Finally I fix the problem, im going to describe the entire process. In essence you have to follow this steps: https://xgboost.readthedocs.io/en/latest/build.html Specifically this is important: brew install gcc@8 This command download the version of gcc that supports openMP an important library to XGBoost due to the nature of some parallel characteristics. Maybe the shared library xgboost.so fails due to a "symbol not found error". This occurs when your are trying to link objects compiled from different gcc versions. More info here: What does "Symbol not found / Expected in: flat namespace" actually mean? To fix this I changed the contents of ~/.R/Makevars file to : CC=/usr/local/bin/gcc-8 CXX=/usr/local/bin/g++-8 CXX11=/usr/local/bin/g++-8 Note CX11 is different from original question version. This solved my problem. More info about Makevars file here : Understanding the contents of the Makevars file in R (macros, variables, ~/.R/Makevars and pkg/src/Makevars) If the above fails it is recommended to delete the R libraries and reinstall it, there may be a problem with a symbolic link or similar. R libraries (Mac Os High Sierra) are stored here: /Library/Frameworks/R.framework/Versions/3.5/Resources/library/

This is an answer for MATLAB In a general fashion, animating a plot (or 3d plot, or scatter plot, or surface, or other graphic objects) can be done following the same approach: Do the first plot/plot3/scatter/surf, and retrieve its handle. The first plot can incorporate the first "initial" sets of points or even be empty (use NaN value to create a plot with invisible data point). Set axis limits and all other visualisation options which are going to be fixed (view point, camera angle, lightning...). No need to set the options which are going to evolove during the animation. In a loop, update the minimum set of plot object properties: XData, YData ( ZData if 3D plot, CData if the plot object has some and you want to animate the color). The code below is an implementation of the approach above adapted to your case: <pre class="lang-matlab prettyprint-override">``` %% Read data and place coordinates in named variables csvfile = '3D scatter plot.csv' ; data = csvread(csvfile,2) ; % [optional], just to simplify notations further down x = data(:,2) ; y = data(:,3) ; z = data(:,4) ; %% Generate empty [plot3] objects figure % create an "axes" object, and retrieve the handle "hax" hax = axes ; % create 2 empty 3D point plots: % [hp_new] will contains only one point (the new point added to the graph) % [hp_trail] will contains all the points displayed so far hp_trail = plot3(NaN,NaN,NaN,'.b','Parent',hax,'MarkerSize',2) ; hold on hp_new = plot3(NaN,NaN,NaN,'or','Parent',hax,'MarkerSize',6,'MarkerEdgeColor','r','MarkerFaceColor','g','LineWidth',2) ; hold off %% Set axes limits (to limit "wobbling" during animation) xl = [min(x) max(x)] ; yl = [min(y) max(y)] ; zl = [min(z) max(z)] ; set(hax, 'XLim',xl,'YLim',yl,'ZLim',zl) view(145,72) % set a view perspective (optional) %% Animate np = size(data,1) ; for ip=1:np % update the "new point" graphic object set( hp_new , 'XData',x(ip), 'YData',y(ip), 'ZData',z(ip) ) % update the "point history" graphic object % we will display points from index 1 up to the current index ip % (minus one) because the current index point is already displayed in % the other plot object indices2display = 1:ip-1 ; set(hp_trail ,... 'XData',x(indices2display), ... 'YData',y(indices2display), ... 'ZData',z(indices2display) ) % force graphic refresh drawnow % Set the "speed" % actually the max speed is given by your harware, so we'll just set a % short pause in case you want to slow it down pause(0.01) % <= comment this line if you want max speed end This will produce:

Would this be considered simpler? ggplot(df) + geom_arc(aes(x0 = x, y0 = y, r = r, start = 0, end = -1.5 * pi), arrow = arrow()) + annotate("text", x = df$x, y = df$y, label = df$label) + theme_void() # equivalent to above with geom_text instead; I'm not sure if your actual use # case has preference for one or the other ggplot(df) + geom_arc(aes(x0 = x, y0 = y, r = r, start = 0, end = -1.5 * pi), arrow = arrow()) + geom_text(aes(x = x, y = y, label = label)) + theme_void()

Since you tagged it as Shiny, I'm going to assume you want to include raw HTML in a shiny app. In this case, you can use the HTML tag library(shiny) # add the below in your ui.R script tags$div( HTML( <your raw HTML goes here> ) ) See https://shiny.rstudio.com/articles/html-tags.html for more details, scrolling down to the "Raw HTML" section.

