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This is a small list with 25 visualization using gt Package.
GT package is one of the most amazing package to create tables, and we want to show a gallery of examples with full R code to encourage you to use it in your projects.
An informal definition could be: “A good table sirve para leer de la forma mas rapida y facil un conjunto de datos numericos”.
library(gt)
library(tidyverse)
library(glue)
# Define the start and end dates for the data range
start_date <- "2010-06-07"
end_date <- "2010-06-14"
# Create a gt table based on preprocessed
# `sp500` table data
sp500 %>%
dplyr::filter(date >= start_date & date <= end_date) %>%
dplyr::select(-adj_close) %>%
dplyr::mutate(date = as.character(date)) %>%
gt() %>%
tab_header(
title = "S&P 500",
subtitle = glue::glue("{start_date} to {end_date}")
) %>%
fmt_date(
columns = vars(date),
date_style = 3
) %>%
fmt_currency(
columns = vars(open, high, low, close),
currency = "USD"
) %>%
fmt_number(
columns = vars(volume),
scale_by = 1 / 1E9,
pattern = "{x}B"
)
S&P 500 | |||||
---|---|---|---|---|---|
2010-06-07 to 2010-06-14 | |||||
date | open | high | low | close | volume |
Mon, Jun 14, 2010 | $1,095.00 | $1,105.91 | $1,089.03 | $1,089.63 | 4.43B |
Fri, Jun 11, 2010 | $1,082.65 | $1,092.25 | $1,077.12 | $1,091.60 | 4.06B |
Thu, Jun 10, 2010 | $1,058.77 | $1,087.85 | $1,058.77 | $1,086.84 | 5.14B |
Wed, Jun 9, 2010 | $1,062.75 | $1,077.74 | $1,052.25 | $1,055.69 | 5.98B |
Tue, Jun 8, 2010 | $1,050.81 | $1,063.15 | $1,042.17 | $1,062.00 | 6.19B |
Mon, Jun 7, 2010 | $1,065.84 | $1,071.36 | $1,049.86 | $1,050.47 | 5.47B |
This example is Table S2 in Broman et al. (2015) Genetics 192:267-279 doi:https://doi.org/10.1534/genetics.112.142448
# the table's data
tab <- data.frame(n=c(300, 450, 600),
all_part_all_crosses = c(4.56, 4.51, 4.49),
all_part_min_crosses = c(4.48, 4.47, 4.44),
tree_part_all_crosses = c(4.43, 4.36, 4.32),
tree_part_min_crosses = c(4.33, 4.33, 4.29))
# create the gt table
gt(tab) %>%
cols_align("center") %>%
cols_label(n="total sample size",
all_part_all_crosses="all crosses",
all_part_min_crosses="min crosses",
tree_part_all_crosses="all crosses",
tree_part_min_crosses="min crosses") %>%
tab_spanner(label="Tree partitions",
starts_with("tree")) %>%
tab_spanner(label="All partitions",
starts_with("all"))
total sample size | All partitions | Tree partitions | ||
---|---|---|---|---|
all crosses | min crosses | all crosses | min crosses | |
300 | 4.56 | 4.48 | 4.43 | 4.33 |
450 | 4.51 | 4.47 | 4.36 | 4.33 |
600 | 4.49 | 4.44 | 4.32 | 4.29 |
sessionInfo()
R version 3.5.1 (2018-07-02)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: OS X El Capitan 10.11.6
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] bindrcpp_0.2.2 glue_1.3.0 forcats_0.3.0 stringr_1.3.1
[5] dplyr_0.7.8 purrr_0.2.5 readr_1.1.1 tidyr_0.8.2
[9] tibble_1.4.2 ggplot2_3.1.0 tidyverse_1.2.1 gt_0.1.0
loaded via a namespace (and not attached):
[1] tidyselect_0.2.5 haven_1.1.2 lattice_0.20-35 colorspace_1.3-2
[5] htmltools_0.3.6 yaml_2.2.0 rlang_0.3.0.1 pillar_1.3.1
[9] withr_2.1.2 modelr_0.1.2 readxl_1.1.0 bindr_0.1.1
[13] plyr_1.8.4 munsell_0.5.0 commonmark_1.7 gtable_0.2.0
[17] workflowr_1.2.0 cellranger_1.1.0 rvest_0.3.2 evaluate_0.12
[21] knitr_1.20 broom_0.5.0 Rcpp_1.0.0 scales_1.0.0
[25] backports_1.1.2 checkmate_1.8.5 jsonlite_1.6 fs_1.2.6
[29] hms_0.4.2 digest_0.6.18 stringi_1.2.4 grid_3.5.1
[33] rprojroot_1.3-2 cli_1.0.1 tools_3.5.1 magrittr_1.5
[37] sass_0.1.0.9000 lazyeval_0.2.1 crayon_1.3.4 whisker_0.3-2
[41] pkgconfig_2.0.2 xml2_1.2.0 lubridate_1.7.4 assertthat_0.2.0
[45] rmarkdown_1.10 httr_1.3.1 rstudioapi_0.8 R6_2.3.0
[49] nlme_3.1-137 git2r_0.23.0 compiler_3.5.1