I have a data matrix with 20 columns.
I am easily able to create the heatmap and determine a color scale.
HOWEVER, I want to create a single heatmap- where specific columns have specific color scales
I want columns 1,3,5,7,9,11,13,15,17,19 to be one color scale.
and then columns 2,4,6,8,10,12,14,16,18,20 to be another color scale.
They would ultimately be the same scale.. 0 to 1. but i want a constrast between the columns because they represent two different groups.
Related
I have a few hundred images that I would like to have a user manually sort along two axes. Each row represents a users perceived nominal label, eg red, orange, yellow, green, ... The images in a row are ordered according to some feature perceived by the user (eg brightness). So given an image the person sorting should be able to determine which row it belongs to and which two images it should be between in the row and insert it there.
Initially I tried using Google sheets and loading the images into cells in the spreadsheet. The problem I encountered are the images are really low resolution and Google sheets applies some blending to the pixels (eg linear?, bicubic?) which made understanding the images too difficult for my user. If I could load an image and have it resize using the nearest pixel color I think it would be fine.
I have looked at some photo organizing software, the closest feature I can find is organizing photos based on geo-coordinates onto a 2D map, which isn't intuitive for my user.
I suppose I could create a webapp that the user could assign a row and column too, but it seems like there should be an easier way.
The intent is to apply machine learning on the provided labels so that we can automatically sort larger datasets, so it would be great if the solution could be used with machine provided metadata, which could then be visually inspected for accuracy.
What will be a good way in a scatter chart to have different point/symbol sizes?
We want to make the scatter point sizes larger based on count of same record value. Currently we use http://dc-js.github.io/dc.js/examples/scatter-brushing.html which has a single point when we have data of same values controlled by symbolSize.
We want the symbolSize to vary based on the count of record values.More the data of same value larger the point size.
I am looking for something like the c3.js jsfiddle example in Scatter plot size on "tooltip" .
I'm trying to reduce the number of points in a DC.js line chart to improve performance. The docs lead me to believe xUnits() is the way to do this:
The coordinate grid chart uses the xUnits function to calculate the number of data projections on x axis such as the number of bars for a bar chart or the number of dots for a line chart.
but xUnits does not even seem to be used:
http://jsfiddle.net/m5tguakf/2/
What am I doing wrong?
The number of points is actually determined by crossfilter - dc.js doesn't do any aggregation on its own, so it has no way to add or reduce the number of points.
That documentation may be misleading - it doesn't alter the shape of the data. xUnits is really just needed for dc.js to know the number of elements it is going to draw. It's used for two purposes:
to determine the width of bars or box-plots
to know whether the x scale is ordinal or quantitative
Could dc.js just count the number of points in the crossfilter group? Perhaps.
Anyway, to get back to your original question: if you want to reduce the number of points drawn, aggregate your data differently in your group. Usually this means creating larger bins which either sum or average the data which fall into that interval.
As a simple example, you can combine every other point in your fiddle by binning by even numbers, like so:
var BINSIZE = 2;
// ...
speedSumGroup = runDimension
.group(function(r) { return Math.floor(r/BINSIZE) * BINSIZE; })
// ...
http://jsfiddle.net/gordonwoodhull/djrhodkj/2/
This causes e.g. both Run 6 and Run 7 to fall in the same bin, because they have the same group key. In a real example, you'd probably want to average them, as shown in the annotated stock example.
Can someone point me in the direction of what I should be tweaking to get deterministic color band? For example, if they array of colors contains 6 colors, I would like the values 10-30 to always go to the 5th color band, 50-80 to the 6th, etc.
(in case someone is wondering why I need such an odd thing, right now the value 30 shows up in several different colors, depending on what other values are in the set -- can be pretty confusing for a user over time). I thought of restricting the min and max values in the set to achieve stable colors but that would distort the lables. Also, ideally, I would like to specify the mapping of input data value to color myself
This won't let you do arbitrary assignments of values to colors, but you can set the min and max values cubism uses to assign colors with the extent option:
var context = cubism.context();
var horizon = context.horizon();
horizon.extent([-80,80]);
The extent will then be divided up evenly among the color bands you have set.
Let's say I have a list of values and I have already chunked them into groups to make a histogram.
Since Excel doesn't have histograms, I made a bar plot using the groups I developed. Specifically, I have the frequencies 2 6 12 10 2 and it produces the bar plot you see below.
Next, I want to add a normal distribution (line plot) with a mean of 0.136 and standard deviation of 0.497 on top of this histogram. How can I do this in excel? I need the axis to line up such that it takes up the width of the bar plot. Otherwise, you get something like I've attached.
But...the normal should be overlayed on the bar plot. How can I get this effect?
There are two main part to this answer:
First, I reverse-engineered the grouped data to come up with an appropriate mean and standard deviation on this scale.
Second, I employed some chart trickery to make the normal distribution curve look right when superimposed on the column chart. I used Excel 2007 for this; hopefully you have the same options available in your version.
Part 1: Reverse-Engineer
The column B formulae are:
Last Point =MAX(A2:A6)
Mean =SUMPRODUCT(B2:B6,A2:A6)/SUM(B2:B6)
E(x^2f) =SUMPRODUCT(A2:A6^2,B2:B6)
E(xf)^2 =SUMPRODUCT(A2:A6,B2:B6)^2
E(f) =SUM(B2:B6)
Variance =B10-B11/B12
StDev =SQRT(B13/(B12-1))
Part 2: Chart Trickery
Data table:
Column D is just an incremental counter. This will be the number of data points in the normal distribution curve.
E2 =D2/$B$8 etc.
F2 =NORMDIST(E2,$B$9,$B$14,FALSE) etc.
Chart:
Now, add Columns E:F to the chart. You will need to massage a few things:
Change the series to be an X-Y plot. This might require some editing of the chart series to force a single series to use your desired X and Y values.
Change the series to use the secondary axes (both X and Y).
Change the secondary X-axis range to 0.5-5.5 (i.e., 0.5 on either side of the column chart category values). This will effectively align the primary and secondary X-axes.
Change the secondary Y-axis range to 0-1
Format the X-Y series appearance to taste (I suggest removing value markers).
The result so far:
Lastly, you can remove the tick marks and labels on the secondary axes to clean up the look.
Postscript: Thanks to John Peltier for innumerable charting inspirations over the years.