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mv nr. editors graph to history for #34
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@mpadge
mpadge committed Apr 30, 2024
1 parent 8516708 commit f625c61
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2 changes: 1 addition & 1 deletion DESCRIPTION
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@@ -1,6 +1,6 @@
Package: dashboard
Title: What the Package Does (One Line, Title Case)
Version: 0.2.2.003
Version: 0.2.2.004
Authors@R:
person(given = "First",
family = "Last",
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2 changes: 1 addition & 1 deletion codemeta.json
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Expand Up @@ -6,7 +6,7 @@
"name": "dashboard: What the Package Does (One Line, Title Case)",
"codeRepository": "https://github.com/ropensci-review-tools/dashboard",
"license": "https://spdx.org/licenses/MIT",
"version": "0.2.2.003",
"version": "0.2.2.004",
"programmingLanguage": {
"@type": "ComputerLanguage",
"name": "R",
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84 changes: 0 additions & 84 deletions quarto/editors.qmd
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Expand Up @@ -480,87 +480,3 @@ ggiraph::girafe (ggobj = g, fonts = list (sans = "Open Sans"))
```{r reset-fig-ht, echo = FALSE}
knitr::opts_chunk$set (fig.height = opts$fig.height)
```

## Numbers of Editors

rOpenSci relies on our team of volunteer editors. We can only provide review
services if we have sufficient numbers of editors available to handle
submissions. It is therefore important to monitor historical trends in overall
editor availability. This first graph shows total numbers of editors over time,
and corresponding lines for numbers of those engaged during each time period in
ongoing reviews, and numbers who are not handling any submissions during each
period and are therefore free to accept new submissions.

This number of "Free" editors may include those who have yet to edit their
first submissions, in which case these will not appear in any subsequent
graphs. Thus the total number in this first graph may be greater than
identifiable numbers from any subsequent graphs.


```{r ed-availability-prepro, echo = FALSE}
# Use all editors, not just current ones
num_eds_busy <- ed_dat$timeline_total |>
dplyr::filter (value > 0L) |>
dplyr::group_by (month) |>
dplyr::summarise (n = dplyr::n ())
ed_dates <- ed_dat$timeline_total |>
dplyr::filter (value > 0L) |>
dplyr::group_by (name) |>
dplyr::summarise (start = min (month), end = max (month))
ed_dates$end [ed_dates$name %in% ed_status$editor] <- max (ed_dates$end)
ed_dates <- as.matrix (ed_dates [, c ("start", "end")])
dates <- apply (ed_dates, 1, function (i) {
seq (lubridate::ymd (i [1]), lubridate::ymd (i [2]), by = "quarter") |>
as.character ()
})
n <- table (unlist (dates))
dates_month <- lubridate::ymd (names (n))
index <- match (dates_month, num_eds_busy$month)
num_eds_total <- num_eds_free <- data.frame (
month = lubridate::ymd (names (n)),
n = as.integer (n)
)
index <- match (num_eds_busy$month, num_eds_total$month)
num_eds_free$n [index] <- num_eds_total$n [index] - num_eds_busy$n
# Function to smooth 'busy' and 'free', but not needed in current form.
filter_dat <- function (dat, flen = 5) {
index <- seq_len (length (dat) - flen + 1) + floor (flen / 2)
x <- seq_len (flen) - ceiling (flen / 2)
x <- -abs (x)
filt <- exp (x)
filt <- filt / sum (filt)
dat [index] <- stats::filter (dat, filt) [index]
return (dat)
}
# num_eds_busy$n <- filter_dat (num_eds_busy$n, flen = 3)
# num_eds_free$n <- filter_dat (num_eds_free$n, flen = 3)
num_eds <- rbind (
cbind (num_eds_busy, status = "Busy"),
cbind (num_eds_total, status = "Total"),
cbind (num_eds_free, status = "Free")
)
```

::: {style="all.initial;"}
```{r timeline-num-eds-plot, echo = FALSE, fig.width = 8, fig.height = 8}
ggplot (num_eds, aes (x = month, y = n, colour = status)) +
geom_line (lwd = 1.0) +
xlab ("Year") +
ylab ("Number of editors") +
theme_minimal () +
theme (
plot.background = element_rect (fill = bg_col),
panel.grid.major = element_line (colour = "#CCCCCC"),
panel.grid.minor = element_blank (),
legend.position = "inside",
legend.position.inside = c (0.1, 0.8),
axis.text.x = element_text (size = 12),
axis.text.y = element_text (size = 10),
axis.title = element_text (size = 14)
)
```
:::
129 changes: 113 additions & 16 deletions quarto/history.qmd
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Expand Up @@ -19,6 +19,20 @@ library (lubridate)
dat <- review_history (quiet = TRUE)
```

```{r ggtheme, echo = FALSE}
this_theme <- theme_minimal () +
theme (
panel.grid.major = element_line (colour = "#CCCCCC"),
panel.grid.minor = element_blank (),
legend.position = "inside",
legend.position.inside = c (0.1, 0.8),
axis.text.x = element_text (size = 12),
axis.text.y = element_text (size = 10),
axis.title = element_text (size = 14)
)
```


## Package submissions

This chart shows the total number of packages *submitted for review* each
Expand Down Expand Up @@ -74,11 +88,7 @@ ggplot (submissions, aes (x = date, y = submissions, colour = type)) +
geom_line (linetype = submissions$lty) +
xlab ("Year") +
ylab (ytxt) +
theme_minimal () +
theme (
legend.position = "inside",
legend.position.inside = c (0.1, 0.8)
)
this_theme
```

