June2025/PebbleCountGrainSizePlots at main · JVanDerHout/June2025 · GitHub

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---
title: "Icicle Grain Size Distribution"
author: "JVDH"
date: "2025-03-07"
output: html_document
editor_options:
  chunk_output_type: console
---

```{r}
library(tidyverse)

#getwd()
#setwd("//neo/Terra/ClientFiles/U-Z/YN_Reach_Assessments_2024_240213/Design_Analysis/Geomorphology/Icicle/PebbleCounts_GrainSize/RawData")
#df <- read_csv("GrainSizeDistributionForPieCharts.csv")

# Convert data to long format for plotting
df_long <- df %>%
  pivot_longer(cols = c(SandPct, GravelPct, CobblePct, BoulderPct),
               names_to = "SedimentType",
               values_to = "Percentage") %>%
  mutate(Percentage_Plot = Percentage * 100) %>%
  mutate(SedimentType = str_sub(SedimentType, 1, -4))

class(df_long$Percentage_Plot)
```

plot with for loop
```{r}

library(ggrepel)  # For better text placement

unique_reaches <- unique(df_long$reach)

# Loop through each reach and generate a pie chart
for (reach_name in unique_reaches) {

  # Filter data for the current reach
  df_filtered <- df_long %>%
    filter(reach == reach_name)

  # Generate the pie chart
  p <- ggplot(df_filtered, aes(x = "", y = Percentage_Plot, fill = SedimentType)) +
    geom_bar(stat = "identity", width = 1) +
    coord_polar(theta = "y") +
    theme_void() +
    theme(legend.position = "right") +
    labs(title = paste("Sediment Composition -", reach_name)) +
    geom_text_repel(aes(label = ifelse(Percentage_Plot > 0,
                                       paste0(SedimentType, ": ", round(Percentage_Plot, 1), "%"),
                                       "")),
                    position = position_stack(vjust = 0.5),
                    size = 3,
                    box.padding = 0.5,  # Adjusts distance between labels
                    point.padding = 0.2,
                    segment.color = "grey50")  # Adds guiding lines to labels

  # Print the plot
  print(p)

  # Optionally, save the plot as an image file
  ggsave(filename = paste0("Sediment_Composition_", reach_name, ".png"), plot = p, width = 6, height = 6, dpi = 300)
}

```

or plot individual charts
```{r}
# Filter data for the selected reach
df_filtered <- df_long %>%
  filter(reach == "Reach 20 GC 1") # update as needed

# Generate the pie chart for the selected reach
ggplot(df_filtered, aes(x = "", y = Percentage_Plot, fill = SedimentType)) +
  geom_bar(stat = "identity", width = 1) +
  coord_polar(theta = "y") +
  theme_void() +
  theme(legend.position = "right") +
  labs(title = paste("Sediment Composition -", "Reach 20 GC 1")) +
  geom_text(aes(label = paste0(SedimentType, ": ", round(Percentage_Plot, 1), "%")),
            position = position_stack(vjust = 0.5),
            size = 3)  # Adjust text size as needed

```