How to Plot Histogram/ Frequency-Count of a Vector with Ggplot

How to plot histogram/ frequency-count of a vector with ggplot?

Please look at the help page ?geom_histogram. From the first example you may find that this works.

qplot(as.factor(dice_results), geom="histogram")

Also look at ?ggplot. You will find that the data has to be a data.frame

Plotting a histogram with ggplot with only x values and frequency count, instead of usual frequency vector

You can use stat="identity" with geom_bar.

e.g.

testdt <- data.frame(x = c(1,2,3,4,5,6), count = c(10, 20, 10, 5, 15, 25))
ggplot(data = testdt) + geom_bar(aes(x = x, y = count), stat = "identity")

how to generate histogram/ frequency count in ggplot: weird behavior

This is not a weird behaviour: ggplot2 simply operates on data.frame objects - and not vectors:

ggplot(data.frame(x=c(1,2,3,3,4,5)), aes(x=x)) + geom_histogram()

plot histogram of frequency of values occurring in a column based on list of values from another file

You can easily calculate the frequency of V2 (in l2) with the function count() from the library dplyr.

library(dplyr)
count(l2, V2)

#   V2        n
# 1 A1        2
# 2 C         1
# 3 D         1
# 4 E1        2

Then, transform l1 to a dataframe, and merge it with the result of the count in order to keep all the levels in l1:

l1 <- c("A1", "A2", "B-1", "C", "D", "E1")
left_join(data.frame(V2 = l1), count(l2, V2), by = 'V2') 

#    V2  n
# 1  A1  2
# 2  A2 NA
# 3 B-1 NA
# 4   C  1
# 5   D  1
# 6  E1  2

Then you can divide by number of observations (6 in this case) to calculate the proportion, and you can build an histogram (with ggplot2 for instance, or with barplot() if your prefer).

library(ggplot2)
left_join(data.frame(V2 = l1), count(l2, V2), by = 'V2') %>% 
   ggplot(aes(x = V2, y = n)) + 
   geom_col()

Multiple Relative frequency histogram in R, ggplot

Below are some basic example with the build-in iris dataset. The relative part is obtained by multiplying the density with the binwidth.

library(ggplot2)

ggplot(iris, aes(Sepal.Length, fill = Species)) +
  geom_histogram(aes(y = after_stat(density * width)),
                 position = "identity", alpha = 0.5)
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

ggplot(iris, aes(Sepal.Length)) +
  geom_histogram(aes(y = after_stat(density * width))) +
  facet_wrap(~ Species)
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

^{Created on 2022-03-07 by the reprex package (v2.0.1)}

Plot a histogram for a frequency table in R- ggplot2

First make your data from wide to longer using pivot_longer. After that you can create a stacked barplot like this:

library(ggplot2)
library(dplyr)
library(tidyr)
df_1 %>%
  pivot_longer(-ref) %>%
  ggplot(aes(x = ref, y =value, fill = name)) +
  geom_bar(stat = "identity", position = "stack")

Output:

One Vector to DataFrame for use in ggplot histogram in R

library(ggplot2)

prime <- c(2,3,5,7,11,13,17,19,23,29,31,37,41,43,47,53,59,61,67,71,73,79,83,89,97)

data <- as.data.frame(prime)

main <-"Frequency of Prime Numbers"

ggplot(data, aes(x=prime)) +  geom_histogram(binwidth = 1) + ggtitle(main)

Make Frequency Histogram for Factor Variables

It seems like you want barplot(prop.table(table(animals))):

However, this is not a histogram.

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