Any simple solution to aligning custom shapes in a table using tableau? I don't have any text in the table cell, only the custom shapes based on conditions. The only solution I can find is to create two dummy variables with two axis and adjust by increasing or decreasing characters in a string/text. I'm kinda surprised there isn't a simpler way to do this in tableau. Did I miss something here?
Related
I'm trying to create a geochoropleth that maps subregions, but also includes outlines of larger regions. (You can think of it like mapping counties, but then wanting to include thicker outlines of states). Not all subregions are part of larger regions that need to be outlined. (Most aren't.) You can see an example of what I'm trying to replicate here:
What's the best way to add this regional outline to my map? I've tried keeping the regions and subregions as two separate files, with two overlaygeojsons calls in my geochoropleth call (with added d3 styling to change the fill and stroke to just be an outline). But when I do - the projection of the regional outline layer is strangely offset from the lower one.
I've also considered having both sets of boundaries in just the one geojson. However, I wasn't sure how to work with this.
While it would be nice to be able to mouseover the boundaries of the larger regions and get a tooltip before crossing over into the individual subregions and getting their tooltips, this isn't a must. I could live with just outlines around the regions. Please advise on the best way to do this. Happy to provide more detail, and thanks so much!
EDIT: I discovered that I had a misplaced transform tag which is what offset the second layer. Fixed now!
This is half a question, as I have this 'sort of' thought through. Still, I'd like to have some confirmation. Here it goes:
From what I've seen so far, a group holds all the information necessary for a plot. Let's imagine a bar chart for the 'canonical' dc data array. We define a dimension on type and then a group. The group data will give us all the necessary coordinates for drawing the bars.
Why do we need dimensions, then? Is this for plotting, or just for keeping track of the filters and dynamically updating the chart?
This is only half an answer. :)
Yes, there is some redundancy between dimensions and groups for sure.
The group key function needs to be a refinement of (and must be consistent with) the dimension key function.
There's only one place where I've found it's helpful to refine the group key function more than the dimension key function: when the dimension is time and the group is some quantization of time like months or hours. Otherwise there is no need to specify the group key function at all. I haven't seen too many people create sets of time-series charts where different charts are quantized at different levels, so I am not sure if that's the motivation.
Filtering happens through the dimension, not the group, and a group does not observe its dimension's filters - so you might want them to be different objects so you that you can optionally have the chart respond to its own filters. That's pretty rare, though - usually a chart will read data from a group on the dimension it filters.
Any other reasons? Please add to this list!
in one of my projects, I would like to create heatmap of user clicks. I was searching a while and found this library - http://www.patrick-wied.at/static/heatmapjs/examples.html . That is basically exactly what I would like to make. I would like to create heatmap in SVG, if possible, that is only difference.
I would like to create my own heatmap and I'm just wondering how to do that. I have XY clicks position. Each click has mostly different XY position, but there can be exceptions time to time, a few clicks can have the came XY position.
I found a few solutions based on grid on website, where you have to check which clicks belong into the same column in this grid and according to these informations you are able to fill the most clicked columns with red or orange and so on. But it seems a little bit complicated to me and maybe slower for bigger grids.
So I'm wondering if there is another solution how to "calculate" heatmap colors or I would like to know the main idea used in library above.
Many thanks
To make this kind of heat map, you need some kind of writable array (or, as you put it, a "grid"). User clicks are added onto this array in a cumulative fashion, by adding a small "filter" sub-array (aligned around each click) to the writable array.
Unfortunately, this "grid" method seems to be the easiest, simplest way to get that kind of smooth, blobby appearance. Fortunately, this kind of operation is well-supported by software and hardware, under the name "computer graphics".
When considered as a computer graphics operation, the writable array is called an "accumulation buffer". The filter is what gives you the nice blobby appearance, even with a relatively small number of clicks -- you can tweak the size of the filter according to the needs of your application.
After accumulating the user clicks, you will need to convert from the raw accumulated values to some kind of visible color scale. This may involve looking through the entire accumulation buffer to find the largest value, and mapping your chosen color scale accordingly. Alternately, you could adjust your scale according to the number of mouse clicks, or (as in the demo you linked to) just choose a fixed scale regardless of the content of the buffer.
Finally, I should mention that SVG is not well-adapted to representing this kind of graphic. It should probably be saved as some kind of image file (.jpg or .png) instead.
