我在 R 中有一个名为 df 的数据框:
# Load necessary libraries
library(tibble)
library(tidyverse)
library(ggplot2)
library(ggpubr)
library(ggstats)
# Define categories and Likert levels
var_levels <- c("A", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "L", "M", "N", "O", "P", "Q")
likert_levels <- c(
"Strongly disagree",
"Disagree",
"Neither agree nor disagree",
"Agree",
"Strongly agree"
)
# Set seed for reproducibility
set.seed(42)
# Create the dataframe with three Likert response columns
df <- tibble(
var = sample(var_levels, 50, replace = TRUE), # Random values from A to Q
val1 = sample(likert_levels, 50, replace = TRUE) # Random values from Likert levels
)
# View the first few rows of the dataframe
print(df)
我正在使用之前在这里询问的解决方案
展开它并要求在它旁边添加另一个条形图,其中包含每个类别的计数。我想将每个条形与左侧的水平李克特量表相匹配。我怎样才能在 R 中成功?
ibrary(tidyverse)
library(ggstats)
dat <- df |>
mutate(
across(-var, ~ factor(.x, likert_levels))
) |>
pivot_longer(-var, names_to = "group") |>
count(var, value, group) |>
complete(var, value, group, fill = list(n = 0)) |>
mutate(
prop = n / sum(n),
prop_lower = sum(prop[value %in% c("Strongly disagree", "Disagree")]),
prop_higher = sum(prop[value %in% c("Strongly agree", "Agree")]),
.by = c(var, group)
) |>
arrange(group, prop_lower) |>
mutate(
y_sort = paste(var, group, sep = "."),
y_sort = fct_inorder(y_sort)
)
top10 <- dat |>
distinct(group, var, prop_lower) |>
slice_max(prop_lower, n = 10, by = group)
dat <- dat |>
semi_join(top10)
dat_tot <- dat |>
distinct(group, var, y_sort, prop_lower, prop_higher) |>
pivot_longer(-c(group, var, y_sort),
names_to = c(".value", "name"),
names_sep = "_"
) |>
mutate(
hjust_tot = ifelse(name == "lower", 1, 0),
x_tot = ifelse(name == "lower", -1, 1)
)
ggplot(dat, aes(y = y_sort, x = prop, fill = value)) +
geom_col(position = position_likert(reverse = FALSE)) +
geom_text(
aes(
label = label_percent_abs(hide_below = .05, accuracy = 1)(prop),
color = after_scale(hex_bw(.data$fill))
),
position = position_likert(vjust = 0.5, reverse = FALSE),
size = 3.5
) +
geom_label(
aes(
x = x_tot,
label = label_percent_abs(accuracy = 1)(prop),
hjust = hjust_tot,
fill = NULL
),
data = dat_tot,
size = 3.5,
color = "black",
fontface = "bold",
label.size = 0,
show.legend = FALSE
) +
scale_y_discrete(labels = \(x) gsub("\\..*$", "", x)) +
scale_x_continuous(
labels = label_percent_abs(),
expand = c(0, .15)
) +
scale_fill_brewer(palette = "BrBG") +
facet_wrap(~group,
scales = "free_y", ncol = 1,
strip.position = "right"
) +
theme_light() +
theme(
legend.position = "bottom",
panel.grid.major.y = element_blank()
) +
labs(x = NULL, y = NULL, fill = NULL)
我的努力
dat%>%
select(var,n)%>%
group_by(var)%>%
summarise(count = sum(n))%>%
ggplot(., aes(y = var, x = count)) +
geom_bar(stat = "identity", fill = "lightgrey")+labs(x="Response Count",y="")+
geom_text(aes(label = count),position = position_stack(vjust = .5)) +
theme_bw()+
theme(
axis.text.y = element_blank(),
axis.ticks.y = element_blank(),
axis.text.x = element_blank(), # Remove x-axis text
axis.ticks.x = element_blank() # Remove x-axis ticks
)
如果我正确理解你的问题,你可以使用
patchwork
