dataFrame.index[index.row()]
col = self._dataFrame.columns[index.column()]
columnDtype = self._dataFrame[col].dtype
if role == Qt.DisplayRole:
# return the value if you wanne show True/False as text
if columnDtype == numpy.bool:
result = self._dataFrame.ix[row, col]
else:
result = convertValue(row, col, columnDtype)
elif role == Qt.EditRole:
result = convertValue(row, col, columnDtype)
elif role == Qt.CheckStateRole:
if columnDtype == numpy.bool_:
if convertValue(row, col, columnDtype):
result = Qt.Checked
else:
result = Qt.Unchecked
else:
result = None
elif role == DATAFRAME_ROLE:
result = self._dataFrame.ix[row, col]
else:
result = None
return result
def flags(self, index):
"""Returns the item flags for the given index as ored value, e.x.: Qt.ItemIsUserCheckable | Qt.ItemIsEditable
If a combobox for bool values should pop up ItemIsEditable have to set for bool columns too.
Args:
index (QtCore.QModelIndex): Index to define column and row
Returns:
if column dtype is not boolean Qt.ItemIsSelectable | Qt.ItemIsEnabled | Qt.ItemIsEditable
if column dtype is boolean Qt.ItemIsSelectable | Qt.ItemIsEnabled | Qt.ItemIsUserCheckable
"""
flags = super(DataFrameModel, self).flags(index)
if not self.editable:
return flags
col = self._dataFrame.columns[index.column()]
if self._dataFrame[col].dtype == numpy.bool:
flags |= Qt.ItemIsUserCheckable
else:
# if you want to have a combobox for bool columns set this
flags |= Qt.ItemIsEditable
return flags
def setData(self, index, value, role=Qt.DisplayRole):
"""Set the value to the index position depending on Qt::ItemDataRole and data type of the column
Args:
index (QtCore.QModelIndex): Index to define column and row.
value (object): new value.
role (Qt::ItemDataRole): Use this role to specify what you want to do.
Raises:
TypeError: If the value could not be converted to a known datatype.
Returns:
True if value is changed. Calls layoutChanged after update.
False if value is not different from original value.
"""
if not index.isValid() or not self.editable:
return False
if value != index.data(role):
self.layoutAboutToBeChanged.emit()
row = self._dataFrame.index[index.row()]
col = self._dataFrame.columns[index.column()]
#print 'before change: ', index.data().toUTC(), self._dataFrame.iloc[row][col]
columnDtype = self._dataFrame[col].dtype
if columnDtype == object:
pass
elif columnDtype in self._intDtypes:
dtypeInfo = numpy.iinfo(columnDtype)
if value < dtypeInfo.min:
value = dtypeInfo.min
elif value > dtypeInfo.max:
value = dtypeInfo.max
elif columnDtype in self._floatDtypes:
value = numpy.float64(value).astype(columnDtype)
elif columnDtype in self._boolDtypes:
value = numpy.bool_(value)
elif columnDtype in self._dateDtypes:
# convert the given value to a compatible datetime object.
# if the conversation could not be done, keep the original
# value.
if isinstance(value, QtCore.QDateTime):
value = value.toString(self.timestampFormat)
try:
value = pandas.Timestamp(value)
except ValueError, e:
return False
else:
raise TypeError, "try to set unhandled data type"
self._dataFrame.set_value(row, col, value)
#print 'after change: ', value, self._dataFrame.iloc[row][col]
self.layoutChanged.emit()
return True
else:
match = re.match(self.boolPattern, s)
if match:
return (QtGui.QValidator.Acceptable, s, pos)
else:
return (QtGui.QValidator.Invalid, s, pos)
elif self.dtype in SupportedDtypes.datetimeTypes():
try:
ts = Timestamp(s)
except ValueError, e:
return (QtGui.QValidator.Intermediate, s, pos)
return (QtGui.QValidator.Acceptable, s, pos)
else:
dtypeInfo = None
if self.dtype in SupportedDtypes.intTypes():
match = re.search(self.intPattern, s)
if match:
try:
value = int(match.string)
except ValueError, e:
return (QtGui.QValidator.Invalid, s, pos)
dtypeInfo = numpy.iinfo(self.dtype)
elif self.dtype in SupportedDtypes.uintTypes():
match = re.search(self.uintPattern, s)
if match:
try:
value = int(match.string)
except ValueError, e:
match = re.match(self.boolPattern, s)
if match:
return (QtGui.QValidator.Acceptable, s, pos)
else:
return (QtGui.QValidator.Invalid, s, pos)
elif self.dtype in SupportedDtypes.datetimeTypes():
try:
ts = Timestamp(s)
except ValueError, e:
return (QtGui.QValidator.Intermediate, s, pos)
return (QtGui.QValidator.Acceptable, s, pos)
else:
dtypeInfo = None
if self.dtype in SupportedDtypes.intTypes():
match = re.search(self.intPattern, s)
if match:
try:
value = int(match.string)
except ValueError, e:
return (QtGui.QValidator.Invalid, s, pos)
dtypeInfo = numpy.iinfo(self.dtype)
elif self.dtype in SupportedDtypes.uintTypes():
match = re.search(self.uintPattern, s)
if match:
try:
value = int(match.string)
except ValueError, e:
def updateValidatorDtype(self, index):
(dtype, name) = SupportedDtypes.tupleAt(index)
self.defaultValueLineEdit.clear()
self.lineEditValidator.validateType(dtype)
