https://github.com/hadley/table-shapes
https://github.com/hadley/table-shapes
Last synced: about 13 hours ago
JSON representation
- Host: GitHub
- URL: https://github.com/hadley/table-shapes
- Owner: hadley
- Created: 2019-03-24T13:53:09.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2019-03-26T01:04:12.000Z (about 6 years ago)
- Last Synced: 2025-04-14T08:12:55.851Z (about 13 hours ago)
- Size: 118 KB
- Stars: 34
- Watchers: 2
- Forks: 2
- Open Issues: 2
-
Metadata Files:
- Readme: README.Rmd
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README
---
output: github_document
---
# Pivot function names
On 2019-03-22, I [tweeted about](https://twitter.com/hadleywickham/status/1109132826631421952) a [survey](https://forms.gle/vvYgBw1EwHK69gA17) to help me pick names for the [new pivot functions](https://tidyr.tidyverse.org/dev/articles/pivot.html) in the dev version of tidyr.
In the survey, I showed a picture of two tables containing the same data, and asked participants to describe their relative shapes. This document describes the results.
```{r, include=FALSE}
knitr::opts_chunk$set(comment = "#>", collapse = TRUE)
```
```{r setup, message = FALSE}
library(googlesheets)
library(tidyverse)
# This googlesheet is public if you want to do your own analysis
key <- gs_key("1Do5R1k5sEZrwU0N1KmIjKaapHDrf7eYLdIlcGNx-MsI")
results <- googlesheets::gs_read(key, col_types = list())
names(results) <- c("timestamp", "table_a", "table_b")
head(results)
nrow(results)
# Capture for posterity
write_csv(results, "results.csv")
```
## Table A -> Table B
Wider is the clear winner with ~80% of responses.
```{r}
table_a <- results %>%
filter(!is.na(table_a)) %>%
mutate(top3 = table_a %>% fct_lump(3) %>% fct_infreq() %>% fct_rev()) %>%
count(top3) %>%
mutate(prop = n / sum(n))
table_a %>%
ggplot(aes(top3, prop)) +
geom_col() +
scale_y_continuous(labels = scales::percent) +
labs(
x = NULL,
y = "Percent of responses"
) +
coord_flip()
```
There were a wide range of write in respones. The most popular included concise, compact, condense, denser.
```{r}
results %>%
mutate(
table_a = table_a %>%
str_remove("Table A is ") %>%
str_remove(" than Table B") %>%
str_trunc(50)
) %>%
count(table_a, sort = TRUE) %>%
print(n = Inf)
```
## Table B -> Table A
Longer is the clear winner with ~70% of responses. Given the number of people who suggested taller to me, I had expected it to come in much higher. Interestingly narrower is much less common than shorter, it's equivalent above.
```{r}
table_b <- results %>%
filter(!is.na(table_b)) %>%
mutate(top3 = table_b %>% fct_lump(3) %>% fct_infreq() %>% fct_rev()) %>%
count(top3) %>%
mutate(prop = n / sum(n))
table_b %>%
ggplot(aes(top3, prop)) +
geom_col() +
scale_y_continuous(labels = scales::percent) +
labs(
x = NULL,
y = "Percent of responses"
) +
coord_flip()
```
There were a wide range of write in respones. The most popular included expanded and skinnier.
```{r}
results %>%
mutate(
table_b = table_b %>%
str_remove("Table B is ") %>%
str_remove(" than Table A") %>%
str_trunc(50)
) %>%
count(table_b, sort = TRUE) %>%
print(n = Inf)
```
## Conclusion
The new functions will be called `pivot_wider()` and `pivot_longer()`: these are not the most natural names for everyone, but they are are the most popular by a large margin. I like pivot because it suggests the form of the underlying operation (a pivoting or rotation), and it is evocative to excel users.
A few alternatives that were suggested, considered, and rejected:
* `VERB_long()`/`VERB_wide()`: not obvious whether they take long/wide
data or return long/wide data.
* `VERB_to_long()`/`VERB_to_wider()`: implies that long and wide are absolute
terms. I don't think it makes sense to talk about long or wide form data;
you can only say one form is longer or wider than another form.
* `to_long()`/`to_wide()`: isn't a verb, and implies that there's only one
operation that makes data longer/wider. The next version of tidyr will also
contain functions that unnest list-columns of vectors, and that verb (name
TBA) also needs directional suffixes.
* `reshape_SHAPE`: too much potential for confusion with the existing
`base::resahpe()`
* `gather()`/`spread()`: while some people clearly liked these functions they
were not memorable to a large number of people I talked to.
I appreciate the enthusiasm that people have for naming functions!