Ytukyg

I have the below dataframes and want to plot 2 weeks of data with ggplot.

df<-data.frame(

  Date=sample(seq(as.Date('2018-10-25'), as.Date('2018-11-20'), by = "day"), 100,replace = T),

  category1=sample(letters[1:6],100,replace = T),

  count=sample(1:1000,100,replace = T)

)

Data Frame-1 (Last 7 Days)

df1<-df%>%select(everything())%>%filter(Date < Sys.Date()-1 & Date>=Sys.Date()-8)%>%

  group_by(Date,category1)%>%summarise(Total=sum(count))

Data Frame-2 (Last 8 days to 15 days)

df2<-df%>%select(everything())%>%filter(Date < Sys.Date()-8 & Date>=Sys.Date()-15)%>%

  group_by(Date,category1)%>%summarise(Total=sum(count))

Plots :

ggplot(df1,aes(Date,Total,fill=category1))+geom_bar(stat = "identity",position = "stack",width = 0.8,alpha=0.8)

ggplot(df2,aes(Date,Total,fill=category1))+geom_bar(stat = "identity",position = "stack",width = 0.8,alpha=0.8)

Now how to plot the same content comparing the 2 plots ?
Any extra information if required please let me know.

Here's an approach using facets, where I show each date of the last week as a facet, with the # of whole weeks prior on the x axis of each facet.

library(tidyverse)

df1 <- df %>%

  mutate(days_old = (as.Date("2018-11-20") - Date) / lubridate::ddays(1),

         weeks_ago = days_old %/% 7,

         adj_to_this_week = as.Date("2018-11-20") - days_old %% 7) %>%

  group_by(adj_to_this_week, weeks_ago, category1) %>% 

  summarise(Total=sum(count))





ggplot(df1 %>%

         filter(weeks_ago <= 1) %>%

         mutate(nice_dates = format(adj_to_this_week, "%b %d") %>% 

                             fct_reorder(adj_to_this_wk)), 

       aes(-weeks_ago, Total,fill=category1)) + 

  geom_bar(stat = "identity",position = "stack",width = 0.8,alpha=0.8) +

  scale_x_continuous(breaks = -1:0, labels = c("LW", "TW")) +

  facet_wrap(~nice_dates, nrow = 1) +

  labs(title = "Last week (LW) vs. This week (TW)", x ="") +

  theme(panel.grid.major.x = element_blank(),

        panel.grid.minor.x = element_blank())

Sample data:

set.seed(42)

df<-data.frame(

  Date=sample(seq(as.Date('2018-10-25'), as.Date('2018-11-20'), by = "day"), 100,replace = T),

  category1=sample(letters[1:6],100,replace = T),

  count=sample(1:1000,100,replace = T)

)