CLN: removed pandas.sandbox

[ci skip]

Author: gfyoung

doc/source/ecosystem.rst

@@ -93,6 +93,12 @@ targets the IPython Notebook environment.
 
 `Plotly’s <https://plot.ly/>`__ `Python API <https://plot.ly/python/>`__ enables interactive figures and web shareability. Maps, 2D, 3D, and live-streaming graphs are rendered with WebGL and `D3.js <http://d3js.org/>`__. The library supports plotting directly from a pandas DataFrame and cloud-based collaboration. Users of `matplotlib, ggplot for Python, and Seaborn <https://plot.ly/python/matplotlib-to-plotly-tutorial/>`__ can convert figures into interactive web-based plots. Plots can be drawn in `IPython Notebooks <https://plot.ly/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 <https://plot.ly/product/plans/>`__, `offline <https://plot.ly/python/offline/>`__, or `on-premise <https://plot.ly/product/enterprise/>`__ accounts for private use.
 
+`Pandas-Qt <https://github.com/datalyze-solutions/pandas-qt>`__
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Spun off from the main pandas library, the `Pandas-Qt <https://github.com/datalyze-solutions/pandas-qt>`__
+library enables DataFrame visualization and manipulation in PyQt4 and PySide applications.
+
 .. _ecosystem.ide:
 
 IDE

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 <https://github.com/datalyze-solutions/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 <https://github.com/datalyze-solutions/pandas-qt>`_ does
+provide this functionality.

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`)

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',

pandas/sandbox/__init__.py

@@ -560,7 +560,6 @@ def pxd(name):
                 'pandas.io.sas',
                 'pandas.formats',
                 'pandas.rpy',
-                'pandas.sandbox',
                 'pandas.sparse',
                 'pandas.sparse.tests',
                 'pandas.stats',