gt包创建和定制表格

R语言数据分析指南

发布于 2024-01-23 13:56:49

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代码可运行

文章被收录于专栏：R语言数据分析指南

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代码可运行

官方文档

❝https://github.com/rstudio/gt ❞

加载R包

devtools::install_github("rstudio/gt")
library(gt)
library(tidyverse)

案例1

dplyr::tibble(a = c(
  paste(rnorm(20, 20, 10), collapse = ","),  # 创建一个包含正态分布随机数的字符串
  paste(rnorm(100, 0, 5), collapse = ","),  # 创建另一个包含正态分布随机数的字符串
  paste(rnorm(15, 8, 2), collapse = ","),  # 再创建一个包含正态分布随机数的字符串
  paste(rnbinom(120, 10, 0.5), collapse = ","),  # 创建一个包含负二项分布随机数的字符串
  paste(rnbinom(150, 5, 0.25), collapse = ",")  # 创建另一个包含负二项分布随机数的字符串
)) %>%
  gt() %>%
  cols_nanoplot(columns = a, plot_type = "boxplot") %>%
  cols_hide(columns = a)  # 创建一个gt表格，添加箱线图，并隐藏原始数据列

案例2


dplyr::tibble(
  a = c(-20, -10, 0, 10, 5)
) |>
  gt() |>
  cols_nanoplot(
    columns = a,
    plot_type = "bar",
    options = nanoplot_options(
      data_bar_negative_fill_color = "lightblue",  # 设置负值条形图的填充颜色
      data_bar_fill_color = "lightgreen",  # 设置正值条形图的填充颜色
      data_bar_stroke_color = "forestgreen",  # 设置正值条形图的边框颜色
      data_bar_negative_stroke_color = "steelblue",  # 设置负值条形图的边框颜色
      interactive_data_values = FALSE  # 设置条形图为非交互式
    )
  ) |>
  tab_style(
    style = cell_borders(sides = c("left", "right"), weight = "2px"),  # 设置单元格边框样式
    locations = cells_body(columns = nanoplots)  # 应用样式到包含nanoplots的单元格
  )

案例3

illness |>
  dplyr::slice_head(n = 10) |>
  gt(rowname_col = "test") |>
  tab_header("Partial summary of daily tests performed on YF patient") |>
  tab_stubhead(label = md("**Test**")) |>
  cols_hide(columns = c(starts_with("norm"), starts_with("day"))) |>
  fmt_units(columns = units) |>
  cols_nanoplot(
    columns = starts_with("day"),
    new_col_name = "nanoplots",
    new_col_label = md("*Progression*"),
    options = nanoplot_options(data_area_fill_color = "lightgreen")  # 设置区域图的填充颜色
  ) |>
  cols_align(align = "center", columns = nanoplots) |>
  cols_merge(columns = c(test, units), pattern = "{1} ({2})") |>
  tab_footnote(
    footnote = "Measurements from Day 3 through to Day 8.",  # 添加脚注
    locations = cells_column_labels(columns = nanoplots))  # 指定脚注位置