Following this question, Multiple values in one tile with geom_tile and matrix plot, I’d like the tile attributes in agreement_num to be symmetrical, i.e. for the reverse pair combination, I’d like to plot the same agreement_num. I’m creating a new question since this entails finding the reverse combination of pairs, assigning the corresponding agreement_num and then inserting new rows for each combination and agreement_num. E.g. from Kazakhstan to Kyrgyzstan there are six rows and six unique agreement_num. The expected output would be to have these rows in the dataframe:

from        to          weight          agreement_num
Kyrgyzstan  Kazakhstan  1.337996e+08    51
Kyrgyzstan  Kazakhstan  1.337996e+08    176
Kyrgyzstan  Kazakhstan  1.337996e+08    58
Kyrgyzstan  Kazakhstan  1.337996e+08    224
Kyrgyzstan  Kazakhstan  1.337996e+08    133
Kyrgyzstan  Kazakhstan  1.337996e+08    135

to be able to plot the same tile attribute for the reverse country combination in the matrix plot.

I’ve managed to get quite far to create the data below, but cannot figure out the last steps of inserting new rows and assigning the agreement_num for each row:

# Create empty vectors to store values
oneway <- logical(nrow(plot_data))
additional_value <- list()

# Iterate over each row of the data frame
for (i in 1:nrow(plot_data)) {
  # Find indices of reverse pairs
  reverse_indices <- which(plot_data$from == plot_data$to[i] & plot_data$to == plot_data$from[i] & seq_len(nrow(plot_data)) != i)
  
  # Assign the oneway value
  oneway[i] <- length(reverse_indices) > 0
  
  # Assign additional value based on reverse combination
  if (oneway[i]) {
    # Add the additional values from the "agreement_num" column of the reverse pairs
    additional_value[[i]] <- unique(plot_data$agreement_num[reverse_indices])
  } else {
    # Assign NA if oneway is FALSE
    additional_value[[i]] <- NA
  }
}

# Add the vectors as new columns to the data frame
plot_data$oneway <- oneway
plot_data$additional_value <- additional_value

Reproducible data:

plot_data <- structure(list(from = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L), levels = c("Afghanistan", 
"Kazakhstan", "Kyrgyzstan", "Tajikistan", "Turkmenistan", "Uzbekistan"
), class = "factor"), to = structure(c(1L, 3L, 3L, 3L, 3L, 3L, 
3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 2L, 6L), levels = c("Afghanistan", 
"Kazakhstan", "Kyrgyzstan", "Tajikistan", "Turkmenistan", "Uzbekistan"
), class = "factor"), weight = c(1291072130433.34, 480160896152.234, 
480160896152.234, 480160896152.234, 480160896152.234, 480160896152.234, 
480160896152.234, 3474907531417.02, 3474907531417.02, 3474907531417.02, 
867103764128.709, 867103764128.709, 7791981051421.92, 7791981051421.92, 
133799551.098735, 1102379004.66647), agreement_num = c(NA, 51L, 
176L, 58L, 224L, 133L, 135L, 58L, 51L, 224L, 51L, 224L, 51L, 
224L, NA, NA), com.x = c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L), com.y = c(2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), cut = c(3, 1, 1, 1, 
1, 1, 1, 3, 3, 3, 3, 3, 4, 4, 1, 1), oneway = c(FALSE, TRUE, 
TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, TRUE, FALSE), additional_value = list(NA, NA_integer_, 
    NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, 
    NA, NA, NA, NA, NA, NA, NA, c(51L, 176L, 58L, 224L, 133L, 
    135L), NA)), row.names = c(NA, -16L), class = "data.frame")

Perhaps there is an easier way to do this, would be happy to get suggestions.

Adding the code for plotting:

ggplot(plot_data, aes(x = from, y = to, fill = agreement_num)) +
  geom_rect(
    aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax)
  ) +
  scale_fill_manual(values = coul) +
  theme_bw() +
  scale_x_discrete(drop = FALSE) +
  scale_y_discrete(drop = FALSE) +
  labs(title = "Community 2") +
  theme(plot.title = element_text(size=17),
    axis.text.x = element_text(
      size = 12, angle = 270,
      hjust = 0, vjust = 0
    ),
    axis.text.y = element_text(size = 12),
    axis.title.x = element_text(size = 15),
    axis.title.y = element_text(size = 15),
    aspect.ratio = 1
  )

>Solution :

If all you need is to reverse the names, how about simple row-binds?

dplyr

library(dplyr)
rename(plot_data, from = to, to = from) |>
  bind_rows(plot_data) |>
  filter(to == "Kyrgyzstan")
#           to       from       weight agreement_num com.x com.y cut oneway           additional_value
# 1 Kyrgyzstan Kazakhstan    133799551            NA     2     2   1   TRUE 51, 176, 58, 224, 133, 135
# 2 Kyrgyzstan Uzbekistan   1102379005            NA     2     2   1  FALSE                         NA
# 3 Kyrgyzstan Kazakhstan 480160896152            51     2     2   1   TRUE                         NA
# 4 Kyrgyzstan Kazakhstan 480160896152           176     2     2   1   TRUE                         NA
# 5 Kyrgyzstan Kazakhstan 480160896152            58     2     2   1   TRUE                         NA
# 6 Kyrgyzstan Kazakhstan 480160896152           224     2     2   1   TRUE                         NA
# 7 Kyrgyzstan Kazakhstan 480160896152           133     2     2   1   TRUE                         NA
# 8 Kyrgyzstan Kazakhstan 480160896152           135     2     2   1   TRUE                         NA

(filtered just to show that your desired six rows are there)

base R

transform(plot_data, to = from, from = to) |>
  rbind(plot_data)