use latexdiff to see changes in new version of tex document

Download https://github.com/ftilmann/latexdiff/

Then put your two files in the same folder

Use command

latexdiff original.tex new.tex > diff.tex

sql query to find non-singleton clone groups

select CID,size from
(SELECT distinct(clusterID) as CID, count(clusterID) as size FROM `cluster`
group by clusterID) as t
where size>1

Switch columns to rows in Excel

The solution is to use the TRANSPOSE function

Follow instructions here:
https://support.office.com/en-us/article/transpose-function-ed039415-ed8a-4a81-93e9-4b6dfac76027

Step 1: Select blank cells

First select some blank cells. But make sure to select the same number of cells as the original set of cells, but in the other direction. For example, there are 8 cells here that are arranged vertically:

So, we need to select eight horizontal cells, like this:

This is where the new, transposed cells will end up.

Step 2: Type =TRANSPOSE(

With those blank cells still selected, type: =TRANSPOSE(

Excel will look similar to this:

Notice that the eight cells are still selected even though we have started typing a formula.

Step 3: Type the range of the original cells.

Now type the range of the cells you want to transpose. In this example, we want to transpose cells from A1 to B4. So the formula for this example would be: =TRANSPOSE(A1:B4) -- but don't press ENTER yet! Just stop typing, and go to the next step.

Excel will look similar to this:

Step 4: Finally, press CTRL+SHIFT+ENTER

Now press CTRL+SHIFT+ENTER. Why? Because the TRANSPOSE function is only used in array formulas, and that's how you finish an array formula. An array formula, in short, is a formula that gets applied to more than one cell. Because you selected more than one cell in step 1 (you did, didn't you?), the formula will get applied to more than one cell. Here's the result after pressing CTRL+SHIFT+ENTER:

Code for making color pack visualization in R using custom dataset

library(ggraph)
library(igraph)
library(dplyr)


df <- data.frame(group=c("root", "root", "a","a","b","b","b"), 
                 subitem=c("a", "b", "x","y","z","u","v"),
                 size=c(0, 0, 6,2,3,2,5))

# create a dataframe with the vertices' attributes

vertices <- df %>%
  distinct(subitem, size) %>%
  add_row(subitem = "root", size = 0)

graph <- graph_from_data_frame(df, vertices = vertices)

ggraph(graph, layout = "circlepack", weight = size) +
  geom_node_circle(aes(fill =depth)) +
  # adding geom_text to see which circle is which node
  geom_text(aes(x = x, y = y, label = paste(name, "size=", size))) +
  coord_fixed()

Code for making a color pack visualization in R using flare dataset

library(ggraph)
library(igraph)
library(tidyverse)
# We need a data frame giving a hierarchical structure. Let's consider the flare dataset:
edges <- flare$edges

# Usually we associate another dataset that give information about each node of the dataset:
vertices <- flare$vertices

# Then we have to make a 'graph' object using the igraph library:
mygraph <- graph_from_data_frame( edges, vertices = vertices )

# Make the plot
ggraph(mygraph, layout = 'circlepack') +
  geom_node_circle() +
  theme_void()

ggraph(mygraph, 'treemap', weight = size) +
  geom_node_tile(aes(fill = depth), size = 0.25) +
  theme_void() +
  theme(legend.position="none")