scale_x_date returns error: how can I apply time frame to x-axis?
scale_x_date returns error: how can I apply time frame to x-axis?
我正在比较 Covid-19 大流行之前和期间每周 急性外科手术的频率。我有一个简单的线性回归，其中每个观察值对应一周，并以 lin.model$cons_week 表示。有 221 个观测值，对应于 2017-01-02（2017 年第一个星期一）到 2021-04-05
以来的连续 221 周
mod <- fortify(lm(n ~ cons_week * corona, data = lin.model))
其中n为手术次数，corona表示cons_week属于哪个时间段。
我有
mod %>%
ggplot(aes(y = .cooksd)) +
geom_col(data = filter(mod, corona == "Normal") %>% droplevels(),
aes(seq_along(.cooksd)),
color = "#6DBCC3", fill = alpha("#6DBCC3", .2)) +
geom_col(data = filter(mod, corona == "C19") %>% droplevels(),
aes(seq_along(.cooksd)+167),
color = "#8B3A62", fill = alpha("#8B3A62", .2)) +
geom_hline(yintercept = 4/nrow(lin.model), col = "black", lty = 2) +
geom_vline(xintercept = 167, color = "red", lty = 2) +
scale_y_continuous(name = "Cook's Distance")
给予
但是，我希望 x-axis 显示某种合理的时间线，因为 Cook's 中的每个观察对应 一个 周。
我试过了scale_date_x():
mod %>%
mutate(cons_week_dt = as.Date("2017-01-02") + cons_week*7) %>%
ggplot(aes(x = cons_week_dt, y = .cooksd)) +
geom_col(data = filter(mod, corona == "Normal") %>% droplevels(),
aes(seq_along(.cooksd)),
color = "#6DBCC3", fill = alpha("#6DBCC3", .2)) +
geom_col(data = filter(mod, corona == "C19") %>% droplevels(),
aes(seq_along(.cooksd)+167),
color = "#8B3A62", fill = alpha("#8B3A62", .2)) +
geom_hline(yintercept = 4/nrow(lin.model), col = "black", lty = 2) +
geom_vline(xintercept = 167, color = "red", lty = 2) +
scale_y_continuous(name = "Cook's Distance") +
scale_x_date(name = "",
date_breaks = "3 months", date_labels = "%B-%Y", expand = c(0.01, 0))
但是那个returns一个错误：
Error: Invalid input: date_trans works with objects of class Date only
lin.model <- structure(list(corona = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L), .Label = c("Normal", "C19"), class = "factor"), cons_week = c(56,
6, 150, 87, 16, 100, 16, 149, 62, 38, 74, 3, 80, 64, 72, 80,
71, 25, 100, 159, 80, 72, 35, 14, 55, 162, 14, 4, 100, 34, 81,
59, 156, 84, 165, 129, 70, 140, 113, 13, 65, 76, 33, 7, 93, 40,
107, 72, 43, 123, 142, 65, 83, 119, 63, 116, 18, 48, 97, 6, 93,
79, 81, 158, 8, 45, 143, 114, 83, 96, 26, 91, 113, 22, 54, 126,
93, 39, 33, 132, 97, 126, 136, 145, 35, 30, 109, 160, 20, 74,
162, 26, 112, 145, 28, 22, 28, 153, 131, 136, 209, 203, 188,
180, 214, 180, 176, 203, 219, 172, 222, 212, 183, 200, 218, 208,
198, 169, 210, 222, 207, 184, 175, 185, 198, 192, 206, 195, 219,
193, 197, 217, 204, 193, 193, 182, 175, 169, 170, 208, 192, 181,
186, 186, 209, 212, 200, 194, 213, 178, 213, 212, 209, 205, 183,
206, 199, 181, 187, 174, 177, 215, 193, 207, 207, 204, 187, 195,
174, 184, 171, 218, 188, 181, 197, 180, 208, 203, 192, 173, 218,
173, 196, 185, 212, 201, 194, 221, 205, 210, 213, 174, 207, 181,
189, 179, 200, 196, 216, 201), n = c(9L, 14L, 11L, 15L, 19L,
12L, 19L, 20L, 12L, 17L, 9L, 13L, 7L, 6L, 12L, 7L, 11L, 15L,
12L, 8L, 7L, 12L, 15L, 13L, 10L, 11L, 13L, 20L, 12L, 10L, 11L,
11L, 16L, 17L, 13L, 12L, 15L, 6L, 13L, 14L, 14L, 16L, 25L, 15L,
11L, 19L, 22L, 12L, 18L, 18L, 12L, 14L, 11L, 18L, 14L, 11L, 14L,
14L, 15L, 14L, 11L, 15L, 11L, 15L, 16L, 14L, 11L, 12L, 11L, 18L,
19L, 16L, 13L, 10L, 14L, 19L, 11L, 12L, 25L, 9L, 15L, 19L, 15L,
19L, 15L, 17L, 11L, 11L, 17L, 9L, 11L, 19L, 16L, 19L, 17L, 10L,
