gt table truncated when output as png-CodePudding

I am attempting to output a fairly long gt table using gtsave. It keeps getting truncated, where the last few columns are missing. The scrollbar also shows up in the outputted image.

Here is the outputted table:

I want it to look like my 5% variation table, which is below:

Here is my code for both tables (including R Markdown headers):

3% Table

{r hotspot 3% 100 coverage reads table, fig.dim = c(12, 6)}
setwd(output_hotspot)
hotspot_3pct_table <- hotspot_3pct_longer %>% 
  ungroup() %>%
  gt() %>%
  tab_header(title = "Variation Across Lots at Select Base Pairs", subtitle = paste0("At least 100 coverage reads with at least 3% variation")) %>% 
    cols_label(
    lot = "Lot"
  ) %>%
  fmt_number(columns = 2:24, decimals = 2) %>%
  fmt_missing(columns =  everything(), missing_text = "--") %>%
  tab_source_note(source_note = paste0("Dash indicates no variation present in lot")) %>%
  tab_options(
    table.width = pct(100)
  )

gtsave(hotspot_3pct_table, "hotspot_3pct.png")

5% Table

{r hotspot 5% 100 coverage reads table, fig.dim = c(12, 6)}
setwd(output_hotspot)
hotspot_5pct_table <- hotspot_5pct_longer %>% 
  ungroup() %>%
  gt() %>%
  tab_header(title = "Variation Across Lots at Select Base Pairs", subtitle = paste0("At least 100 coverage reads with at least 5% variation")) %>% 
    cols_label(
    lot = "Lot"
  ) %>%
  fmt_number(columns = 2:18, decimals = 2) %>%
  fmt_missing(columns =  everything(), missing_text = "--") %>%
  tab_source_note(source_note = paste0("Dash indicates no variation present in lot"))

gtsave(hotspot_5pct_table, "hotspot_5pct.png", expand = 10)

I have tried different fig.dim settings and different expand settings. I haven't encountered this issue before, so I am not sure how to approach this.

Reprex of each dataset:

3% Dataset

hotspot_3pct_longer = structure(list(lot = c("ABL GMP1", "MVS", "Tox Lot", "MVB1", 
"MVB2", "CTM2", "CTM1", "Fuji 30k", "Fuji 7.5k"), `12` = c(0.0382775119617225, 
0.0390625, 0.034883720930233, NA, NA, NA, NA, NA, NA), `13` = c(0.0588235294117647, 
NA, NA, 0.048076923076924, 0.0714285714285714, 0.0417789757412399, 
NA, NA, NA), `253` = c(NA, NA, 0.03360709902766, NA, NA, NA, 
NA, NA, NA), `1266` = c(0.0646451454923886, NA, NA, NA, NA, NA, 
NA, NA, NA), `1820` = c(1, NA, NA, NA, NA, NA, NA, NA, NA), `1821` = c(1, 
NA, NA, NA, NA, NA, NA, NA, NA), `2861` = c(0.0434994715017482, 
NA, NA, NA, NA, NA, NA, NA, NA), `3031` = c(0.183159188690842, 
NA, NA, NA, NA, NA, NA, NA, NA), `3252` = c(0.0521527362955475, 
NA, NA, NA, NA, NA, NA, NA, NA), `3368` = c(0.107515576323988, 
NA, NA, NA, NA, NA, NA, NA, NA), `3512` = c(0.345980014097939, 
NA, 0.064333937531195, NA, NA, 0.0822086320821032, 0.078818748712571, 
0.089279658964298, NA), `3527` = c(0.17209788747124, NA, 0.0377838832455329, 
NA, NA, 0.0471288691223414, 0.044333490343853, 0.059236465044716, 
NA), `3554` = c(0.250983372072233, NA, 0.05112660944206, NA, 
NA, 0.0639663737103554, 0.055374526495866, 0.0861535232698471, 
0.031875819851334), `4752` = c(NA, NA, 0.04827943749595, NA, 
NA, 0.0498005129666572, 0.049766115231033, 0.052495800335974, 
0.0519236625723281), `4761` = c(NA, NA, 0.038136808232708, NA, 
NA, 0.0317014863319821, 0.036080058906219, 0.034794423440454, 
0.033717392388648), `7078` = c(NA, NA, 0.032269021739131, NA, 
NA, NA, NA, NA, NA), `7299` = c(0.0830269157229004, 0.083128195417535, 
0.361278273500727, 0.375946173254836, 0.216166788588149, 0.110078513058805, 
0.10393717387867, 0.355137204850032, 0.310679611650486), `7300` = c(0.0525369400359628, 
0.050222762251924, 0.245149911816579, 0.232037691401649, 0.148067737733391, 
0.0629358437935844, 0.063008245663919, 0.236435818262021, 0.20123839009288
), `7301` = c(NA, NA, 0.0519736842105269, 0.038054968287527, 
NA, NA, NA, 0.037803780378038, 0.034240150093809), `7315` = c(NA, 
NA, NA, 0.037735849056604, 0.0406386066763426, NA, NA, NA, 0.036363636363637
), `7318` = c(0.0474754244861484, 0.07482430756511, NA, NA, 0.0369206598586017, 
0.0493811726465808, 0.046463780540078, NA, NA), `7319` = c(0.0623240852432649, 
0.083063994828701, NA, 0.0326086956521739, 0.058765915768854, 
0.0560072267389341, 0.0604447228311939, 0.053601340033501, 0.039495798319328
), `7320` = c(0.0808298755186722, 0.10897808803568, NA, 0.045643153526971, 
0.0581113801452785, 0.0764283011729096, 0.081006685017696, 0.04, 
0.031458531935177)), row.names = c(NA, -9L), groups = structure(list(
    lot = c("ABL GMP1", "CTM1", "CTM2", "Fuji 30k", "Fuji 7.5k", 
    "MVB1", "MVB2", "MVS", "Tox Lot"), .rows = structure(list(
        1L, 7L, 6L, 8L, 9L, 4L, 5L, 2L, 3L), ptype = integer(0), class = c("vctrs_list_of", 
    "vctrs_vctr", "list"))), row.names = c(NA, -9L), class = c("tbl_df", 
"tbl", "data.frame"), .drop = TRUE), class = c("grouped_df", 
"tbl_df", "tbl", "data.frame"))

