Jan Broder Engler

@jbengler.de

3223 Followers 844 Following

Scientist and software developer. Creator of tidyplots.org and sepacode.app. Website jbengler.de.

library(tidyplots) spendings |> tidyplot(x = category, y = amount, color = category) |> add_sum_bar() |> adjust_x_axis(rotate_labels = TRUE) |> sort_x_axis_levels() |> adjust_colors(new_colors = colors_discrete_candy)
library(pak) # install the latest CRAN release pak("tidyplots") # install the development version pak("jbengler/tidyplots") # install a specific version pak("jbengler/tidyplots@v0.0.1") # install a specific commit pak("jbengler/tidyplots@9f7294a")
library(tidyplots) animals |> tidyplot(x = weight, y = size) |> add_data_points() |> add_data_points(data = max_rows(weight, n = 3), color = "red", shape = 1, size = 3)
library(tidyplots) climate |> tidyplot(x = month, y = max_temperature) |> add_data_points_beeswarm(alpha = 0.3, color = "grey") |> add_mean_line(linewidth = 0.5) |> add_sd_ribbon()
library(tidyplots) study |> tidyplot(x = treatment, y = score, color = treatment) |> add_mean_bar(alpha = 0.4) |> add_sem_errorbar() |> add_data_points_beeswarm() |> remove_legend() |> remove_x_axis_ticks() |> remove_y_axis_title()
library(tidyplots) animals |> tidyplot(x = weight, y = size) |> add_data_points() |> add_data_labels_repel(data = max_rows(weight, n = 3), label = animal, color = "black")
library(tidyplots) my_style <- function(x) { x |> adjust_colors(colors_discrete_apple) |> adjust_font(family = "mono", face = "bold") |> remove_x_axis_ticks() |> remove_y_axis_ticks() } energy_week |> tidyplot(date, power, color = energy_source) |> add_areastack_relative() |> my_style()
library(tidyplots) climate |> tidyplot(x = month, y = max_temperature) |> add_data_points_beeswarm(white_border = TRUE, rasterize = TRUE, rasterize_dpi = 100)
library(tidyplots) gene_expression |> head(n = 180) |> tidyplot(x = group, y = expression, color = group) |> add_mean_bar(alpha = 0.3) |> add_sem_errorbar() |> add_data_points_beeswarm(white_border = TRUE) |> adjust_size(width = 25, height = 25) |> split_plot(by = external_gene_name, ncol = 3, nrow = 3)
library(tidyplots) gene_expression |> tidyplot(x = group, y = expression, color = group) |> add_violin() |> add_data_points_beeswarm(white_border = TRUE) |> adjust_size(width = 25, height = 25) |> split_plot(by = external_gene_name, ncol = 3, nrow = 4) |> save_plot("my_genes.pdf")
library(tidyplots) gene_expression |> tidyplot(x = group, y = expression, color = group) |> add_violin() |> add_data_points_beeswarm(white_border = TRUE) |> split_plot(by = external_gene_name, ncol = 1, nrow = 1) |> save_plot("my_genes.pdf", multiple_files = TRUE)
library(tidyplots) study |> tidyplot(x = group, y = score, color = dose) |> add_mean_dash() |> add_sem_errorbar() |> add_data_points_beeswarm() |> save_plot("my_plot.pdf") |> save_plot("my_plot.png") |> save_plot("my_plot.svg")
library(tidyplots) study |> tidyplot(x = treatment, y = score, color = treatment) |> add_violin() |> add_data_points_beeswarm() |> adjust_colors(new_colors = c("A" = "#5B8DFE", "B" = "#DD227D", "C" = "#FE5F00", "D" = "#FFB109"))
library(tidyplots) study |> tidyplot(x = group, y = score, color = dose) |> add_boxplot() |> add_mean_dash() |> add_test_asterisks()
library(tidyplots) spendings |> tidyplot(x = category, y = amount, color = category) |> add_sum_bar(alpha = 0.2) |> add_sum_dash() |> add_sum_value(accuracy = 1, color = "black") |> adjust_x_axis(rotate_labels = TRUE)
library(tidyplots) spendings |> tidyplot(x = category, y = amount, color = category) |> add_sum_bar(alpha = 0.2) |> add_sum_dash() |> add_sum_value(accuracy = 1, color = "black") |> adjust_x_axis(rotate_labels = TRUE) |> sort_x_axis_levels()
df_error <- data.frame( treatment = c("A", "B", "C", "D"), ymin = c(3,5,20,20), ymax = c(5,20,60,40), score = NA ) study |> tidyplot(x = treatment, y = score, color = treatment) |> add_mean_dash() |> add_data_points() |> add(geom_errorbar(data = df_error, mapping = aes(ymin = ymin, ymax = ymax), width = 0.4, linewidth = 0.25))