17L, 14L, 12L, 15L, 15L, 12L, 14L, 10L, 13L, 10L, 9L, 12L, 18L,
15L, 20L, 17L, 13L, 10L, 14L, 13L, 17L, 15L, 14L, 20L, 16L, 10L,
11L, 9L, 17L, 15L, 15L, 9L, 18L, 12L, 14L, 10L, 16L, 12L, 12L,
16L, 11L, 15L, 8L, 13L, 15L, 13L, 19L, 19L, 15L, 17L, 10L, 8L,
10L, 12L, 10L, 17L, 15L, 19L, 13L, 15L, 17L, 13L, 15L, 13L, 11L,
16L, 12L, 16L, 16L, 16L, 15L, 9L, 13L, 10L, 11L, 14L, 14L, 13L,
14L, 10L, 13L, 12L, 15L, 22L, 14L, 22L, 22L, 9L, 17L, 15L, 8L,
9L, 19L, 14L, 10L, 13L, 16L, 13L, 12L, 15L, 10L, 22L, 14L, 15L
)), row.names = c(NA, -200L), groups = structure(list(corona = structure(1:2, .Label = c("Normal",
"C19"), class = "factor"), .rows = structure(list(1:100, 101:200), ptype = integer(0), class = c("vctrs_list_of",
"vctrs_vctr", "list"))), row.names = c(NA, -2L), class = c("tbl_df",
"tbl", "data.frame"), .drop = TRUE), class = c("grouped_df",
"tbl_df", "tbl", "data.frame"))
您的代码的主要问题是您将 seq_along(.cooksd) 映射到 x。要解决此问题，只需将数据准备为一个单独的步骤，以便所有层都使用相同的数据。另外，不需要子集和两个geom_col。在 color 和 fill 上映射您的 var corona 并通过 scale_color/fill_manual
设置颜色时只需要一个
library(ggplot2)
library(dplyr)
mod <- fortify(lm(n ~ cons_week * corona, data = lin.model))
mod1 <- mod %>%
mutate(cons_week_dt = as.Date("2017-01-02") + cons_week*7)
cols <- c(Normal = "#6DBCC3", C19 = "#8B3A62")
ggplot(mod1, aes(x = cons_week_dt, y = .cooksd)) +
geom_col(aes(color = corona, fill = corona)) +
geom_hline(yintercept = 4/nrow(lin.model), col = "black", lty = 2) +
geom_vline(xintercept = 167, color = "red", lty = 2) +
scale_color_manual(values = cols) +
scale_fill_manual(values = alpha(cols, .2)) +
scale_y_continuous(name = "Cook's Distance") +
scale_x_date(name = "",
date_breaks = "3 months", date_labels = "%B-%Y", expand = c(0.01, 0)) +
guides(color = "none", fill = "none")
我正在比较 Covid-19 大流行之前和期间每周 急性外科手术的频率。我有一个简单的线性回归，其中每个观察值对应一周，并以 lin.model$cons_week 表示。有 221 个观测值，对应于 2017-01-02（2017 年第一个星期一）到 2021-04-05
mod <- fortify(lm(n ~ cons_week * corona, data = lin.model))
其中n为手术次数，corona表示cons_week属于哪个时间段。
我有
mod %>%
ggplot(aes(y = .cooksd)) +
geom_col(data = filter(mod, corona == "Normal") %>% droplevels(),
aes(seq_along(.cooksd)),
color = "#6DBCC3", fill = alpha("#6DBCC3", .2)) +
geom_col(data = filter(mod, corona == "C19") %>% droplevels(),
aes(seq_along(.cooksd)+167),
color = "#8B3A62", fill = alpha("#8B3A62", .2)) +
geom_hline(yintercept = 4/nrow(lin.model), col = "black", lty = 2) +
geom_vline(xintercept = 167, color = "red", lty = 2) +
scale_y_continuous(name = "Cook's Distance")
给予
但是，我希望 x-axis 显示某种合理的时间线，因为 Cook's 中的每个观察对应 一个 周。
我试过了scale_date_x():
mod %>%
mutate(cons_week_dt = as.Date("2017-01-02") + cons_week*7) %>%
ggplot(aes(x = cons_week_dt, y = .cooksd)) +
geom_col(data = filter(mod, corona == "Normal") %>% droplevels(),
aes(seq_along(.cooksd)),
color = "#6DBCC3", fill = alpha("#6DBCC3", .2)) +
geom_col(data = filter(mod, corona == "C19") %>% droplevels(),
aes(seq_along(.cooksd)+167),
color = "#8B3A62", fill = alpha("#8B3A62", .2)) +
geom_hline(yintercept = 4/nrow(lin.model), col = "black", lty = 2) +
geom_vline(xintercept = 167, color = "red", lty = 2) +
scale_y_continuous(name = "Cook's Distance") +
scale_x_date(name = "",
date_breaks = "3 months", date_labels = "%B-%Y", expand = c(0.01, 0))
但是那个returns一个错误：
Error: Invalid input: date_trans works with objects of class Date only
