trying to understand why the last line of a script won't produce any output

General
1

Trying to run a script on R Studio:

library(readr)
library(dplyr)
library(ggplot2)
rm(list = ls())
compensation <- read_csv("C:/Users/Rupert/Documents/MyFirstAnalysis/datasets/compensation.csv")
glimpse(compensation)
summary(compensation)

Final line of script seems not to be generating output.

Actual output generated from script is:

Attaching package: 'dplyr'

The following objects are masked from 'package:stats':

filter, lag

The following objects are masked from 'package:base':

intersect, setdiff, setequal, union

Parsed with column specification:
cols(
Root = col_double(),
Fruit = col_double(),
Grazing = col_character()
)
Rows: 40
Columns: 3
Root <dbl> 6.225, 6.487, 4.919, 5.130, 5.417, 5.359, 7.614, 6.352, 4.9... Fruit 59.77, 60.98, 14.73, 19.28, 34.25, 35.53, 87.73, 63.21, 24....
$ Grazing "Ungrazed", "Ungrazed", "Ungrazed", "Ungrazed", "Ungrazed",...

Seems as though second last line of script is producing output but not last line. Why would that be, does anyone know?

2

Hi,

Welcome to the RStudio community!

It seems strange that glimpse would work, but summary not. Could you give us a reprex of this issue? A reprex consists of the minimal code and data needed to recreate the issue/question you're having. (we have the code, but no data) You can find instructions how to build and share one here:

Thanks,
PJ

3

Thanks Pieter,

I did a reprex on a small version of the dataset and then the problem is solved, the code runs as is expected, but then when I go back to running the script on the file called "compensation.csv", the problem comes back, when I run the script and look in the "Jobs" frame I see only the output of the glimpse() line but not the summary() line. So I guess I need to work out how to construct a reprex for you that will actually reproduce the problem. It's a relatively small dataset; it is maybe worth my while to try to construct a reprex from the entire dataset to see if that reproduces the issue?

4

Hi,

Try and create a reprex indeed. If the data is too large for the reprex, consider uploading it to a repository like GitHub, DropBox etc and share a link for download. You can only do this if your data is not private or sensitive of course! If you can't you'll have to try and generate a random dataset the same shape and size of your original data. Using functions like sample() and runiform() can help with that. Maybe then you can recreate the problem.

PJ

5

The data file I was using is called "compensation.csv", to get it go here

download the zip file, and then while reading the zip file open the folder called "datasets-master", then get the file called compensation.csv from there.

With that together with the code in my first post, does that allow you to re-create the problem for yourself?

6

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