| rstudiosurvey {rimu} | R Documentation |
Subset of RStudio 2019 Community Survey
Description
The 'rstudiosurvey' data set contains 1838 rows of responses from the 2019 RStudio Community Survey, where columns are the 51 questions and a column for the timestamp. The variable names are the full questions. Multiple responses are separated by a comma and space. Non-ASCII characters have been converted with the "ASCII//TRANSLIT" option of iconv.
Usage
data("rstudiosurvey")Format
A data frame with 1838 observations on the following 52 variables.
Timestampa character vector
- ‘How would you rate your level of experience using R?’
a character vector
- ‘Compared with other technical topics you've learned in school and on the job, on a scale of 1 to 5, how difficult do you expect learning R to be?’
a numeric vector
- ‘From what you know about R, how long do you expect that it will take for you to learn enough to use R productively?’
a character vector
- ‘How do you think you would go about the process of learning R?’
a character vector
- ‘Which statement most closely reflects the primary reason why you are interested in learning R?’
a character vector
- ‘If you were to learn R, what would do you think you would use it for? (check all that apply)’
a character vector
- ‘Which analytical tools do you use today for the functions that you might learn R for? (please check all that apply)’
a character vector
- ‘What do you think is the biggest obstacle you must overcome in trying to learn R? The choices below are only suggestions; if we haven't listed your obstacle, please choose "Other" and add your obstacle in the text. ’
a character vector
- ‘What year did you first start learning R?’
a numeric vector
- ‘How did you learn R? If you used multiple methods, please select the one you used the most.’
a character vector
- ‘Compared with other technical topics you've learned in school and on the job, on a scale of 1 to 5, how difficult has it been for you to learn R?’
a numeric vector
- ‘Roughly how long did it take you to achieve proficiency in R?’
a character vector
- ‘Which statement most closely reflects the primary reason why you learned R?’
a character vector
- ‘What do you think was the biggest obstacle you had to overcome in learning R? The choices below are only suggestions; if we haven't listed your obstacle, please choose "Other" and add your obstacle in the text. ’
a character vector
- ‘How often do you use R today, either for professional or personal projects?’
a character vector
- ‘What applications do you use R for most? (check all that apply)’
a character vector
- ‘Please rate how much you enjoy using R on a scale of 1 to 5, where 1 is you don't enjoy it at all, and 5 is that you enjoy it a great deal.’
a numeric vector
- ‘How likely are you to recommend R to a colleague, friend, or family member?’
a numeric vector
- ‘Which tools do you use with your R applications? (please check all that apply)’
a character vector
- ‘Did you use tidyverse packages such as ggplot2 or dplyr to learn R?’
a character vector
- ‘Do you use tidyverse packages when you use R now?’
a character vector
- ‘What do you like best about using R?’
a character vector
- ‘What do you like least about using R?’
a character vector
- ‘When you have problems in R, where do you go for help?’
a character vector
- ‘How do you discover new packages or packages that are unfamiliar to you?’
a character vector
- ‘How do you share the results that you create in R? Check all that apply.’
a character vector
- ‘Looking ahead, how do you expect your use of R to change in 2020?’
a character vector
- ‘To help us ensure that you are not a robot, please enter the number of characters in the word "analysis" in the text box below. Please type your answer as a word; for example if you want 3 to be your answer, type "three".’
a character vector
- ‘Do you currently use R Markdown? Choose the statement that most closely matches your use.’
a character vector
- ‘What applications do you use R Markdown for? Check all that apply.’
a character vector
- ‘Looking forward, how do you expect your use of R Markdown to change in 2020?’
a character vector
- ‘How often do you currently use Shiny? Choose the statement that most closely matches your use.’
a character vector
- ‘Looking forward, how do you expect your use of Shiny to change in 2020?’
a character vector
- ‘Do you currently use Python? Choose the statement that most closely matches your use.’
a character vector
- ‘What applications do you use Python for most? (check all that apply)’
a character vector
- ‘Please rate how much you enjoy using Python on a scale of 1 to 5, where 1 is you don't enjoy it at all, and 5 is that you enjoy it a great deal.’
a numeric vector
- ‘How likely are you to recommend Python to a colleague, friend, or family member?’
a numeric vector
- ‘Looking forward, how do you expect your use of Python to change in 2020?’
a character vector
- ‘What computer tools and/or languages have you used besides R?’
a character vector
- ‘What was the FIRST computer language or tool that you learned?’
a character vector
- ‘What year were you born?’
a numeric vector
- ‘What gender do you identify with?’
a character vector
- ‘I identify my ethnicity as (select all that apply):’
a character vector
- ‘What is the highest degree or level of school you have completed? If currently enrolled, please use the highest degree received.’
a character vector
- ‘In what country do you currently reside?’
a character vector
- ‘What industry do you work or participate in?’
a character vector
- ‘What is your job title, if any?’
a character vector
- ‘Which category best describes the work you do?’
a character vector
- ‘How many people in your organization or work group do you feel that you can ask for help or support when working with R?’
a numeric vector
- ‘Which of the following events have you attended, if any? Check all that apply.’
a character vector
- ‘How did you hear about this survey?’
a character vector
Source
https://github.com/rstudio/r-community-survey/tree/master/2019
Examples
data(rstudiosurvey)
names(rstudiosurvey)[40]
## Other software being used
other_software<- as.mr(rstudiosurvey[[40]])
mtable(other_software)
## top 20 responses
common<-mr_lump(other_software, n=20)
mtable(common)
## 'None' isn't really another package
common<-mr_drop(common, "None")
mtable(common)
## UpSet plot
plot(common)
## Excel users filled in the survey later
timestamp<-as.Date(rstudiosurvey[[1]],format="%m/%d/%y")
boxplot(timestamp~I(common %has% "Excel"))
## names in order of popularity
t<-mtable(common)
popular<-colnames(t)[order(t,decreasing=TRUE)]
## most popular package for each user
cuml_users <- mr_flatten(common, popular, sort=TRUE)
class(cuml_users)
table(cuml_users)
## two-way tables
## people who also use Stata or Julia are less happy with R than those who don't
names(rstudiosurvey)[18]
happy<-factor(rstudiosurvey[[18]])
mtable(happy, common)
round(prop.table(mtable(happy,common),2),2)
## mr objects can be dataframe columns, or expanded to individual levels
df<-data.frame(timestamp, happy, common)
dim(df)
head(df)
df_raw<-data.frame(timestamp, happy, as.matrix(common))
dim(df_raw)
head(df_raw)
[Package rimu version 0.6 Index]