From 523e10b75ba17c3f8b43e85d078dedf592a45396 Mon Sep 17 00:00:00 2001 From: Emily Boyer Date: Thu, 11 Jun 2026 10:23:45 -0600 Subject: [PATCH] Mark BVBRC_stats vignette Docker chunks eval=FALSE to fix CI --- vignettes/BVBRC_stats.Rmd | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/vignettes/BVBRC_stats.Rmd b/vignettes/BVBRC_stats.Rmd index f88f1a5..587794e 100644 --- a/vignettes/BVBRC_stats.Rmd +++ b/vignettes/BVBRC_stats.Rmd @@ -174,7 +174,7 @@ summarize_block <- function(df, cols, block_name) { Here we fetch the BV-BRC bacterial metadata table, clean it, and compute four artifacts that drive the rest of the vignette: `col_stats` (one row per column with totals, missing counts, and distinct non-missing values), `host_block_stats` and `geo_block_stats` (per-block presence summaries across host and geographic columns respectively), and `diag_table` (a focused per-column view of just the host + geo columns). -```{r stats} +```{r stats, eval = FALSE} # download the bvbrc table bvbrc <- fetchCompleteBVBRCMetadata() @@ -231,7 +231,7 @@ diag_table <- tibble(column = diag_cols) |> The table below shows how complete each column in the BV-BRC bacterial metadata is — sorted with the most sparsely populated columns first. Columns with very high `pct_missing` are unlikely to be useful downstream and may be worth dropping from featurization. -```{r col_stats_output} +```{r col_stats_output, eval = FALSE} cat("\n--- Per-column stats (whole table) ---\n") print(col_stats, n = Inf) ``` @@ -240,7 +240,7 @@ print(col_stats, n = Inf) Presence of the host-related columns (`host_common_name`, `host_group`, `host_name`) treated as a block. `n_rows_any_present` is the number of rows where at least one host field is populated; `n_rows_all_missing` is the number where every host field is empty. -```{r host_block_output} +```{r host_block_output, eval = FALSE} cat("\n--- Host block stats ---\n") print(host_block_stats) ``` @@ -249,7 +249,7 @@ print(host_block_stats) Same idea as the host block, but across the geographic columns (`isolation_source`, `geographic_location`, `isolation_country`, `state_province`, `city`, `county`, `latitude`, `longitude`). -```{r geo_block_output} +```{r geo_block_output, eval = FALSE} cat("\n--- Geographic block stats ---\n") print(geo_block_stats) ``` @@ -258,7 +258,7 @@ print(geo_block_stats) Column-by-column missingness for just the host and geographic fields, so you can see which specific columns drive the block-level numbers above. -```{r diag_output} +```{r diag_output, eval = FALSE} cat("\n--- Diagnostics for host + geo columns ---\n") print(diag_table, n = Inf) ```