R - How to Make Barplot Plot Zeros for Missing Values Over the Data Range

R - how to make barplot plot zeros for missing values over the data range?

Try

barplot(table(factor(mysample, levels=1:10)));

By using a factor, R will know which levels are "missing"

R: barplot {base} complete missing integer values on x axis

We can merge with a full dataset, replace the NA elements to 0 and then do the barplot

df1 <- merge(data.frame(year = min(df$year):max(df$year)), df, all.x=TRUE)
df1$area[is.na(df1$area)] <- 0
barplot(setNames(df1$area, df1$year))

-output

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This can also be done with tidyverse

library(tidyverse)
df %>%
   complete(year = min(year):max(year), fill = list(area = 0)) %>% 
   ggplot(., aes(year, area)) + 
   geom_bar(stat = 'identity') +
   theme_bw()

-output

How to force plotly R to plot missing values with category axis

There is info in reference: https://plotly.com/r/reference/layout/xaxis/#layout-xaxis-range, but not so obvious.

But first of all: categorical variable needs to be factor.

Second you need to specify range from 0 to number of levels -1. To better looking use +-0.5 on ends

dt_plot <- data.frame(categories = letters[1:10], values = c(rep(NA_integer_, 3), 1:5, rep(NA_integer_, 2)))
dt_plot$categories <- as.factor(dt_plot$categories)
plot_ly(data = dt_plot) %>%
  add_bars(x = ~categories, y = ~values)%>% 
  layout(xaxis = list(range = list(-0.5, 9.5)))

Forcing a category with a frequency of zero to a bar chart

Providing a factor to the table function fixes this. And you'll also need to adjust name.arg.

sick = c(0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,2,2,2,2,2,3,3,3,3,4,4,4,4,4,5,5,5,5,5,5,5,5,7,7,7,7,7,8,8,9)
ft = data.frame(table(sick))
colnames(ft) = c('Value','Freq')
ft$Perc = round(ft$Freq / sum(ft$Freq) * 100,1)
counts = table(factor(sick,levels = c(0:9)))
bp = barplot(counts, main="Sick Leave Distribution", ylab = "Frequency", xlab = "Days of Sick Leave Taken" , ylim = c(0,10), cex.names = 1, col = "blue", names.arg=gsub("\\s","\n", c(0:9)))
text(x=bp, y=counts, labels=round(counts,0), pos=3, xpd=NA)

Missing a grouping variable when creating multiple barplots with ggplot2

If you want to create a facetted ggplot2 graph, you'll need to have a single variable in your data.frame by which you facet or break up the data. Let's start with some example data based on your question:

CategoryLevels <- c("none", "suspected", "light", "medium", "severe")

myData <- data.frame(SubjectID = LETTERS[1:10], 
                     Gender = sample(c("M", "F", "divers"), 10, replace = TRUE),
                     DepressionSymptoms = 
                           factor(sample(CategoryLevels, 10, replace = TRUE), 
                                  levels = CategoryLevels),
                     FearSymptoms = 
                           factor(sample(CategoryLevels, 10, replace = TRUE), 
                                  levels = CategoryLevels),
                     SomaticSymptoms =
                           factor(sample(CategoryLevels, 10, replace = TRUE), 
                                  levels = CategoryLevels))

I'm guessing your data structure looks something like this. As @Greg was saying, you'll need to convert your data from the wide format (each column is a symptom) to a longer format (one column listing the symptom and another column listing the subject's response). To do that, you'll need a subject ID to link everything so that you make sure you know whose answers were whose.

myData <- myData %>% 
      pivot_longer(names_to = "Symptom", values_to = "Response", 
                   cols = matches("Symptom"))

Now that you've got your data in a long format, you can facet on the "Symptom" column and fill the bar colors by the subjects' genders.

ggplot(myData, aes(x = Response, fill = Gender)) +
      geom_bar(stat = "count") +
      facet_wrap(~ Symptom)

add extra labels to x axis barplot

You need to make it a factor and declare the levels:

counts <- table(factor(mtcars$gear,levels=2:6))
barplot(counts, main="Car Distribution",
xlab="Number of Gears")

To add an explanation, factors are something meant for categorical variables. There's two aspect achieved by setting the levels as above. One you can detail what levels to expect, including missing. This is useful when say you subset and table etc. Second, you order the categories or factors. You can see it is plotted from 2 to 6. You can try doing this:

counts <- table(factor(mtcars$gear,levels=6:2))
barplot(counts, main="Car Distribution",
xlab="Number of Gears")

The plot will reverse now. You can also see this R chapter on factors

How to remove 0 values from labels in a histogram plot

You can create an ifelse to the labels of your bars in the text command. You can use the following code:

h <- hist(ChiSumxE17$sumlength, breaks = 10, xlim = c(0,100), ylim = c(0,32), xlab = "Length (mm)", main = "")
text(h$mids, h$counts + 1, ifelse(h$counts == 0, "", h$counts))

Output:

As you can see from the plot, the labels of the bars with 0 frequency are removed.

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