假设我们跑了install.packages("ggplot2")
install.packages("babynames")
然后
library(babynames)
data(babynames)
my_d <- babynames %>%
filter(
name == "Josiah" & sex == "M" |
name == "Alicia" & sex == "F" |
name == "Gabriel" & sex == "M" |
name == "Joshua" & sex == "M"
) %>%
group_by(name, year, sex) %>%
summarise(n = sum(n) ) %>%
arrange(year)
ggplot(my_d, aes(x = year, y = n, color = name) ) +
geom_line(se = FALSE) +
scale_x_continuous(breaks = seq(1900, 2020, by = 10) )
给予
很好,但是我想“稍微”使它平滑,所以我愿意
ggplot(my_d, aes(x = year, y = n, color = name) ) +
geom_smooth(se = FALSE) +
scale_x_continuous(breaks = seq(1900, 2020, by = 10) )
这很平滑,但是为“约书亚”添加了负值。
如何避免这种“副作用”?
编辑:更改
geom_smooth(se = FALSE)
到
geom_smooth(se = FALSE, method = "loess") +
ylim(0, 30000)
除去负值,但“平滑度”仍然很粗糙,也可以说。它显示“ Gabriel”具有增加的趋势,但不是。结果是
span =
参数应根据documentation进行平滑“ wigglier”。也许解决这个问题将解决您的问题。以下是span = .1
的示例。粗略的边缘已经消失了,但是总体趋势趋于保持可见和真实。 span
设置得太低可能会导致存储问题,具体取决于数据的大小。
library(babynames)
library(tidyverse)
data(babynames)
my_d <- babynames %>%
filter(
name == "Josiah" & sex == "M" |
name == "Alicia" & sex == "F" |
name == "Gabriel" & sex == "M" |
name == "Joshua" & sex == "M"
) %>%
group_by(name, year, sex) %>%
summarise( n = sum(n) ) %>%
arrange( year )
ggplot( my_d, aes(x = year, y = n, color = name) ) +
geom_smooth(se = FALSE, method = "loess", span = .1) +
scale_x_continuous( breaks = seq(1900, 2020, by = 10) )
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由reprex package(v0.3.0)在2020-02-21创建