library(tidyplots) spendings |> tidyplot(x = amount, y = category, color = category) |> add_sum_bar(alpha = 0.2) |> add_sum_dash() |> add_sum_value(accuracy = 1, color = "black") |> sort_y_axis_levels() |> remove_legend()
library(tidyplots) energy |> tidyplot(x = year, y = energy, color = energy_type) |> add_barstack_absolute()
library(tidyplots) x <- c(2.3, 4.5, 6.3, 3.4, 7.8, 6.7) df <- data.frame( x = c(x, x + c(0.8, 0.75)), group = paste0("g", rep(c(1, 2), each = 6)), batch = paste0("b", c(1:6, 1:6)), shuffle = paste0("c", c(1:6, 6:1)) ) df |> tidyplot(group, x, color = group) |> add_boxplot() |> add_data_points() |> add_test_pvalue(paired_by = batch) |> add_line(group = batch, color = "black")
library(tidyplots) study |> tidyplot(x = treatment, y = score, color = treatment) |> add_mean_dash() |> add_sem_errorbar() |> add_data_points() |> add_test_pvalue(comparisons = list(c(1,3),c(2,4)))
library(tidyplots) gene_expression |> tidyplot(x = group, y = expression, color = group) |> add_violin() |> add_data_points_beeswarm(white_border = TRUE) |> view_plot(data = filter_rows(external_gene_name == "Apol6"), title = "Apol6")
library(tidyplots) # Define style my_style <- function(x) x |> adjust_colors(colors_discrete_candy) |> adjust_font(family = "mono") |> adjust_size(height = 30) # Set global options tidyplots_options(my_style = my_style) study |> tidyplot(x = group, y = score, color = dose) |> add_mean_bar() # Reset global options tidyplots_options()
library(tidyplots) time_course |> tidyplot(x = day, y = score, color = treatment) |> add_mean_line() |> add_mean_dot() |> add_sem_ribbon()
library(tidyplots) study |> tidyplot(x = treatment, y = score, color = treatment) |> add_mean_dash() |> save_plot("stage_1.pdf") |> add_sem_errorbar() |> save_plot("stage_2.pdf") |> add_data_points_beeswarm() |> save_plot("stage_3.pdf")
library(tidyplots) study |> tidyplot(x = treatment, y = score, color = treatment) |> add_violin() |> add_data_points_beeswarm(white_border = TRUE) |> reorder_x_axis_levels("C", "D", "A", "B")
library(tidyplots) study |> tidyplot(x = treatment, y = score, color = treatment) |> add_violin() |> add_data_points_beeswarm(white_border = TRUE) |> rename_x_axis_levels(new_names = c( "A" = "Dog", "B" = "Cat", "C" = "Hamster", "D" = "Dinosaur"))
library(tidyplots) spendings |> tidyplot(x = category, y = amount, color = category) |> add_sum_bar() |> adjust_x_axis(rotate_labels = TRUE) |> sort_x_axis_levels()
library(tidyplots) spendings |> tidyplot(x = category, y = amount, color = category) |> add_sum_bar(alpha = 0.2) |> add_sum_dash() |> add_sum_value(accuracy = 1, color = "black") |> adjust_x_axis(rotate_labels = TRUE) |> sort_x_axis_levels()
library(tidyplots) spendings |> tidyplot(x = category, y = amount, color = category) |> add_sum_bar() |> adjust_x_axis(rotate_labels = TRUE) |> sort_x_axis_levels() |> adjust_colors(new_colors = c("Health" = "#ff3b30"), na.value = "lightgrey")
library(tidyheatmaps) tidyheatmap(df = data_exprs, rows = external_gene_name, columns = sample, values = expression, scale = "row", annotation_col = c(sample_type, condition, group), annotation_row = c(is_immune_gene, direction), gaps_row = direction, gaps_col = group )
library(tidyplots) new_color_scheme( c("#085578","#538085","#faf1e2","#e3baaa","#e47e8c","#ffaa6a"), name = "My custom color scheme")
library(pak) # install the latest CRAN release pak("tidyplots") # install the development version pak("jbengler/tidyplots") # install a specific version pak("jbengler/tidyplots@v0.0.1") # install a specific commit pak("jbengler/tidyplots@9f7294a")
library(tidyplots) animals |> tidyplot(x = weight, y = size) |> add_data_points() |> add_data_points(data = max_rows(weight, n = 3), color = "red", shape = 1, size = 3)