CODEWITHSUNDEEP
rggplot2
Banjo
Banjo

Reputation: 1251

Plotting the occurrence of an item per date

I have this kind of data:

dat
     date shop_id
1 2013-01       1
2 2013-02       2
3 2013-02       2
4 2013-02       2
5 2013-02       1
6 2013-03       3
7 2013-04       1

shop_id stands for a specific shop and year_month stands for the date. If a shop is listed at a specific date it means that it´s open, if not it´s closed (i.e. in Janury 2013/2013-01 shop 1 was open but not shop 2 and 3, in March 2013/2013-03 shop 3 was open but not shop 1 and 2). Since the data is about sales of a specific product, a shop can occur more than once per date. I want to plot the data. It should look like the plot below: On the y-axis should be the date, on the x-axis should be the shop_id and fill should be if the shop is open (shop_id occurs together with a specific date) or not. 

  dput(dat)
    structure(list(date = structure(c(1L, 2L, 2L, 2L, 2L, 3L, 4L), .Label = c("2013-01", 
"2013-02", "2013-03", "2013-04"), class = "factor"), shop_id = c(1, 
2, 2, 2, 1, 3, 1)), class = "data.frame", row.names = c(NA, -7L
))

enter image description here

Upvotes: 0

Views: 126

Answers (1)

Paweł Chabros
Paweł Chabros

Reputation: 2399

Is this what you are looking for?

library(tidyverse)
library(lubridate)

df %>%
  group_by(shop_id) %>%
  mutate(
    date = ymd(paste0(date, "-01")),
    start = min(date),
    end = max(date) %>% ceiling_date(unit = "month") # as Julian_Hn suggested
  ) %>%
  ungroup() %>%
  ggplot(aes(x = factor(shop_id))) +
  geom_linerange(aes(
      ymin = start,
      ymax = end
    ),
    size = 40 # bar width
  )

Second proposition:

library(tidyverse)

df %>%
  group_by(date) %>%
  nest() %>%
  arrange(date) %>%
  mutate(ypos = row_number()) %>%
  unnest() %>%
  ggplot() +
  geom_rect(aes(
    xmin = shop_id - .25,
    xmax = shop_id + .25,
    ymin = ypos - .5,
    ymax = ypos + .5
  ))

Upvotes: 1

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