Removal of dead links to tutorials in examples

examples/reference/elements/bokeh/Area.ipynb

@@ -30,7 +30,7 @@
    "source": [
     "``Area`` elements are ``Curve`` elements where the area below the line is filled. Like ``Curve`` elements, ``Area`` elements are used to display the development of quantitative values over an interval or time period. ``Area`` Elements may also be stacked to display multiple data series in a cumulative fashion over the value dimension.\n",
     "\n",
-    "The data of an ``Area`` Element should be tabular with one key dimension representing the samples over the interval or the timeseries and one or two value dimensions. A single value dimension will fill the area between the curve and the x-axis, while two value dimensions will fill the area between the curves. See the [Columnar Data Tutorial](../Tutorials/Columnar_Data.ipynb) for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays."
+    "The data of an ``Area`` Element should be tabular with one key dimension representing the samples over the interval or the timeseries and one or two value dimensions. A single value dimension will fill the area between the curve and the x-axis, while two value dimensions will fill the area between the curves. See the [Tabular Datasets](../../../user_guide/07-Tabular_Datasets.ipynb) user guide for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays."
    ]
   },
   {

examples/reference/elements/bokeh/Bars.ipynb

@@ -30,7 +30,7 @@
    "source": [
     "The ``Bars`` Element uses bars to show discrete, numerical comparisons across categories. One axis of the chart shows the specific categories being compared and the other axis represents a continuous value.\n",
     "\n",
-    "Bars may also be stacked by supplying a second key dimensions representing sub-categories. Therefore the ``Bars`` Element expects a tabular data format with one or two key dimensions and one value dimension. See the [Columnar Data Tutorial](../Tutorials/Columnar_Data.ipynb) for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays."
+    "Bars may also be stacked by supplying a second key dimensions representing sub-categories. Therefore the ``Bars`` Element expects a tabular data format with one or two key dimensions and one value dimension. See the [Tabular Datasets](../../../user_guide/07-Tabular_Datasets.ipynb) user guide for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays."
    ]
   },
   {

examples/reference/elements/bokeh/BoxWhisker.ipynb

@@ -30,7 +30,7 @@
    "source": [
     "A ``BoxWhisker`` Element is a quick way of visually summarizing one or more groups of numerical data through their quartiles. \n",
     "\n",
-    "The data of a ``BoxWhisker`` Element may have any number of key dimensions representing the grouping of the value dimension and a single value dimensions representing the distribution of values within each group. See the [Columnar Data Tutorial](../Tutorials/Columnar_Data.ipynb) for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays."
+    "The data of a ``BoxWhisker`` Element may have any number of key dimensions representing the grouping of the value dimension and a single value dimensions representing the distribution of values within each group. See the [Tabular Datasets](../../../user_guide/07-Tabular_Datasets.ipynb) user guide for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays."
    ]
   },
   {

examples/reference/elements/bokeh/Curve.ipynb

@@ -28,7 +28,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "``Curve`` Elements are used to display quantitative values over a continuous interval or time span. They accept tabular data with one key dimension representing the samples along the x-axis and one value dimension of the height of the curve at for each sample. See the [Columnar Data Tutorial](../Tutorials/Columnar_Data.ipynb) for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays."
+    "``Curve`` Elements are used to display quantitative values over a continuous interval or time span. They accept tabular data with one key dimension representing the samples along the x-axis and one value dimension of the height of the curve at for each sample. See the [Tabular Datasets](../../../user_guide/07-Tabular_Datasets.ipynb) user guide for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays."
    ]
   },
   {

examples/reference/elements/bokeh/ErrorBars.ipynb

@@ -30,7 +30,7 @@
    "source": [
     "``ErrorBars`` provide a visual indicator for the variability of the plotted data on a graph. They are usually applied on top of other plots such as scatter, curve or bar plots to indicate the variability in each sample. \n",
     "\n",
-    "``ErrorBars`` may be used to represent symmetric error or asymmetric error. An ``ErrorBars`` Element must have one key dimensions representing the samples along the x-axis and two or three value dimensions representing the value of the sample and positive and negative error values associated with that sample. See the [Columnar Data Tutorial](../Tutorials/Columnar_Data.ipynb) for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays."
+    "``ErrorBars`` may be used to represent symmetric error or asymmetric error. An ``ErrorBars`` Element must have one key dimensions representing the samples along the x-axis and two or three value dimensions representing the value of the sample and positive and negative error values associated with that sample. See the [Tabular Datasets](../../../user_guide/07-Tabular_Datasets.ipynb) user guide for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays."
    ]
   },
   {

