How to remove white spaces between stacked geom_col

Question

library(tidyverse)
library(lubridate)

date <- seq(ymd('2018-08-01'), ymd('2018-08-31'), by = '1 day')
c <- 21.30
x1 <- runif(length(date), 0, 20)
x2 <- rnorm(length(date), 10, 3)
x3 <- abs(rnorm(length(date), 40, 10))
data <- data.frame(c, x1, x2, x3) %>% 
  t() %>% as.data.frame() %>% rownames_to_column('var')
data <- data %>%
  mutate(category1 = c('catA', 'catB', 'catB', 'catC') %>% as.factor(),
         category2 = c('catAA', 'catBA', 'catBB', 'catCA') %>% as.factor())
names(data) <- c('var', as.character(date), 'category1', 'category2')
data_long <- data %>% 
  gather(date, value, -var, -category1, -category2) %>% 
  mutate(date = ymd(date))

data_long %>%
  ggplot(aes(date, value, fill = category1)) +
  geom_col(position = 'stack') +
  scale_x_date(breaks = '1 week', date_labels = '%Y-%m-%d', expand = c(.01, .01)) +
  theme_minimal() +
  theme(axis.text.x = element_text(angle = 90, vjust = .4)) +
  labs(fill = '')

With the example data and code above I generate the following plot:

What I need to do is to remove white spaces between columns. I have found some similar topics, but they recommended use of position_dodge() while it can't be used in my case as I already have position = 'stack', which can't be replaced. How can I make the columns adjacent to each other then?

Edit

Setting width = 1, as proposed by @camille, seems to work ok with the raw data, but not with aggregated to weeks or months - please see the code below:

data_long %>%
  mutate(date = floor_date(date, unit = 'week', week_start = 1)) %>% 
  group_by(category1, date) %>% 
  summarise(value = sum(value, na.rm = TRUE)) %>% 
  ungroup() %>% 
  ggplot(aes(date, value, fill = category1, width = 1)) +
  geom_col(position = 'stack') +
  scale_x_date(breaks = '1 month', date_labels = '%Y-%m', expand = c(.01, .01)) +
  theme_minimal() +
  theme(axis.text.x = element_text(angle = 90, vjust = .4)) +
  labs(fill = '')

Edit 2.

As pointed out by @Camille, width of 1 may refer to 1 day in case of date scale. However, the following doesn't produce expected output and returns warning message: position_stack requires non-overlapping x intervals

 data_long %>%
    mutate(date = floor_date(date, unit = 'month', week_start = 1)) %>% 
    group_by(category1, date) %>% 
    summarise(value = sum(value, na.rm = TRUE),
              n = n()) %>% 
    ungroup() %>% 
    ggplot(aes(date, value, fill = category1, width = n)) +
    geom_col(position = 'stack') +
    scale_x_date(breaks = '1 month', date_labels = '%Y-%m', expand = c(.01, .01)) +
    theme_minimal() +
    theme(axis.text.x = element_text(angle = 90, vjust = .4)) +
    labs(fill = '')

Answer 1

The docs for geom_col are more specific than what I put in my comment above. The more detailed meaning of the width parameter:

Bar width. By default, set to 90% of the resolution of the data.

In a general case, such as your first one, this probably just means the distance between one discrete case and another. But in the case of dates, which have a real resolution, this seems to refer to days. I'm not sure if there's a different way to set the resolution of the dates, such as for one unit to refer to one week, instead of one day.

I'm decreasing the alpha just to be able to see if bars overlap.

So without setting a width, this defaults to 90% of the distance between observations, i.e. 90% of one week.

library(tidyverse)
library(lubridate)
...

summarized <- data_long %>%
  mutate(date = floor_date(date, unit = 'week', week_start = 1)) %>% 
  group_by(category1, date) %>% 
  summarise(value = sum(value, na.rm = TRUE)) %>% 
  ungroup()

ggplot(summarized, aes(date, value, fill = category1)) +
  geom_col(alpha = 0.6) +
  scale_x_date(breaks = '1 week', expand = c(.01, .01))

Setting width to 1 means the width is 1 day. I feel like there's a discrepancy here that someone else might be able to explain, why this is read as 1 day rather than 100% of the resolution.

ggplot(summarized, aes(date, value, fill = category1)) +
  geom_col(alpha = 0.6, width = 1) +
  scale_x_date(breaks = '1 week', expand = c(.01, .01))

So to get a width of 1 week, aka 7 days, set width to 7. Again, I think there's a bit of explanation someone else could fill in here.

ggplot(summarized, aes(date, value, fill = category1)) +
  geom_col(alpha = 0.6, width = 7) +
  scale_x_date(breaks = '1 week', expand = c(.01, .01))

Edit: Based on the link in my comment, the best way might just be converting the dates to strings so you can just plot on a discrete x-scale as normal. Before you call as.character, you could do whatever formatting you might want.

summarized %>%
  mutate(date = as.character(date)) %>%
  ggplot(aes(x = date, y = value, fill = category1)) +
    geom_col(width = 1)