lin.model <- structure(list(corona = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L), .Label = c("Normal", "C19"), class = "factor"), cons_week = c(56,
6, 150, 87, 16, 100, 16, 149, 62, 38, 74, 3, 80, 64, 72, 80,
71, 25, 100, 159, 80, 72, 35, 14, 55, 162, 14, 4, 100, 34, 81,
59, 156, 84, 165, 129, 70, 140, 113, 13, 65, 76, 33, 7, 93, 40,
107, 72, 43, 123, 142, 65, 83, 119, 63, 116, 18, 48, 97, 6, 93,
79, 81, 158, 8, 45, 143, 114, 83, 96, 26, 91, 113, 22, 54, 126,
93, 39, 33, 132, 97, 126, 136, 145, 35, 30, 109, 160, 20, 74,
162, 26, 112, 145, 28, 22, 28, 153, 131, 136, 209, 203, 188,
180, 214, 180, 176, 203, 219, 172, 222, 212, 183, 200, 218, 208,
198, 169, 210, 222, 207, 184, 175, 185, 198, 192, 206, 195, 219,
193, 197, 217, 204, 193, 193, 182, 175, 169, 170, 208, 192, 181,
186, 186, 209, 212, 200, 194, 213, 178, 213, 212, 209, 205, 183,
206, 199, 181, 187, 174, 177, 215, 193, 207, 207, 204, 187, 195,
174, 184, 171, 218, 188, 181, 197, 180, 208, 203, 192, 173, 218,
173, 196, 185, 212, 201, 194, 221, 205, 210, 213, 174, 207, 181,
189, 179, 200, 196, 216, 201), n = c(9L, 14L, 11L, 15L, 19L,
12L, 19L, 20L, 12L, 17L, 9L, 13L, 7L, 6L, 12L, 7L, 11L, 15L,
12L, 8L, 7L, 12L, 15L, 13L, 10L, 11L, 13L, 20L, 12L, 10L, 11L,
11L, 16L, 17L, 13L, 12L, 15L, 6L, 13L, 14L, 14L, 16L, 25L, 15L,
11L, 19L, 22L, 12L, 18L, 18L, 12L, 14L, 11L, 18L, 14L, 11L, 14L,
14L, 15L, 14L, 11L, 15L, 11L, 15L, 16L, 14L, 11L, 12L, 11L, 18L,
19L, 16L, 13L, 10L, 14L, 19L, 11L, 12L, 25L, 9L, 15L, 19L, 15L,
19L, 15L, 17L, 11L, 11L, 17L, 9L, 11L, 19L, 16L, 19L, 17L, 10L,
17L, 14L, 12L, 15L, 15L, 12L, 14L, 10L, 13L, 10L, 9L, 12L, 18L,
15L, 20L, 17L, 13L, 10L, 14L, 13L, 17L, 15L, 14L, 20L, 16L, 10L,
11L, 9L, 17L, 15L, 15L, 9L, 18L, 12L, 14L, 10L, 16L, 12L, 12L,
16L, 11L, 15L, 8L, 13L, 15L, 13L, 19L, 19L, 15L, 17L, 10L, 8L,
10L, 12L, 10L, 17L, 15L, 19L, 13L, 15L, 17L, 13L, 15L, 13L, 11L,
16L, 12L, 16L, 16L, 16L, 15L, 9L, 13L, 10L, 11L, 14L, 14L, 13L,
14L, 10L, 13L, 12L, 15L, 22L, 14L, 22L, 22L, 9L, 17L, 15L, 8L,
9L, 19L, 14L, 10L, 13L, 16L, 13L, 12L, 15L, 10L, 22L, 14L, 15L
)), row.names = c(NA, -200L), groups = structure(list(corona = structure(1:2, .Label = c("Normal",
"C19"), class = "factor"), .rows = structure(list(1:100, 101:200), ptype = integer(0), class = c("vctrs_list_of",
"vctrs_vctr", "list"))), row.names = c(NA, -2L), class = c("tbl_df",
"tbl", "data.frame"), .drop = TRUE), class = c("grouped_df",
"tbl_df", "tbl", "data.frame"))
您的代码的主要问题是您将 seq_along(.cooksd) 映射到 x。要解决此问题，只需将数据准备为一个单独的步骤，以便所有层都使用相同的数据。另外，不需要子集和两个geom_col。在 color 和 fill 上映射您的 var corona 并通过 scale_color/fill_manual
library(ggplot2)
library(dplyr)
mod <- fortify(lm(n ~ cons_week * corona, data = lin.model))
mod1 <- mod %>%
mutate(cons_week_dt = as.Date("2017-01-02") + cons_week*7)
cols <- c(Normal = "#6DBCC3", C19 = "#8B3A62")
ggplot(mod1, aes(x = cons_week_dt, y = .cooksd)) +
geom_col(aes(color = corona, fill = corona)) +
geom_hline(yintercept = 4/nrow(lin.model), col = "black", lty = 2) +
geom_vline(xintercept = 167, color = "red", lty = 2) +
scale_color_manual(values = cols) +
scale_fill_manual(values = alpha(cols, .2)) +
scale_y_continuous(name = "Cook's Distance") +
scale_x_date(name = "",
date_breaks = "3 months", date_labels = "%B-%Y", expand = c(0.01, 0)) +
guides(color = "none", fill = "none")