包来做到这一点。 将绘图添加在一起将使它们并排匹配绘图区域:
library(tibble)
library(tidyverse)
library(ggplot2)
library(ggpubr)
library(ggstats)
# Define categories and Likert levels
var_levels <- c("A", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "L", "M", "N", "O", "P", "Q")
likert_levels <- c(
"Strongly disagree",
"Disagree",
"Neither agree nor disagree",
"Agree",
"Strongly agree"
)
# Set seed for reproducibility
set.seed(42)
# Create the dataframe with three Likert response columns
df <- tibble(
var = sample(var_levels, 50, replace = TRUE), # Random values from A to Q
val1 = sample(likert_levels, 50, replace = TRUE) # Random values from Likert levels
)
library(tidyverse)
library(ggstats)
dat <- df |>
mutate(
across(-var, ~ factor(.x, likert_levels))
) |>
pivot_longer(-var, names_to = "group") |>
count(var, value, group) |>
complete(var, value, group, fill = list(n = 0)) |>
mutate(
prop = n / sum(n),
prop_lower = sum(prop[value %in% c("Strongly disagree", "Disagree")]),
prop_higher = sum(prop[value %in% c("Strongly agree", "Agree")]),
.by = c(var, group)
) |>
arrange(group, prop_lower) |>
mutate(
y_sort = paste(var, group, sep = "."),
y_sort = fct_inorder(y_sort)
)
top10 <- dat |>
distinct(group, var, prop_lower) |>
slice_max(prop_lower, n = 10, by = group)
dat <- dat |>
semi_join(top10)
#> Joining with `by = join_by(var, group, prop_lower)`
dat_tot <- dat |>
distinct(group, var, y_sort, prop_lower, prop_higher) |>
pivot_longer(-c(group, var, y_sort),
names_to = c(".value", "name"),
names_sep = "_"
) |>
mutate(
hjust_tot = ifelse(name == "lower", 1, 0),
x_tot = ifelse(name == "lower", -1, 1)
)
p1 <- ggplot(dat, aes(y = y_sort, x = prop, fill = value)) +
geom_col(position = position_likert(reverse = FALSE)) +
geom_text(
aes(
label = label_percent_abs(hide_below = .05, accuracy = 1)(prop),
color = after_scale(hex_bw(.data$fill))
),
position = position_likert(vjust = 0.5, reverse = FALSE),
size = 3.5
) +
geom_label(
aes(
x = x_tot,
label = label_percent_abs(accuracy = 1)(prop),
hjust = hjust_tot,
fill = NULL
),
data = dat_tot,
size = 3.5,
color = "black",
fontface = "bold",
label.size = 0,
show.legend = FALSE
) +
scale_y_discrete(labels = \(x) gsub("\\..*$", "", x)) +
scale_x_continuous(
labels = label_percent_abs(),
expand = c(0, .15)
) +
scale_fill_brewer(palette = "BrBG") +
facet_wrap(~group,
scales = "free_y", ncol = 1,
strip.position = "right"
) +
theme_light() +
theme(
legend.position = "bottom",
panel.grid.major.y = element_blank()
) +
labs(x = NULL, y = NULL, fill = NULL)
p2 <- dat%>%
select(var,n)%>%
group_by(var)%>%
summarise(count = sum(n))%>%
ggplot(., aes(y = var, x = count)) +
geom_bar(stat = "identity", fill = "lightgrey")+labs(x="Response Count",y="")+
geom_text(aes(label = count),position = position_stack(vjust = .5)) +
theme_bw()+
theme(
axis.text.y = element_blank(),
axis.ticks.y = element_blank(),
axis.text.x = element_blank(), # Remove x-axis text
axis.ticks.x = element_blank() # Remove x-axis ticks
)
library(patchwork)
p1 + p2 + plot_layout(guides = "collect") & theme(legend.position="bottom")
创建于 2024 年 11 月 13 日,使用 reprex v2.1.0