## Packages under review
Expand Down Expand Up @@ -138,11 +148,7 @@ ggplot (reviews, aes (x = date, y = reviews, colour = type)) +
geom_line (linetype = reviews$lty) +
xlab ("Year") +
ylab ("Nr. active reviews / month") +
theme_minimal () +
theme (
legend.position = "inside",
legend.position.inside = c (0.1, 0.8)
)
this_theme
```

## Review duration {#review-duration}
Expand Down Expand Up @@ -211,13 +217,104 @@ rev_dur <- rbind (rev_dur_all, rev_dur_gen, rev_dur_stats)

```{r rev-duration-plot, echo = FALSE, warning = FALSE}
ggplot (rev_dur, aes (x = date, y = dur, colour = type)) +
geom_line (linetype = rev_dur$lty) +
theme_minimal () +
geom_line (linetype = rev_dur$lty, lwd = 1.0) +
xlab ("Year") +
ylab ("Review Duration (months)") +
ylim (c (0, 11)) +
theme (
legend.position = "inside",
legend.position.inside = c (0.1, 0.8)
)
this_theme
```


## Numbers of Editors

```{r get-ed-dat-history, echo = FALSE, message = FALSE}
#| cache: true
aggregation_period <- "quarter" # default
ed_dat <- editor_status (quiet = TRUE, aggregation_period = aggregation_period)
ed_status <- ed_dat$status
```

```{r clean-editor-status-history, echo = FALSE}
# Taken straight from editors.qmd
#| cache: false
eds_to_rm <- dashboard:::eds_to_remove
ed_status <- dplyr::filter (ed_status, !editor %in% eds_to_rm) |>
dplyr::relocate (other_langs, .before = domain_expertise) |>
dplyr::rename (
"Languages" = other_langs,
"Expertise" = domain_expertise
) |>
tidyr::replace_na (list (inactive_for = "(waiting)"))
```

rOpenSci relies on our team of volunteer editors. We can only provide review
services if we have sufficient numbers of editors available to handle
submissions. It is therefore important to monitor historical trends in overall
editor availability. This first graph shows total numbers of editors over time,
and corresponding lines for numbers of those engaged during each time period in
ongoing reviews, and numbers who are not handling any submissions during each
period and are therefore free to accept new submissions.

This number of "Free" editors may include those who have yet to edit their
first submissions, in which case these will not appear in any subsequent
graphs. Thus the total number in this first graph may be greater than
identifiable numbers from any subsequent graphs.


```{r ed-availability-prepro, echo = FALSE}
# Use all editors, not just current ones
num_eds_busy <- ed_dat$timeline_total |>
dplyr::filter (value > 0L) |>
dplyr::group_by (month) |>
dplyr::summarise (n = dplyr::n ())
ed_dates <- ed_dat$timeline_total |>
dplyr::filter (value > 0L) |>
dplyr::group_by (name) |>
dplyr::summarise (start = min (month), end = max (month))
ed_dates$end [ed_dates$name %in% ed_status$editor] <- max (ed_dates$end)
ed_dates <- as.matrix (ed_dates [, c ("start", "end")])
dates <- apply (ed_dates, 1, function (i) {
seq (lubridate::ymd (i [1]), lubridate::ymd (i [2]), by = "quarter") |>
as.character ()
})
n <- table (unlist (dates))
dates_month <- lubridate::ymd (names (n))
index <- match (dates_month, num_eds_busy$month)
num_eds_total <- num_eds_free <- data.frame (
month = lubridate::ymd (names (n)),
n = as.integer (n)
)
index <- match (num_eds_busy$month, num_eds_total$month)
num_eds_free$n [index] <- num_eds_total$n [index] - num_eds_busy$n
# Function to smooth 'busy' and 'free', but not needed in current form.
filter_dat <- function (dat, flen = 5) {
index <- seq_len (length (dat) - flen + 1) + floor (flen / 2)
x <- seq_len (flen) - ceiling (flen / 2)
x <- -abs (x)
filt <- exp (x)
filt <- filt / sum (filt)
dat [index] <- stats::filter (dat, filt) [index]
return (dat)
}
# num_eds_busy$n <- filter_dat (num_eds_busy$n, flen = 3)
# num_eds_free$n <- filter_dat (num_eds_free$n, flen = 3)
num_eds <- rbind (
cbind (num_eds_busy, status = "Busy"),
cbind (num_eds_total, status = "Total"),
cbind (num_eds_free, status = "Free")
)
```

::: {style="all.initial;"}
```{r timeline-num-eds-plot, echo = FALSE, fig.width = 8, fig.height = 8}
ggplot (num_eds, aes (x = month, y = n, colour = status)) +
geom_line (lwd = 1.0) +
xlab ("Year") +
ylab ("Number of editors") +
this_theme
```
:::

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