plot_r01.R

# Load libraries
library(data.table)
library(ggplot2)
library(lubridate)  # for month()

# https://reporter.nih.gov/search/43gg1_mEQUWulgAiysCfEg/projects?shared=true
# Load data
data <- fread('SearchResult_Export_06Jul2025_102053.csv')
data <- data[!duplicated(`Serial Number`)]
# Convert 'Award Notice Date' to Date
data[, `Award Notice Date` := as.Date(`Award Notice Date`, format = "%m/%d/%Y")]

# Extract Year and Month
data[, Year := format(`Award Notice Date`, "%Y")]
data[, Month_Num := month(`Award Notice Date`)]  # numeric month

# Aggregate number of awards by Year and Month
monthly_counts <- data[, .N, by = .(Year, Month_Num)]

# Ensure correct month order
setorder(monthly_counts, Month_Num)

# Flag 2025 for bolding
monthly_counts[, LineSize := ifelse(Year == "2025", 5.5, 0.8)]
monthly_counts[, PointSize := ifelse(Year == "2025", 3, 1.5)]

# remove years before 2023
monthly_counts <- monthly_counts[Year >= 2023]

# Plot
ggplot(monthly_counts, aes(x = Month_Num, y = N, group = Year, color = Year)) +
  geom_line(aes(size = LineSize)) +
  scale_x_continuous(breaks = 1:12, labels = month.abb) +
  scale_size_identity() + 
  labs(title = "NIH R01 New Year 1 Awards by Award Notice Date", 
       x = "", y = "Number of Awards") +
  theme_minimal() +
  theme(
    plot.title = element_text(size = 24, hjust = 0.5, face = "bold"),
    axis.title = element_text(size = 18, face = "bold"),             
    axis.text = element_text(size = 14),                             
    legend.title = element_text(size = 16, face = "bold"),           
    legend.text = element_text(size = 14),                           
    legend.key.width = unit(2, "cm")                                 
  ) +
  scale_color_manual(values = c("2023" = "#E69F00", "2024" = "#56B4E9", "2025" = "#009E73")) +
  theme(axis.text.x = element_text(size = 18),
        axis.text.y = element_text(size = 18),
        axis.title.y = element_text(size = 22, face = "bold")) +
      guides(color = guide_legend(override.aes = list(linewidth = 5)))

plot_sbir.R

library(data.table)
library(ggplot2)
library(lubridate)

# Load data
# https://reporter.nih.gov/search/DNC_QozdAkOzNk372Q_MOQ/projects?shared=true
data <- fread('/home/chase/Downloads/SearchResult_Export_05Jul2025_091110.csv')
data <- data[!duplicated(`Serial Number`)]

# Convert 'Award Notice Date' to Date
data[, `Award Notice Date` := as.Date(`Award Notice Date`, format = "%m/%d/%Y")]

# Extract award_notice_year and Month
data[, award_notice_year := as.integer(format(`Award Notice Date`, "%Y"))]
data[, award_notice_month := month(`Award Notice Date`)]

# Aggregate number of awards by award_notice_year and Month
monthly_counts <- data[, .N, by = .(award_notice_year, award_notice_month)]

# Split data
historic_data <- monthly_counts[award_notice_year >= 2010 & award_notice_year <= 2024]
data_2025 <- monthly_counts[award_notice_year == 2025]

# Calculate mean and sd for each month (historic)
summary_stats <- historic_data[, .(
  mean_n = mean(N),
  sd_n = sd(N)
), by = award_notice_month]

# Prepare data for ribbons with legend
ribbon_data <- rbindlist(list(
  summary_stats[, .(award_notice_month, ymin = mean_n - 1 * sd_n, ymax = mean_n + 1 * sd_n, sd_level = "±1 SD")],
  summary_stats[, .(award_notice_month, ymin = mean_n - 2 * sd_n, ymax = mean_n + 2 * sd_n, sd_level = "±2 SD")],
  summary_stats[, .(award_notice_month, ymin = mean_n - 3 * sd_n, ymax = mean_n + 3 * sd_n, sd_level = "±3 SD")]
))

# Ensure sd_level order
ribbon_data[, sd_level := factor(sd_level, levels = c("±3 SD", "±2 SD", "±1 SD"))]

# Plot with legend for shading
ggplot() +
  geom_ribbon(data = ribbon_data,
              aes(x = award_notice_month, ymin = ymin, ymax = ymax, fill = sd_level),
              alpha = 0.4) +
  geom_line(data = summary_stats,
            aes(x = award_notice_month, y = mean_n),
            color = "blue", size = 1) +
  geom_line(data = data_2025,
            aes(x = award_notice_month, y = N),
            color = "red", size = 1.5) +
  scale_x_continuous(breaks = 1:12,
                     labels = month.abb) +
  scale_fill_manual(values = c("±3 SD" = "grey80", "±2 SD" = "grey60", "±1 SD" = "grey40")) +
  labs(
        title = "NIH SBIR Phase 1 Awards by Month\n(2010 to 2024 Avg ± 1, 2, 3 SD vs. 2025)",
        x = "",
        y = "Number of Awards",
        fill = "Shading Bands"
      ) +
  theme_minimal() +
  theme(
    plot.title = element_text(size = 24, hjust = 0.5, face = "bold"),
    axis.title = element_text(size = 18, face = "bold"),             
    axis.text = element_text(size = 14),                             
    legend.title = element_text(size = 16, face = "bold"),           
    legend.text = element_text(size = 14),                           
    legend.key.width = unit(2, "cm")                                 
  ) +
  theme(axis.text.x = element_text(size = 18),
        axis.text.y = element_text(size = 18),
        axis.title.y = element_text(size = 22, face = "bold"))