ggplot中的面板数据移动平均线答案

【问题标题】：Panel data moving average in ggplotggplot中的面板数据移动平均线
【发布时间】：2020-05-11 10:39:37
【问题描述】：

我正在处理如下所示的面板数据：

library(dplyr)
library(ggplot2)

df <- tibble(id = rep(1:5, each = 12),
             year = rep(2009:2020, 5),
             moved = c(1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1, 1, 0,
                       1, 0, 1, 0 , 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 0 , 1, 0),
             occupation = c('carpenter','carpenter', 'carpenter', 'carpenter', 'carpenter', 'cleaner',
                            'cleaner', 'cleaner', 'cleaner', 'cleaner', 'mechanic', 'mechanic',
                            'mechanic', 'mechanic', 'mechanic', 'carpenter', 'carpenter', 'carpenter',
                            'carpenter', 'carpenter', 'cleaner', 'mechanic', 'carpenter', 'cleaner',
                            'cleaner', 'carpenter', 'cleaner', 'mechanic', 'mechanic', 'mechanic',
                            'carpenter','carpenter', 'carpenter', 'carpenter', 'carpenter', 'cleaner',
                            'cleaner', 'cleaner', 'cleaner', 'cleaner', 'mechanic', 'mechanic',
                            'mechanic', 'mechanic', 'mechanic', 'carpenter', 'carpenter', 'carpenter',
                            'carpenter', 'carpenter', 'cleaner', 'mechanic', 'carpenter', 'cleaner',
                            'cleaner', 'carpenter', 'cleaner', 'mechanic', 'mechanic', 'mechanic'))

为了可视化随时间推移的职业移动，我使用了以下代码：

ggplot(df,aes(x=year,y=moved,col=occupation)) +
  stat_summary(fun=mean,geom="line",alpha=0.7, size=1)

现在我想重新制作面板，以便获得“已移动”的 2 年移动平均线。是否可以通过使用 ggplot 来做到这一点，还是我需要重新制作面板？最好的解决方案是什么？

【问题讨论】：

标签： r ggplot2 dplyr

【解决方案1】：

这是一个可能的解决方案。通常最好在数据框中进行计算。这是一种方法。我对最终图表的外观做了一些假设，因为问题中没有任何要求，所以我选择了清晰。

library(dplyr)
library(tidyr)
library(zoo)
library(ggplot2)

#Data

df <- tibble(id = rep(1:5, each = 12),
             year = rep(2009:2020, 5),
             moved = c(1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1, 1, 0,
                       1, 0, 1, 0 , 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 0 , 1, 0),
             occupation = c('carpenter','carpenter', 'carpenter', 'carpenter', 'carpenter', 'cleaner',
                            'cleaner', 'cleaner', 'cleaner', 'cleaner', 'mechanic', 'mechanic',
                            'mechanic', 'mechanic', 'mechanic', 'carpenter', 'carpenter', 'carpenter',
                            'carpenter', 'carpenter', 'cleaner', 'mechanic', 'carpenter', 'cleaner',
                            'cleaner', 'carpenter', 'cleaner', 'mechanic', 'mechanic', 'mechanic',
                            'carpenter','carpenter', 'carpenter', 'carpenter', 'carpenter', 'cleaner',
                            'cleaner', 'cleaner', 'cleaner', 'cleaner', 'mechanic', 'mechanic',
                            'mechanic', 'mechanic', 'mechanic', 'carpenter', 'carpenter', 'carpenter',
                            'carpenter', 'carpenter', 'cleaner', 'mechanic', 'carpenter', 'cleaner',
                            'cleaner', 'carpenter', 'cleaner', 'mechanic', 'mechanic', 'mechanic'))


#data wrangle

df1 <- 
  df %>% 
  group_by(occupation, year) %>%
  summarise(m_moves = mean(moved)) %>% 
  mutate(m_avg = rollmean(m_moves, 2, fill = NA, align = "right")) %>% 
  pivot_longer(cols = c(m_moves, m_avg), names_to = "avg", values_to = "val")

# Plot

ggplot(df1,aes(year, val))+
  geom_line(aes(linetype = avg, colour = occupation)) +
  scale_linetype_discrete(labels = c("2 year moving average", "Average moves"))+
  facet_wrap(~occupation, ncol = 1)+
  guides(colour = FALSE)+
  labs(linetype = "Average measure:")+
  theme(legend.position = "bottom")
#> Warning: Removed 3 row(s) containing missing values (geom_path).

^{由reprex package (v0.3.0) 于 2020-05-11 创建}

【讨论】：