examples/reference/elements/bokeh/HSV.ipynb

@@ -30,7 +30,7 @@
    "source": [
     "HoloViews makes it trivial to  work in any color space that can be converted to ``RGB`` by making a simple subclass of ``RGB`` as appropriate. For instance, we also provide the  HSV (hue, saturation, value) color space, which is useful for plotting cyclic data (as the Hue) along with two additional dimensions (controlling the saturation and value of the color, respectively).\n",
     "\n",
-    "Like other raster based Element types ``HSV`` accepts gridded data, which may be supplied as a simple array ``NxMx3`` ndarray representing hue, saturation and value channels along with bounds or explicit array coordinates. See the [Gridded Data Tutorial](../doc/Gridded_Data.ipynb) tutorial to see the accepted data formats."
+    "Like other raster based Element types ``HSV`` accepts gridded data, which may be supplied as a simple array ``NxMx3`` ndarray representing hue, saturation and value channels along with bounds or explicit array coordinates. See the [Gridded Datasets](../../../user_guide/08-Gridded_Datasets.ipynb) user guide to see the accepted data formats."
    ]
   },
   {

examples/reference/elements/bokeh/Spread.ipynb

@@ -28,7 +28,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "``Spread`` elements have the same data format as the [``ErrorBars``](ErrorBars.ipynb) element, namely x- and y-values with associated symmetric or asymmetric errors, but are interpreted as samples from a continuous distribution (just as ``Curve`` is the continuous version of ``Scatter``).  These are often paired with an overlaid ``Curve`` to show an average trend along with a corresponding spread of values; see the [Columnar Data tutorial](Columnar_Data.ipynb) for examples. \n",
+    "``Spread`` elements have the same data format as the [``ErrorBars``](ErrorBars.ipynb) element, namely x- and y-values with associated symmetric or asymmetric errors, but are interpreted as samples from a continuous distribution (just as ``Curve`` is the continuous version of ``Scatter``).  These are often paired with an overlaid ``Curve`` to show an average trend along with a corresponding spread of values; see the [Tabular Datasets](../../../user_guide/07-Tabular_Datasets.ipynb) user guide for examples. \n",
     "\n",
     "Note that as the ``Spread`` element is used to add information to a plot (typically a ``Curve``) the default alpha value is less that one, making it partially transparent. \n",
     "\n",

examples/reference/elements/bokeh/Table.ipynb

@@ -115,7 +115,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "For more extended usage of table conversion see the [Columnar Data](Columnnar_Data.ipynb) and [Pandas Conversion](Pandas_Conversion.ipynb) Tutorials."
+    "For more extended usage of table conversion see the [Tabular Data](../../../user_guide/07-Tabular_Datasets.ipynb) user guide."
    ]
   }
  ],

examples/reference/elements/matplotlib/Area.ipynb

@@ -30,7 +30,7 @@
    "source": [
     "``Area`` elements are ``Curve`` elements where the area below the line is filled. Like ``Curve`` elements, ``Area`` elements are used to display the development of quantitative values over an interval or time period. ``Area`` Elements may also be stacked to display multiple data series in a cumulative fashion over the value dimension.\n",
     "\n",
-    "The data of an ``Area`` Element should be tabular with one key dimension representing the samples over the interval or the timeseries and one or two value dimensions. A single value dimension will fill the area between the curve and the x-axis, while two value dimensions will fill the area between the curves. See the [Columnar Data Tutorial](../Tutorials/Columnar_Data.ipynb) for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays."
+    "The data of an ``Area`` Element should be tabular with one key dimension representing the samples over the interval or the timeseries and one or two value dimensions. A single value dimension will fill the area between the curve and the x-axis, while two value dimensions will fill the area between the curves. See the [Tabular Datasets](../../../user_guide/07-Tabular_Datasets.ipynb) user guide for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays."
    ]
   },
   {