There is a very simple way to select a number of rows using the R index for rows and columns. This lets you CLEANLY split the data set given a number of rows - say the 1st 80% of your data. In R all rows and columns are indexed so DataSetName[1,1] is the value assigned to the first column and first row of "DataSetName". I can select rows using [x,] and columns using [,x] For example: If I have a data set conveniently named "data" with 100 rows I can view the first 80 rows using View(data[1:80,]) In the same way I can select these rows and subset them using: train = data[1:80,] test = data[81:100,] Now I have my data split into two parts without the possibility of resampling. Quick and easy.

I would say that the easiest is to use sample and ifelse, also you should probably sample based on the distribution of males/females. # Some data gender <- sample(c("male", "female", "other"), 100, prob = c(0.4, 0.3, 0.3), replace = TRUE) # Calculating proportion of females vs males male_prop <- sum(gender=="male")/(sum(gender=="male")+sum(gender=="female")) female_prop <- sum(gender=="female")/(sum(gender=="male")+sum(gender=="female")) # Replacing other at random gender <- ifelse(gender=="other", sample(c("male", "female"), 1, prob = c(male_prop, female_prop), replace = TRUE), gender) Note: As in markus answer, it is a good idea to set a seed to ensure reproducibility.

Not sure I am correct since I cannot see the data, but it looks like the first line (Academic (nonstudent)) has 0 answering strongly disagree and 4th (Private consultant/self-employed) has 0 answering Strongly disagree or disagree, which would probably be the cause of the problem. I think the solution to it could be a condition that if 0 have answered an option remove the label.

An alternative: apply(df, 1, function(x) sum(as.integer(x[x[["index1"]]:x[["index2"]]]))) Another one: apply(df[-1], 1, function(x) sum((x[(x[["index1"]]:x[["index2"]]) - 1L])))

You can try this: ggplot(df, aes(x = as.numeric(cat), y = eff)) + geom_line(aes(linetype = factor(eff)), size = 1.5) + geom_point(aes(color = segment), size = 3.5) + scale_color_manual(values = c("boat" = "blue", "car" = "green", "plane" = "red")) + scale_linetype_manual(values = c("0" = "solid", "25" = "dashed", "50" = "dotted", "75" = "twodash")) (Note: based on the sample data, the points corresponding to car are completely hidden beneath other points.)

The solution to this problem was to add a pause(0.1) between grid.arrange and menu

the lapply function has a different syntax. Try this: lapply(loci.pairs, function(x) LD2(jaguar, locus=x, details=FALSE)) The first argument of lapply contains the list which you want to iterate over. Since you want to iterate over the combinations you have to use lapply(loci.pairs...) instead of lapply(jaguar,...). Essentially, this call to lapply is (in terms of output) equivalent to the following loop: result_list = list() for (i in 1:n) { result_list[[i]] <- LD2(jaguar, locus=loci.pairs[[i]], details=FALSE) }

Here is a possibility using strftime: weeks <- seq(from = ISOdate(2018,12,10), to = ISOdate(2019,4,1), by="week") strftime(weeks,format="%Y-%W")

There's a similar question at this link. A solution for your flexdashboard would be to replace your column2 code with: ```{r, echo=FALSE} output$mymap = renderLeaflet({ my_size <- input$bubblesize leaflet() %>% addTiles() %>% addCircleMarkers(lng = ~long, lat = ~latt, popup = ~planttext, radius = ~qty * my_size, data = qty_d) }) leafletOutput('mymap', height=1000)

If you want to have some network plot that displays some extra information besides the connections, you could use strength.plot. Following your example: library(Rgraphviz) strength <- arc.strength(network, Data) strength.plot(network, strength, shape = "ellipse") In case it is absolutely necessary to use the results of the parameters of the GBN est.para, you could use the graphviz.plot arguments to highlight edges and nodes (can be done using edgeRenderInfo and nodeRenderInfo). Just as an example, you could use the parameters to choose the width of the edges: library(data.table) plot <- graphviz.plot(network, shape = "ellipse") arc.sizes <- data.table(network$arcs) arc.sizes[, edge.name := paste0(arc.sizes$from, "~", arc.sizes$to)] arc.sizes[, param := abs(est.para[[to]]$coefficients[[from]]), by = .(from, to)] arc.sizes[, lwd := 5*((param - min(param))/(max(param) - min(param)))] lwd <- as.vector(arc.sizes$lwd) names(lwd) <- arc.sizes$edge.name edgeRenderInfo(plot) <- list(lwd = lwd) renderGraph(plot)