CODEWITHSUNDEEP
rggplot2
Rnchriz
Rnchriz

Reputation: 135

Starting ggplot x-axis at 0 when there is no data with 0 values

I am trying to plot the number of unique detections per day throughout the year. I had data that looked like this.

enter image description here

I summarized the number of unique detections per day using these codes

unique_day <- data %>% group_by(Day,tag) %>% filter(Date==min(Date)) %>% slice(1) %>% ungroup()

sum <- unique_day %>% group_by(Date) %>% summarise(Detections=n())

I then ended up with a dataframe like this

enter image description here

I then plot with this code

sum[year(sum$Date)==2016,] %>%
  ggplot(aes(x=Date,y=Detections))+
  theme_bw(base_size = 16,base_family = 'serif')+
  theme(panel.grid.major = element_blank(),panel.grid.minor=element_blank())+
  geom_line(size=1)+
  scale_x_datetime(date_breaks = '1 month',date_labels = "%b",
                   limits = c(as.POSIXct('2016-01-01'),as.POSIXct("2016-12-01")))+
  ggtitle('DIS 2016')+
  theme(plot.title = element_text(hjust = 0.5))+
  xlab("Date")+
  scale_y_continuous(expand = c(0,0),limits = c(0,5))

And get a plot like this enter image description here

I cant seem to get the plot to start at 0... I figure it always starts at 1 because there are no 0 values for detections... I only have a data frame summarizing the days when there was detections, not when there was not detections. I have tried using ylim, scale_y_continuous and coord_cartesian... any ideas?

Any ideas?

Upvotes: 0

Views: 837

Answers (1)

Martin Gal
Martin Gal

Reputation: 16998

Here is a simple way to get to your problem:

df_null <- data.frame(Date = seq(as.Date("2015/01/01"), by = "day", length.out = 365), 
                      Detections = 0)

For the year 2015 we create a data.frame containing all days with value 0. Suppose your data.frame looks like this:

df <- data.frame(Date = c(as.Date("2015/06/07"), as.Date("2015/06/08"), as.Date("2015/12/12")), 
                 Detections = 1:3)

Using dplyr we combine those two data.frames and summarize the values:

df %>%
  bind_rows(df_null) %>%
  group_by(Date) %>%
  summarise(Detections = sum(Detections))

Finally you can get your plot using your ggplot2-code.

Upvotes: 1

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