examples/reference/elements/matplotlib/Bars.ipynb

@@ -30,7 +30,7 @@
    "source": [
     "The ``Bars`` Element uses bars to show discrete, numerical comparisons across categories. One axis of the chart shows the specific categories being compared and the other axis represents a continuous value.\n",
     "\n",
-    "Bars may also be stacked by supplying a second key dimensions representing sub-categories. Therefore the ``Bars`` Element expects a tabular data format with one or two key dimensions and one value dimension. See the [Columnar Data Tutorial](../Tutorials/Columnar_Data.ipynb) for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays."
+    "Bars may also be stacked by supplying a second key dimensions representing sub-categories. Therefore the ``Bars`` Element expects a tabular data format with one or two key dimensions and one value dimension. See the [Tabular Datasets](../../../user_guide/07-Tabular_Datasets.ipynb) user guide for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays."
    ]
   },
   {

examples/reference/elements/matplotlib/BoxWhisker.ipynb

@@ -30,7 +30,7 @@
    "source": [
     "A ``BoxWhisker`` Element is a quick way of visually summarizing one or more groups of numerical data through their quartiles. \n",
     "\n",
-    "The data of a ``BoxWhisker`` Element may have any number of key dimensions representing the grouping of the value dimension and a single value dimensions representing the distribution of values within each group. See the [Columnar Data Tutorial](../Tutorials/Columnar_Data.ipynb) for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays."
+    "The data of a ``BoxWhisker`` Element may have any number of key dimensions representing the grouping of the value dimension and a single value dimensions representing the distribution of values within each group. See the [Tabular Datasets](../../../user_guide/07-Tabular_Datasets.ipynb) user guide for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays."
    ]
   },
   {

examples/reference/elements/matplotlib/Curve.ipynb

@@ -28,7 +28,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "``Curve`` Elements are used to display quantitative values over a continuous interval or time span. They accept tabular data with one key dimension representing the samples along the x-axis and one value dimension of the height of the curve at for each sample. See the [Columnar Data Tutorial](../Tutorials/Columnar_Data.ipynb) for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays."
+    "``Curve`` Elements are used to display quantitative values over a continuous interval or time span. They accept tabular data with one key dimension representing the samples along the x-axis and one value dimension of the height of the curve at for each sample. See the [Tabular Datasets](../../../user_guide/07-Tabular_Datasets.ipynb) user guide for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays."
    ]
   },
   {

examples/reference/elements/matplotlib/ErrorBars.ipynb

@@ -30,7 +30,7 @@
    "source": [
     "``ErrorBars`` provide a visual indicator for the variability of the plotted data on a graph. They are usually applied on top of other plots such as scatter, curve or bar plots to indicate the variability in each sample. \n",
     "\n",
-    "``ErrorBars`` may be used to represent symmetric error or asymmetric error. An ``ErrorBars`` Element must have one key dimensions representing the samples along the x-axis and two or three value dimensions representing the value of the sample and positive and negative error values associated with that sample. See the [Columnar Data Tutorial](../Tutorials/Columnar_Data.ipynb) for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays."
+    "``ErrorBars`` may be used to represent symmetric error or asymmetric error. An ``ErrorBars`` Element must have one key dimensions representing the samples along the x-axis and two or three value dimensions representing the value of the sample and positive and negative error values associated with that sample. See the [Tabular Datasets](../../../user_guide/07-Tabular_Datasets.ipynb) user guide for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays."
    ]
   },
   {

examples/reference/elements/matplotlib/HSV.ipynb

@@ -30,7 +30,7 @@
    "source": [
     "HoloViews makes it trivial to  work in any color space that can be converted to ``RGB`` by making a simple subclass of ``RGB`` as appropriate. For instance, we also provide the  HSV (hue, saturation, value) color space, which is useful for plotting cyclic data (as the Hue) along with two additional dimensions (controlling the saturation and value of the color, respectively).\n",
     "\n",
-    "Like other raster based Element types ``HSV`` accepts gridded data, which may be supplied as a simple array ``NxMx3`` ndarray representing hue, saturation and value channels along with bounds or explicit array coordinates. See the [Gridded Data Tutorial](../doc/Gridded_Data.ipynb) tutorial to see the accepted data formats."
+    "Like other raster based Element types ``HSV`` accepts gridded data, which may be supplied as a simple array ``NxMx3`` ndarray representing hue, saturation and value channels along with bounds or explicit array coordinates. See the [Gridded Datasets](../../../user_guide/08-Gridded_Datasets.ipynb) user guide to see the accepted data formats."
    ]
   },
   {

