How can I do count_if in R

[william01]

Dear,

I do a calculation and visualize data in Excel with count_if function, but I don't find a way to do this in R.
I have a table 1 with the answers, I want to count the total answers and group by category of answer like a table 2, finally make data visualization. All the process like this photos.
Please help find a way to do this in R, thank you

I try to reproducible example, but I don't what is the next steps after create a data frame.

df <- data.frame (
X1 = c ("Yes", "Yes", "No", "Other"),
X2 = c ("Yes", "No", "No", "Other"),
X3 =c ("Other", "No", "No", "Other")
)

[andresrcs]

Hi!

To help us help you, could you please prepare a reproducible example (reprex) illustrating your issue? Please have a look at this guide, to see how to create one:

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

[william01]

Thank you

I will try to edit my post

[startz]

It's not quite clear what you want to count. If it's the answers in column X1 you could do

library(tidyverse)
df %>% group_by(X1) %>% summarise(count = n())

group_by) makes a group for each unique value in X1. summarise() then computes a statistic for each group.

[william01]

Dear,

Thank you for your help, I want to count all the answers of all the column and group to new table, like an example I do in Excel, it is not hard to do in Excel when I use count_if and select the ranges and criteria, but I don't know how to write a code in R.

[andresrcs]

This is a way to do it

library(dplyr)
library(tidyr)
library(ggplot2)

df <- data.frame (
    X1 = c ("Yes", "Yes", "No", "Other"),
    X2 = c ("Yes", "No", "No", "Other"),
    X3 =c ("Other", "No", "No", "Other")
)

(table_2 <- df %>% 
    pivot_longer(cols = everything(),
                 names_to = "column",
                 values_to = "answer") %>% 
    count(answer, name = "count"))
#> # A tibble: 3 × 2
#>   answer count
#>   <chr>  <int>
#> 1 No         5
#> 2 Other      4
#> 3 Yes        3

table_2 %>% 
    ggplot(aes (x = "", y = count, fill = answer)) + 
    geom_col(position = 'stack', width = 1) +
    geom_text(aes(label = paste(round(count / sum(count) * 100, 1), "%"), x = 1.3),
              position = position_stack(vjust = 0.5)) +
    theme_classic() +
    theme(plot.title = element_text(hjust=0.5),
          axis.line = element_blank(),
          axis.text = element_blank(),
          axis.ticks = element_blank()) +
    labs(fill = NULL,
         x = NULL,
         y = NULL,
         title = "Pie Chart") + 
    coord_polar("y")

^{Created on 2022-08-31 with reprex v2.0.2}

[william01]

Dear
Yeah, I got it, thank you so much.

[jcolomb]

I would use this :

df |> 
  tidyr::gather() |> # pool all columns into one
  dplyr::count(value, name = "count") # count values in this one column, same as previous answer.

PS: there is no direct way to do this because the spreadsheet design is actually not perfect. You usually do not need to count cell over different columns, as different columns should indicate different kind of information. The function gather()indeed clean your data first (telling all columns are actually the same kind of data and should be merged) and then it is easy to count (or do other calculations).

[Bernie_Ha]

Apart from the solutions already given, a very basic and simple approach would be to use

> my.df <- data.frame(X1 = c ("Yes", "Yes", "No", "Other"),
                      X2 = c ("Yes", "No", "No", "Other"),
                      X3 =c ("Other", "No", "No", "Other"))
> table(unlist(my.df))

   No Other   Yes 
    5     4     3