diff --git a/doc/source/ecosystem.rst b/doc/source/ecosystem.rst index 8fafe8ec9eaa2..0d010b47f393a 100644 --- a/doc/source/ecosystem.rst +++ b/doc/source/ecosystem.rst @@ -93,6 +93,12 @@ targets the IPython Notebook environment. `Plotly’s `__ `Python API `__ enables interactive figures and web shareability. Maps, 2D, 3D, and live-streaming graphs are rendered with WebGL and `D3.js `__. The library supports plotting directly from a pandas DataFrame and cloud-based collaboration. Users of `matplotlib, ggplot for Python, and Seaborn `__ can convert figures into interactive web-based plots. Plots can be drawn in `IPython Notebooks `__ , edited with R or MATLAB, modified in a GUI, or embedded in apps and dashboards. Plotly is free for unlimited sharing, and has `cloud `__, `offline `__, or `on-premise `__ accounts for private use. +`Pandas-Qt `__ +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +Spun off from the main pandas library, the `Pandas-Qt `__ +library enables DataFrame visualization and manipulation in PyQt4 and PySide applications. + .. _ecosystem.ide: IDE diff --git a/doc/source/faq.rst b/doc/source/faq.rst index e5d659cc31606..d23e0ca59254d 100644 --- a/doc/source/faq.rst +++ b/doc/source/faq.rst @@ -110,78 +110,6 @@ details. Visualizing Data in Qt applications ----------------------------------- -.. warning:: - - The ``qt`` support is **deprecated and will be removed in a future version**. - We refer users to the external package `pandas-qt `_. - -There is experimental support for visualizing DataFrames in PyQt4 and PySide -applications. At the moment you can display and edit the values of the cells -in the DataFrame. Qt will take care of displaying just the portion of the -DataFrame that is currently visible and the edits will be immediately saved to -the underlying DataFrame - -To demonstrate this we will create a simple PySide application that will switch -between two editable DataFrames. For this will use the ``DataFrameModel`` class -that handles the access to the DataFrame, and the ``DataFrameWidget``, which is -just a thin layer around the ``QTableView``. - -.. code-block:: python - - import numpy as np - import pandas as pd - from pandas.sandbox.qtpandas import DataFrameModel, DataFrameWidget - from PySide import QtGui, QtCore - - # Or if you use PyQt4: - # from PyQt4 import QtGui, QtCore - - class MainWidget(QtGui.QWidget): - def __init__(self, parent=None): - super(MainWidget, self).__init__(parent) - - # Create two DataFrames - self.df1 = pd.DataFrame(np.arange(9).reshape(3, 3), - columns=['foo', 'bar', 'baz']) - self.df2 = pd.DataFrame({ - 'int': [1, 2, 3], - 'float': [1.5, 2.5, 3.5], - 'string': ['a', 'b', 'c'], - 'nan': [np.nan, np.nan, np.nan] - }, index=['AAA', 'BBB', 'CCC'], - columns=['int', 'float', 'string', 'nan']) - - # Create the widget and set the first DataFrame - self.widget = DataFrameWidget(self.df1) - - # Create the buttons for changing DataFrames - self.button_first = QtGui.QPushButton('First') - self.button_first.clicked.connect(self.on_first_click) - self.button_second = QtGui.QPushButton('Second') - self.button_second.clicked.connect(self.on_second_click) - - # Set the layout - vbox = QtGui.QVBoxLayout() - vbox.addWidget(self.widget) - hbox = QtGui.QHBoxLayout() - hbox.addWidget(self.button_first) - hbox.addWidget(self.button_second) - vbox.addLayout(hbox) - self.setLayout(vbox) - - def on_first_click(self): - '''Sets the first DataFrame''' - self.widget.setDataFrame(self.df1) - - def on_second_click(self): - '''Sets the second DataFrame''' - self.widget.setDataFrame(self.df2) - - if __name__ == '__main__': - import sys - - # Initialize the application - app = QtGui.QApplication(sys.argv) - mw = MainWidget() - mw.show() - app.exec_() +There is no support for such visualization in pandas. However, the external +package `pandas-qt `_ does +provide this functionality. diff --git a/doc/source/whatsnew/v0.19.0.txt b/doc/source/whatsnew/v0.19.0.txt index 0b9695125c0a9..34b70826f2bf3 100644 --- a/doc/source/whatsnew/v0.19.0.txt +++ b/doc/source/whatsnew/v0.19.0.txt @@ -504,6 +504,7 @@ Deprecations Removal of prior version deprecations/changes ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +- The ``pd.sandbox`` module has been removed in favor of the external library ``pandas-qt`` (:issue:`13670`) - ``DataFrame.to_csv()`` has dropped the ``engine`` parameter, as was deprecated in 0.17.1 (:issue:`11274`, :issue:`13419`) - ``DataFrame.to_dict()`` has dropped the ``outtype`` parameter in favor of ``orient`` (:issue:`13627`, :issue:`8486`) - ``pd.Categorical`` has dropped the ``levels`` attribute in favour of ``categories`` (:issue:`8376`) diff --git a/pandas/api/tests/test_api.py b/pandas/api/tests/test_api.py index 3f6c97441d659..0aefdbeae0518 