examples/reference/elements/matplotlib/Spread.ipynb

@@ -28,7 +28,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "``Spread`` elements have the same data format as the [``ErrorBars``](ErrorBars.ipynb) element, namely x- and y-values with associated symmetric or asymmetric errors, but are interpreted as samples from a continuous distribution (just as ``Curve`` is the continuous version of ``Scatter``).  These are often paired with an overlaid ``Curve`` to show an average trend along with a corresponding spread of values; see the [Columnar Data tutorial](Columnar_Data.ipynb) for examples.\n",
+    "``Spread`` elements have the same data format as the [``ErrorBars``](ErrorBars.ipynb) element, namely x- and y-values with associated symmetric or asymmetric errors, but are interpreted as samples from a continuous distribution (just as ``Curve`` is the continuous version of ``Scatter``).  These are often paired with an overlaid ``Curve`` to show an average trend along with a corresponding spread of values; see the [Tabular Datasets](../../../user_guide/07-Tabular_Datasets.ipynb) user guide for examples.\n",
     "\n",
     "Note that as the ``Spread`` element is used to add information to a plot (typically a ``Curve``) the default alpha value is less that one, making it partially transparent. \n",
     "\n",

examples/reference/elements/matplotlib/Table.ipynb

@@ -113,7 +113,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "For more extended usage of table conversion see the [Columnar Data](Columnnar_Data.ipynb) and [Pandas Conversion](Pandas_Conversion.ipynb) Tutorials."
+    "For more extended usage of table conversion see the [Tabular Data](../../../user_guide/07-Tabular_Datasets.ipynb) user guide."
    ]
   }
  ],

examples/reference/elements/plotly/BoxWhiskers.ipynb

@@ -30,7 +30,7 @@
    "source": [
     "A ``BoxWhisker`` Element is a quick way of visually summarizing one or more groups of numerical data through their quartiles. \n",
     "\n",
-    "The data of a ``BoxWhisker`` Element may have any number of key dimensions representing the grouping of the value dimension and a single value dimensions representing the distribution of values within each group. See the [Columnar Data Tutorial](../Tutorials/Columnar_Data.ipynb) for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays."
+    "The data of a ``BoxWhisker`` Element may have any number of key dimensions representing the grouping of the value dimension and a single value dimensions representing the distribution of values within each group. See the [Tabular Datasets](../../../user_guide/07-Tabular_Datasets.ipynb) user guide for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays."
    ]
   },
   {

examples/reference/elements/plotly/Curve.ipynb

@@ -28,7 +28,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "``Curve`` Elements are used to display quantitative values over a continuous interval or time span. They accept tabular data with one key dimension representing the samples along the x-axis and one value dimension of the height of the curve at for each sample. See the [Columnar Data Tutorial](../Tutorials/Columnar_Data.ipynb) for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays."
+    "``Curve`` Elements are used to display quantitative values over a continuous interval or time span. They accept tabular data with one key dimension representing the samples along the x-axis and one value dimension of the height of the curve at for each sample. See the [Tabular Datasets](../../../user_guide/07-Tabular_Datasets.ipynb) user guide for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays."
    ]
   },
   {

examples/reference/elements/plotly/ErrorBars.ipynb

@@ -30,7 +30,7 @@
    "source": [
     "``ErrorBars`` provide a visual indicator for the variability of the plotted data on a graph. They are usually applied on top of other plots such as scatter, curve or bar plots to indicate the variability in each sample. \n",
     "\n",
-    "``ErrorBars`` may be used to represent symmetric error or asymmetric error. An ``ErrorBars`` Element must have one key dimensions representing the samples along the x-axis and two or three value dimensions representing the value of the sample and positive and negative error values associated with that sample. See the [Columnar Data Tutorial](../Tutorials/Columnar_Data.ipynb) for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays."
+    "``ErrorBars`` may be used to represent symmetric error or asymmetric error. An ``ErrorBars`` Element must have one key dimensions representing the samples along the x-axis and two or three value dimensions representing the value of the sample and positive and negative error values associated with that sample. See the [Tabular Datasets](../../../user_guide/07-Tabular_Datasets.ipynb) user guide for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays."
    ]
   },
   {