def removeDataFrameRows(self, rows):
"""
Removes rows from the dataframe.
:param rows: (list)
of row indexes to removes.
:return: (bool)
True on success, False on failure.
"""
if not self.editable:
return False
if rows:
position = min(rows)
count = len(rows)
self.beginRemoveRows(QtCore.QModelIndex(), position,
position + count - 1)
removedAny = False
for idx, line in self._dataFrame.iterrows():
if idx in rows:
removedAny = True
self._dataFrame.drop(idx, inplace=True)
if not removedAny:
return False
self._dataFrame.reset_index(inplace=True, drop=True)
self.endRemoveRows()
return True
return False
def removeDataFrameColumns(self, columns):
"""
Removes columns from the dataframe.
:param columns: [(int, str)]
:return: (bool)
True on success, False on failure.
"""
if not self.editable:
return False
if columns:
deleted = 0
errored = False
for (position, name) in columns:
position = position - deleted
if position < 0:
position = 0
self.beginRemoveColumns(QtCore.QModelIndex(), position,
position)
try:
self._dataFrame.drop(name, axis=1, inplace=True)
except ValueError as e:
errored = True
continue
self.endRemoveColumns()
deleted += 1
self.dataChanged.emit()
if errored:
return False
else:
return True
return False
def columnCount(self, index=QtCore.QModelIndex()):
"""returns number of columns
Args:
index (QtCore.QModelIndex, optional): Index to define column and row. defaults to empty QModelIndex
Returns:
number of columns
"""
return len(self.headers)
def rowCount(self, index=QtCore.QModelIndex()):
"""returns number of rows
Args:
index (QtCore.QModelIndex, optional): Index to define column and row. defaults to empty QModelIndex
Returns:
number of rows
"""
return len(self._dataFrame.columns)
def columnCount(self, index=QtCore.QModelIndex()):
"""returns number of columns
Args:
index (QtCore.QModelIndex, optional): Index to define column and row. defaults to empty QModelIndex
Returns:
number of columns
"""
# speed comparison:
# In [23]: %timeit len(df.columns)
# 10000000 loops, best of 3: 108 ns per loop
# In [24]: %timeit df.shape[1]
# 1000000 loops, best of 3: 440 ns per loop
return len(self._dataFrame.columns)
def addDataFrameRows(self, count=1):
"""
Adds rows to the dataframe.
:param count: (int)
The number of rows to add to the dataframe.
:return: (bool)
True on success, False on failure.
"""
# don't allow any gaps in the data rows.
# and always append at the end
if not self.editable:
return False
position = self.rowCount()
if count < 1:
return False
if len(self.dataFrame().columns) == 0:
# log an error message or warning
return False
# Note: This function emits the rowsAboutToBeInserted() signal which
# connected views (or proxies) must handle before the data is
# inserted. Otherwise, the views may end up in an invalid state.
self.beginInsertRows(QtCore.QModelIndex(), position,
position + count - 1)
defaultValues = []
for dtype in self._dataFrame.dtypes:
if dtype.type == numpy.dtype('<M8[ns]'):
val = pandas.Timestamp('')
elif dtype.type == numpy.dtype(object):
val = ''
else:
val = dtype.type()
defaultValues.append(val)
for i in range(count):
self._dataFrame.loc[position + i] = defaultValues
self._dataFrame.reset_index()
self.endInsertRows()
return True
def rowCount(self, index=QtCore.QModelIndex()):
"""returns number of rows
Args:
index (QtCore.QModelIndex, optional): Index to define column and row. defaults to empty QModelIndex
Returns:
number of rows
"""
# len(df.index) is faster, so use it:
# In [12]: %timeit df.shape[0]
# 1000000 loops, best of 3: 437 ns per loop
# In [13]: %timeit len(df.index)
# 10000000 loops, best of 3: 110 ns per loop
# %timeit df.__len__()
# 1000000 loops, best of 3: 215 ns per loop
return len(self._dataFrame.index)
def addDataFrameColumn(self, columnName, dtype=str, defaultValue=None):
"""
Adds a column to the dataframe as long as
the model's editable property is set to True and the
dtype is supported.
:param columnName: str
name of the column.
:param dtype: qtpandas.models.SupportedDtypes option
:param defaultValue: (object)
to default the column's value to, should be the same as the dtype or None
:return: (bool)
True on success, False otherwise.
"""
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 as e:
# columnName does already exist
return False
self.endInsertColumns()
self.propagateDtypeChanges(columnPosition, newColumn.dtype)
return True
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_invalidIndex(self, model):
assert model.setData(QtCore.QModelIndex(), None) == False
def test_invalidIndex(self, model):
assert model.data(QtCore.QModelIndex()) is None
