Firstly, I am very, very new to Python. I am trying to come close to a product I make in Excel charts by plotting X and Y. I want to be able to export the data from Excel to a text file and the read into Python to produce the chart. In Excel I have the line segments, defined by X and Y values, separated by empty cells in columns and the other segments in other columns. For right now I am just exporting a single column with the objective of having more columns. So if the image shows up in this post you will see that the different line segments are all connected by straight lines, sort of like Etch-a-Sketch. I got errors when I had blank lines in the text file where I had empty cells in the Excel data. Any guidance would be greatly appreciated.
Attempted chart
Related
I am attempting to generate heatmaps from a data file I've been generating. I could re-format the data however I like, but for the time being, let's say it's a list of 16 numbers that I'd like put into a 4x4 heatmap. However, I have many sets of these 16 numbers sequentially in the same file, and hope to eventually animate them together (something I am more comfortable with, and will come later)
However, for the time being, I cannot find a way to get GnuPlot to select only certain sections of the data file while still plotting properly. A loose example of what I would've thought it WOULD look like:
plot "SortedData.txt" every ::0::15 w image
or:
splot "SortedData.txt" every ::0::15
Both give me errors and fail to render. I could label the data values with an x-y coordinate if needed, but the task is fairly repetitive: I just want the first 16 points mapped, and then the ability to iterate once and have the next 16 points mapped on their own, etc. Stripping the data file to just the first 16 points and removing the 'every' command confirms that it can plot, but trying to specify even just the first 16 manually messes it up.
Can anyone point me in the right direction? The "every" command has been fairly nebulous and seems largely incompatible with images / 3-D data. Also, I am running on Windows, so piping in linux commands is something I'd like to avoid.
Thanks!
edit: Here is 4 example frames of the data. Reformatting it to, say, present as a matrix or label with pixel addresses are all something I can do if needed.
0.000000 -49.314654 -44.425234 -46.613870 -48.494232 -46.884806 -46.553071 -46.555624 -43.755972 -47.817691 -42.481637 -46.819782 -44.347586 -49.487077 -47.291832 -45.140636 -47.945934
0.839906 -49.325396 -44.425493 -46.613214 -48.501283 -46.887236 -46.550858 -46.555285 -43.752786 -47.814706 -42.453793 -46.814333 -44.329492 -49.493501 -47.289394 -45.133555 -47.944045
1.679721 -49.336151 -44.425787 -46.612573 -48.508348 -46.889684 -46.548645 -46.554958 -43.749626 -47.811707 -42.425757 -46.808866 -44.311344 -49.499930 -47.286951 -45.126476 -47.942155
2.519466 -49.346920 -44.426117 -46.611946 -48.515427 -46.892152 -46.546431 -46.554641 -43.746492 -47.808695 -42.397525 -46.803382 -44.293140 -49.506365 -47.284501 -45.119398 -47.940264
It seems that each line in your data file has 17 elements. I assume that the first column is not part of your image data. I would format the remaining 16 values as a 4x4 matrix, with each frame separated by two blank lines:
-49.314654 -44.425234 -46.613870 -48.494232
-46.884806 -46.553071 -46.555624 -43.755972
-47.817691 -42.481637 -46.819782 -44.347586
-49.487077 -47.291832 -45.140636 -47.945934
-49.325396 -44.425493 -46.613214 -48.501283
-46.887236 -46.550858 -46.555285 -43.752786
-47.814706 -42.453793 -46.814333 -44.329492
-49.493501 -47.289394 -45.133555 -47.944045
-49.336151 -44.425787 -46.612573 -48.508348
-46.889684 -46.548645 -46.554958 -43.749626
-47.811707 -42.425757 -46.808866 -44.311344
-49.499930 -47.286951 -45.126476 -47.942155
-49.346920 -44.426117 -46.611946 -48.515427
-46.892152 -46.546431 -46.554641 -43.746492
-47.808695 -42.397525 -46.803382 -44.293140
-49.506365 -47.284501 -45.119398 -47.940264
You can then visualize each frame with the command
plot "data.dat" index FRAME matrix w image
where FRAME is 0, 1, 2 or 3.
Is there a package in R where if you have a line graph, and you click on one of the lines, it will take you to another graph?
So basically I want to portray a large scale view of paramters and then when I click on one of the lines in the graph, it will take me to a more detailed look at the data in a different graph created.
If that isn't possible, then a text hyperlink in the legend would be fantastic.
Thanks!
I have a large file that contains two column data X,Y. I have got a round 20 million records. I want to graph the file in ggplot or even in normal plot (scattered plot). I used to read the file in R by using read command and store the whole data in a data frame, however, with the current size R can't read the file. I managed to plot the data in gnuplot by using every command to reduce the size. But I'd like to graph the file with R.
How to read the large file and plot it. I think reading the file line by line will not help because I want to graph the values. I'm not aware of any command like èvery in R.
Thank you for any suggestions.
I have a plot with many "lines" in it (using points with type being l).
I would like to put a small piece of text next to them. I could do that all sort of ways, such as using mtext, but the problem is that there are many plots to be generated automatically, and there could be many lines in a single plot, so I would like the text to be placed automatically close to the line in an empty spot...
Is there a way to do that?
I have an Excel file with two different columns. One column have values ranging from 2 to 15 and other column have values ranging from positive to negative numbers.
I want to produce a heatmap in such a way that for first column each value should have a different color. Second column should be in the form of a gradient.
I tried using excel conditional formatting to do this.
But I want to know is there any way to do it in R?
The R command image() takes a matrix and makes a heat-map from it. see the help page: ?image. Also worth considering is the heatmap function, which is basically image() with some clustering applied. Below are two examples from these two plotting routines:
image(volcano,col = terrain.colors(30))
heatmap(volcano,col = terrain.colors(30))
Probably the easiest way to export your data from Excel to R is to save it as a .csv file (comma or tab-separated text file), and then import it using read.table()
You can easily create an interactive heatmap in R using plotly:
library(plotly)
plot_ly(z = volcano, type = "heatmap")
More instructions here.