Why is R showing equal values for different entries rather than counting actual frequencies (excludi-CodePudding

I have been learning R recently. While executing the following codes, I found the following results:

Code:

data<-read.csv("pen.csv",header=TRUE)
head(data)
require(reshape2)
dat<-melt(data=data)
names(dat)<-c("species","weight")
summary(dat)

Result:

> summary(dat)

|      species     |  weight         |  
|------------------|-----------------|  
| Adelie   :6      | Min.   :181.0   |
| Gentoo   :6      | 1st Qu.:193.0   |
| Chinstrap:6      | Median :202.0   |
|                  | Mean   :202.3   |  
|                  | 3rd Qu.:215.0   | 
|                  | Max.   :216.0   |
|                  | NA's   :3       |

I was expecting the result like this:

|      species     |  weight         |  
|------------------|-----------------|  
| Adelie   :5      | Min.   :181.0   |
| Gentoo   :6      | 1st Qu.:193.0   |
|Chinstrap :4      | Median :202.0   |
|                  | Mean   :202.3   |  
|                  | 3rd Qu.:215.0   | 
|                  | Max.   :216.0   |
|                  | NA's   :3       |

I even tried considering species as a factor (dat$species<-as.factor(dat$species)).Got the same result. Could anyone help? (Here, I have attached the data set)

Adelie	Gentoo	Chinstrap
181	215	202
186	215	193
195	215	210
NA	216	198
193	215	NA
190	210	NA

CodePudding user response：

You just have some NA values in the original table, so the counts are a bit off. melt does not default to removing them, unless you set na.rm = TRUE:

read_table("Adelie  Gentoo  Chinstrap
181 215 202
186 215 193
195 215 210
NA  216 198
193 215 NA
190 210 NA") %>%
  melt(na.rm = TRUE) %>%
  setNames(c("species","weight")) %>%
  summary()

 #      species      weight     
 # Adelie   :5   Min.   :181.0  
 # Gentoo   :6   1st Qu.:193.0  
 # Chinstrap:4   Median :202.0  
 #               Mean   :202.3  
 #               3rd Qu.:215.0  
 #               Max.   :216.0