5% Dataset

hotspot_5pct_longer = structure(list(lot = c("MVB2", "ABL GMP1", "CTM1", "CTM2", "Tox Lot", 
"Fuji 30k", "Fuji 7.5k", "MVB1", "MVS"), `13` = c(0.0714285714285714, 
0.0588235294117647, NA, NA, NA, NA, NA, NA, NA), `1266` = c(NA, 
0.0646451454923886, NA, NA, NA, NA, NA, NA, NA), `1820` = c(NA, 
1, NA, NA, NA, NA, NA, NA, NA), `1821` = c(NA, 1, NA, NA, NA, 
NA, NA, NA, NA), `3031` = c(NA, 0.183159188690842, NA, NA, NA, 
NA, NA, NA, NA), `3252` = c(NA, 0.0521527362955475, NA, NA, NA, 
NA, NA, NA, NA), `3368` = c(NA, 0.107515576323988, NA, NA, NA, 
NA, NA, NA, NA), `3512` = c(NA, 0.345980014097939, 0.078818748712571, 
0.0822086320821032, 0.064333937531195, 0.089279658964298, NA, 
NA, NA), `3527` = c(NA, 0.17209788747124, NA, NA, NA, 0.059236465044716, 
NA, NA, NA), `3554` = c(NA, 0.250983372072233, 0.055374526495866, 
0.0639663737103554, 0.05112660944206, 0.0861535232698471, NA, 
NA, NA), `4752` = c(NA, NA, NA, NA, NA, 0.052495800335974, 0.0519236625723281, 
NA, NA), `7299` = c(0.216166788588149, 0.0830269157229004, 0.10393717387867, 
0.110078513058805, 0.361278273500727, 0.355137204850032, 0.310679611650486, 
0.375946173254836, 0.083128195417535), `7300` = c(0.148067737733391, 
0.0525369400359628, 0.063008245663919, 0.0629358437935844, 0.245149911816579, 
0.236435818262021, 0.20123839009288, 0.232037691401649, 0.050222762251924
), `7301` = c(NA, NA, NA, NA, 0.0519736842105269, NA, NA, NA, 
NA), `7318` = c(NA, NA, NA, NA, NA, NA, NA, NA, 0.07482430756511
), `7319` = c(0.058765915768854, 0.0623240852432649, 0.0604447228311939, 
0.0560072267389341, NA, 0.053601340033501, NA, NA, 0.083063994828701
), `7320` = c(0.0581113801452785, 0.0808298755186722, 0.081006685017696, 
0.0764283011729096, NA, NA, NA, NA, 0.10897808803568)), row.names = c(NA, 
-9L), groups = structure(list(lot = c("ABL GMP1", "CTM1", "CTM2", 
"Fuji 30k", "Fuji 7.5k", "MVB1", "MVB2", "MVS", "Tox Lot"), .rows = structure(list(
    2L, 3L, 4L, 6L, 7L, 8L, 1L, 9L, 5L), ptype = integer(0), class = c("vctrs_list_of", 
"vctrs_vctr", "list"))), row.names = c(NA, -9L), class = c("tbl_df", 
"tbl", "data.frame"), .drop = TRUE), class = c("grouped_df", 
"tbl_df", "tbl", "data.frame"))

CodePudding user response：

Pass the options to webshot() by using vwidth and vheight. Refer the documentation,