---
output: html_document
---

```{r setup, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  echo = FALSE,
  message = FALSE,
  warning = FALSE
)
```

The following is a graph demonstrating the volume of COVID-19 related preprints posted to popular preprint sites (BioRxiv & MedRxiv).

```{r}
library(httr)

list_preprints_url <- "https://api.biorxiv.org/covid19/"

latest_preprints <- content(GET(paste0(list_preprints_url, 0)))

total_nb <- latest_preprints$messages[[1]]$total

res <- latest_preprints$collection

for (i in seq(30, total_nb, by = 30)) {

  preprints <- content(GET(paste0(list_preprints_url, i)))

  res <- c(res, preprints$collection)

}

df <- lapply(res, function(e) c(e$rel_date, e$rel_site))
df <- do.call(rbind.data.frame, df)
colnames(df) <- c("date", "site")

library(dplyr)
preprints_covid <- df %>%
  mutate(date = as.Date(date)) %>%
  filter(date >= "2020-01-01") %>%
  count(date, site) %>%
  mutate(tot = cumsum(n))
```

```{r}
library(ggplot2)
ggplot(preprints_covid, aes(x = date, y = n, fill = site)) +
  geom_bar(stat = "identity") +
  theme_minimal() +
  labs(x = "Deposition date", y = "Preprints") +
  scale_fill_brewer(palette = "Set1")
```