100644 --- a/pandas/api/tests/test_api.py +++ b/pandas/api/tests/test_api.py @@ -28,7 +28,7 @@ class TestPDApi(Base, tm.TestCase): # these are optionally imported based on testing # & need to be ignored - ignored = ['tests', 'rpy', 'sandbox', 'locale'] + ignored = ['tests', 'rpy', 'locale'] # top-level sub-packages lib = ['api', 'compat', 'computation', 'core', diff --git a/pandas/sandbox/__init__.py b/pandas/sandbox/__init__.py deleted file mode 100644 index e69de29bb2d1d..0000000000000 diff --git a/pandas/sandbox/qtpandas.py b/pandas/sandbox/qtpandas.py deleted file mode 100644 index b6af40a0e2156..0000000000000 --- a/pandas/sandbox/qtpandas.py +++ /dev/null @@ -1,145 +0,0 @@ -""" -Easy integration of DataFrame into pyqt framework - -@author: Jev Kuznetsov -""" - -# flake8: noqa - -# GH9615 - -import warnings -warnings.warn("The pandas.sandbox.qtpandas module is deprecated and will be " - "removed in a future version. We refer users to the external package " - "here: https://github.com/datalyze-solutions/pandas-qt") - -try: - from PyQt4.QtCore import QAbstractTableModel, Qt, QVariant, QModelIndex - from PyQt4.QtGui import ( - QApplication, QDialog, QVBoxLayout, QTableView, QWidget) -except ImportError: - from PySide.QtCore import QAbstractTableModel, Qt, QModelIndex - from PySide.QtGui import ( - QApplication, QDialog, QVBoxLayout, QTableView, QWidget) - QVariant = lambda value=None: value - -from pandas import DataFrame, Index - - -class DataFrameModel(QAbstractTableModel): - """ data model for a DataFrame class """ - def __init__(self): - super(DataFrameModel, self).__init__() - self.df = DataFrame() - - def setDataFrame(self, dataFrame): - self.df = dataFrame - - def signalUpdate(self): - """ tell viewers to update their data (this is full update, not - efficient)""" - self.layoutChanged.emit() - - #------------- table display functions ----------------- - def headerData(self, section, orientation, role=Qt.DisplayRole): - if role != Qt.DisplayRole: - return QVariant() - - if orientation == Qt.Horizontal: - try: - return self.df.columns.tolist()[section] - except (IndexError, ): - return QVariant() - elif orientation == Qt.Vertical: - try: - # return self.df.index.tolist() - return self.df.index.tolist()[section] - except (IndexError, ): - return QVariant() - - def data(self, index, role=Qt.DisplayRole): - if role != Qt.DisplayRole: - return QVariant() - - if not index.isValid(): - return QVariant() - - return QVariant(str(self.df.ix[index.row(), index.column()])) - - def flags(self, index): - flags = super(DataFrameModel, self).flags(index) - flags |= Qt.ItemIsEditable - return flags - - def setData(self, index, value, role): - row = self.df.index[index.row()] - col = self.df.columns[index.column()] - if hasattr(value, 'toPyObject'): - # PyQt4 gets a QVariant - value = value.toPyObject() - else: - # PySide gets an unicode - dtype = self.df[col].dtype - if dtype != object: - value = None if value == '' else dtype.type(value) - self.df.set_value(row, col, value) - return True - - def rowCount(self, index=QModelIndex()): - return self.df.shape[0] - - def columnCount(self, index=QModelIndex()): - return self.df.shape[1] - - -class DataFrameWidget(QWidget): - """ a simple widget for using DataFrames in a gui """ - def __init__(self, dataFrame, parent=None): - super(DataFrameWidget, self).__init__(parent) - - self.dataModel = DataFrameModel() - self.dataTable = QTableView() - self.dataTable.setModel(self.dataModel) - - layout = QVBoxLayout() - layout.addWidget(self.dataTable) - self.setLayout(layout) - # Set DataFrame - self.setDataFrame(dataFrame) - - def setDataFrame(self, dataFrame): - self.dataModel.setDataFrame(dataFrame) - self.dataModel.signalUpdate() - self.dataTable.resizeColumnsToContents() - -#-----------------stand alone test code - - -def testDf(): - """ creates test dataframe """ - data = {'int': [1, 2, 3], 'float': [1.5, 2.5, 3.5], - 'string': ['a', 'b', 'c'], 'nan': [np.nan, np.nan, np.nan]} - return DataFrame(data, index=Index(['AAA', 'BBB', 'CCC']), - columns=['int', 'float', 'string', 'nan']) - - -class Form(QDialog): - def __init__(self, parent=None): - super(Form, self).__init__(parent) - - df = testDf() # make up some data - widget = DataFrameWidget(df) - widget.resizeColumnsToContents() - - layout = QVBoxLayout() - layout.addWidget(widget) - self.setLayout(layout) - -if __name__ == '__main__': - import sys - import numpy as np - - app = QApplication(sys.argv) - form = Form() - form.show() - app.exec_() diff --git a/setup.py b/setup.py index c77ca4d9e60fe..0bff49c4976b8 100755 --- a/setup.py +++ b/setup.py @@ -560,7 +560,6 @@ def pxd(name): 'pandas.io.sas', 'pandas.formats', 'pandas.rpy', - 'pandas.sandbox', 'pandas.sparse', 'pandas.sparse.tests', 'pandas.stats',