Replaced ipython.org with jupyter.org links in Homepage notebook
"cell_type": "markdown",
"metadata": {},
"source": [
- "HoloViews is a [Python](http://python.org) library that makes analyzing and visualizing scientific or engineering data much simpler, more intuitive, and more easily reproducible. Instead of specifying every step for each plot, HoloViews lets you store your data in an annotated format that is instantly visualizable, with immediate access to both the numeric data *and* its visualization. Examples of how HoloViews is used in Python scripts as well as in live [Jupyter Notebooks](http://ipython.org/notebook/) may be accessed directly from the [holoviews-contrib](https://github.com/ioam/holoviews-contrib) repository. Here is a quick example of HoloViews in action:"
+ "HoloViews is a [Python](http://python.org) library that makes analyzing and visualizing scientific or engineering data much simpler, more intuitive, and more easily reproducible. Instead of specifying every step for each plot, HoloViews lets you store your data in an annotated format that is instantly visualizable, with immediate access to both the numeric data *and* its visualization. Examples of how HoloViews is used in Python scripts as well as in live [Jupyter Notebooks](http://jupyter.org) may be accessed directly from the [holoviews-contrib](http://github.com/ioam/holoviews-contrib) repository. Here is a quick example of HoloViews in action:"
]
},
{
"\n",
"Note that just as the 2D array became a 1D curve automatically by sampling to get the cross section, this entire figure would become a single static frame with no slider bar if you chose a specific ``Y`` value by re-running with ``.select(Y=0.3)`` before ``.cols(2)``. There is nothing in the code above that adds the slider bar explicitly -- it appears automatically, just because there is an additional dimension of data that has not been laid out spatially. Additional sliders would appear if there were other dimensions being varied as well, e.g. for parameter-space explorations.\n",
"\n",
- "This functionality is designed to complement the [IPython/Jupyter Notebook](http://ipython.org/notebook) interface, though it can be used just as well separately. This web page and all the [HoloViews Tutorials](Tutorials/) are runnable notebooks, which allow you to interleave text, Python code, and graphical results easily. With HoloViews, you can put a minimum of code in the notebook (typically one or two lines per subfigure), specifying what you would like to see rather than the details of how it should be plotted. HoloViews makes the IPython Notebook a practical solution for both exploratory research (since viewing nearly any chunk of data just takes a line or two of code) and for long-term [reproducibility](Tutorials/Exporting.html) of the work (because both the code and the visualizations are preserved in the notebook file forever, and the data and publishable figures can both easily be exported to an archive on disk). See the [Tutorials](Tutorials/) for detailed examples, and then start enjoying working with your data!"
+ "This functionality is designed to complement the [IPython/Jupyter Notebook](http://jupyter.org) interface, though it can be used just as well separately. This web page and all the [HoloViews Tutorials](Tutorials/) are runnable notebooks, which allow you to interleave text, Python code, and graphical results easily. With HoloViews, you can put a minimum of code in the notebook (typically one or two lines per subfigure), specifying what you would like to see rather than the details of how it should be plotted. HoloViews makes the IPython Notebook a practical solution for both exploratory research (since viewing nearly any chunk of data just takes a line or two of code) and for long-term [reproducibility](Tutorials/Exporting.html) of the work (because both the code and the visualizations are preserved in the notebook file forever, and the data and publishable figures can both easily be exported to an archive on disk). See the [Tutorials](Tutorials/) for detailed examples, and then start enjoying working with your data!"
]
}
],
