```{r echo = FALSE} options(markdown.HTML.options = "toc") ``` # AnalysisPageServer Interactivity Not only does the AnalysisPageServer display your data and plot, it also implements sorting, numeric and text filtering, selecting and tagging points, zoom, full screen mode, and download. Using the example data set this document will walk you through each of these interactions. The interactions are very easy to learn, and you will probably discover many of them just by playing with the example data set. ---------------- ## Working through this guide This is a step-by-step guide. To work your way through it, simply click on this link to open the page in a new window or tab, then follow through the steps of the guide. Or, just read through the guide and look at the screenshots.

When you first open the link, it looks like this:

## Roll-over Rolling over any point in the plot reveals the meta-data associated with the plot.

## Zooming Zooming is done most easily with your mouse roller, which will zoom in/out focusing on the point where your mouse is hovering.

If you get lost then you can always press the `0` key or click on the "reset zoom" button, which is the bottom button from the group of zoom controls (pictured at right). Above the "reset zoom" button are the incremental "zoom in" and "zoom out" buttons which can be used instead of the mouse roller zoom. ## Panning

Once you've zoomed in you might want to move about. If you are in "pan mode" then you can drag the plot to move it around. The mode toggles between "pan mode" and "tag mode" (more on "tag mode" later). "pan mode" is repesented by a 4-way arrow, and "tag mode" by a tag. Whichever button is depressed is the mode that you are in. For example, picture at the right shows "pan mode". If you are in the wrong mode just click on the other button to switch. ## Full screen mode Clicking on the *full screen* button

will expand your plot to fill the whole screen, along with the control buttons. This can be very useful to see more details. Rollover, panning, zooming and selective tagging (more on this later) all work in full screen. Click the full screen mode button or press the `Esc` key to exit full screen.

## Data Table Scroll down the web page and you will see a table of your attached data:

### Column Summaries Roll over the column names to see a quick summary of the contents of the column.

### Sort Click on the sort arrow

to sort the rows of the table based on that column. Click again to reverse sort. This example shows the data reverse sorted on the `y` column:

## Filtering A filter is a selection of a subset of the data. Since there is a correspondence between rows of the data table and points in the plot the filter is a applied to both areas---rows corresponding to points removed from the plot are removed from the table. Filters can be defined based on the values of the data. There are two ways to do this: by clicking the filter icon on the column headings, or using the "Filter Control Area". We'll start with an example using the column headings. Click on the filter icon

to filter the rows of the table based on the content of a column. Simple text filters and numeric filters are available, according to the type of data in that column of your original data frame.

For example, filtering on "red" will include only the rows where the colors field is "red".

Any filter applied to the table is also applied to the plot:

Note that by including the vector of colors in the data frame we can allow the user to filter based on the color of the points. Similarly, by including the `x` and `y` coordinates the user can filter on the position. See the next section for more on this, and also the section on tagging for a more intuitive way of filtering on point position. The control area to the right of the plot displays a summary of how many filters you've applied and how many points remain:

If you click on that you will open up the "Filter Control Area":

Now you can see all of the filters on all the columns. Right now it is just the one filter. You could add another filter, for example on the `x` coordinate:

Now you can see only points with `0 <= x <= 1`. The filter summary updates to show you've applied three filters (`x >= 0` and `x <= 1` count as two separate filters), and as a result are only looking at 6 of the original 100 points. The table is also filtered down to the 6 corresponding rows. To clear the filters just click "Clear". For example, you could turn off just the "red" filter:

And you get points of all the colors, still with the `x` coordinate filter applied:

## Tagging Tagging allows you to add meta-data to the plot. Click either on the "Tag Points" area

, or on the "Tag Mode" button

(If you are following along this tutorial in order you might have to clear the `x` filters from the last section to match this example.) You can then select a field for tagging from the dropdown menu (this is populated with the names of the columns in your data frame), and click "Tag all visible" to add the tags:

The points are annotated with the data from that column of your data frame:

If you change the field then it changes the labels:

The tags are draggable, so you can move them around. Click

to remove the tags.

If you don't want to label all the points, you can select a subset of points to tag. This can be done by clicking on them or highlighting them.

This is what you get:

Once you have some points tagged, if you want to *add more* tags without losing the tags you already made then just hold shift while you click or highlight. Here is the result of *shift*-clicking another point:

## Filtering based on tags Not only do the tags add more information about the elements of your plot, you can also use them to define filters. Click

to hide the rest of the points:

The same points will also be removed from the table. Click

to "release" the filter (restore all the hidden points). ## Download

There are three types of downloads available. Each one will download the data in a way that reflects the current state of filters and tags. To download simply click on the download button (pictured at right) and choose the download you want. 1. `.csv` downloads the data table as a CSV file, which can be opened for example in Microsoft Excel. This file will contain comments about the data being analyzed and the filter applied. 2. `.png` downloads the plot (with current filters and tags) as a PNG file. 2. `.svg` downloads the plot (with current filters and tags) as an SVG file. # Next [Example Servers](ExampleServers.html)