I need some advice about how to improve the visualization of cartographic information.
User can select different species and the webmapping app shows its geographical distribution (polygonal degree cells), each specie with a range of color (e.g darker orange color where we find more info, lighter orange where less info).
The problem is when more than one specie overlaps. What I am currently doing is just to calculate the additive color mix of two colors using http://www.xarg.org/project/jquery-color-plugin-xcolor/
As you can see in the image below, the resulting color where two species overlap (mixed blue and yellow) is not intuitive at all.
Someone has any idea or knows similar tools where to get inspiration? for creating the polygons I use d3.js, so if more complex SVG features have to be created I can give a try.
Some ideas I had are...
1) The more data on a polygon, the thicker the border (or each part of the border with its corresponding color)
2) add a label at the center of polygon saying how many species overlap.
3) Divide polygon in different parts, each one with corresponding species color.
thanks in advance,
Pere
My suggestion is something along the lines of option #3 that you listed, with a twist. Rather painting the entire cell with species colors, place a dot in each cell, one for each species. You can vary the color of each dot in the same way that you currently are: darker for more, ligher for less. This doesn't require you to blend colors, and it will expose more of your map to provide more context to the data. I'd try this approach with the border of the cell and without, and see which one works best.
Your visualization might also benefit from some interactivity. A tooltip providing more detailed information and perhaps a further breakdown of information could be displayed when the user hovers his mouse over each cell.
All of this is very subjective. However one thing's for sure: when you're dealing with multi-dimensional data as you are, the less you project dimensions down onto the same visual/perceptual axis, the better. I've seen some examples of "4-dimensional heatmaps" succeed in doing this (here's an example of visualizing latency on a heatmap, identifying different sources with different colors), but I don't think any attempt's made to combine colors.
My initial thoughts about what you are trying to create (a customized variant of a heat map for a slightly crowded data set, I believe:
One strategy is to employ a formula suggested for
n + 1
with regards to breaks in bin spacing. This causes me some concern regarding how many outliers your set has.
Equally-spaced breaks are ideal for compact data sets without
outliers. In many real data sets, especially proteomics data sets,
outliers can make this representation less effective.
One suggestion I have would be to consider the idea of adding some filters to your categories if you have not yet. This would allow slimming down the rendered data for faster reading by the user.
another solution would be to use something like (Comprehensive) R
or maybe even DanteR
Tutorial in displaying mass spectrometry-based proteomic data using heat maps
(Particularly worth noting I felt, was 'Color mapping'.)
I need the user to set a number of percentage values which should always add up to 100%. What are standard ways to archieve this? I came up with the following:
1) have a standard slider control for each value you need to set. Moving one slider will automatically adjust all the others so the sum will always come out as 100%. You can fix inidividual sliders with a checkbox displayed next to it. Only the remaining, "free", sliders will be adjustable.
Pro: consists entirely of standard widgets users already know
Con: lots of widgets, lots of screen real estate used, looks ugly when you have lots of sliders and thus low percentage values, normalization to 100% isn't immediately obvious.
2) have a slider control with several sliding knobs.
Pro: normalization is implicit and obvious because the length of the slider is fixed, relative weight is easy to see at a glance
Con: non-standard, knobs can easily overlap each other, knobs aren't easy to fix, no obvious place to put a text/number representation for each interval/percentage
3) display a standard pie chart.
Pro: normalization is implicit and obvious, relative weight is easy to see
Con: non-standard for interactive use, hard to make intuitive slice resizing work, no place to put a text/number representation for each slice
4) ... ?
I'm not happy with either of these hence my question here. Any better ideas? I'm dealing with 3-10 individual percentage values on a rich windows client (i.e. not web).
cheers,
Sören
What about vertical sliders? Like a sound mixer. I think it looks a lot better than a list of 10 horizontal sliders.
Or fixed width bar with several sliders on them, a bit like the gradient control of Photoshop if you know it.
Similar to the timeline idea, how about a slider like the partitioning interface in GParted or similar disk partitioning tools?
You could display the percentage values and actual numbers above the dynamically resizing bars to allow the user to edit them numerically instead of using the sliders if they want to configure it manually.
How about a time line view; (gantt chart) kind of like in Microsoft Expression Blend or in flash where you have multiple layers for each action and each action can be within a range on the scale from 0 to 100.