Create frequency distribution matrix in R (categorical variable VS numeric)

Question

I have two columns: supply situation (categorical variable) and number of students (numerical variable). I want to create a table that tells how many students are in each modality (class/levels). This is the goal (example):

I thank you in advance, PS: By helping me in this work, you will help expand innovations like Stack Over Flow in public education (this is my area of study).

Answer 1

I’m gonna create a data.frame such an example:

library(dplyr)
base <- data.frame(
  situacao = rep(c("a ser concluida", "ativa", "concluida"), length.out = 100),
  qtd_alunos = rep(c(6,7,2,3), length.out = 100)
  )

> head(base)
         situacao qtd_alunos
1 a ser concluida          6
2           ativa          7
3       concluida          2
4 a ser concluida          3
5           ativa          6
6       concluida          7

You can then aggregate the qtd_alunos by the categories of the variable situacao using:

base %>% group_by(situacao) %>% summarise(qtd_alunos = sum(qtd_alunos))

Source: local data frame [3 x 2]

         situacao qtd_alunos
1 a ser concluida        153
2           ativa        151
3       concluida        146

The command group_by indicates which variable you want to use to aggregate and the command summarise indicates how you want to aggregate/summarize the information, in case we use the sum.

If each student is a row of your database, and you do not own the column qtd_alunos, you could use the following code to create a frequency table:

base %>% group_by(situacao) %>% summarise(qtd_alunos = n())

In this specific case using the command n() I want to count the number of lines per category.

Note that to have the functions group_byand summariseyou need to have the dplyr package installed: install.packages("dplyr") and then carry it library(dplyr)