---
title: "Example 3: Reshape"
output: rmarkdown::html_vignette
vignette: >
%\VignetteIndexEntry{Example 3: Reshape}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
```
When I design `longer_dt` and `wider_dt`, I could find the `pivot_longer` and `pivot_wider` in `tidyr` and `melt` and `dcast` in `data.table`. Still, designing this API is not easy, as my goal is to let users use it with least pain. Here we would try to reproduce the results in the vignette of `tidyr`(<https://tidyr.tidyverse.org/articles/pivot.html>). First load the packages:
```{r setup}
library(tidyfst)
library(tidyr)
```
## Longer
First inspect the data:
```{r}
relig_income
```
In `tidyr`, to get the longer format you need:
```{r,eval=FALSE}
relig_income %>%
pivot_longer(-religion, names_to = "income", values_to = "count")
```
In `tidyfst`, we have:
```{r,warning=FALSE}
relig_income %>%
longer_dt("religion",name = "income",value = "count")
```
Another example from `tidyr`:
```{r,eval=FALSE}
billboard
# tidyr way:
billboard %>%
pivot_longer(
cols = starts_with("wk"),
names_to = "week",
values_to = "rank",
values_drop_na = TRUE
)
# tidyfst way:
billboard %>%
longer_dt(-"wk",
name = "week",
value = "rank",
na.rm = TRUE
)
# regex could select the groups to keep, and minus could select the reverse
```
A warning would could come out because the merging column has different data types and do the coercion automatically.
## Wider
```{r}
## data
fish_encounters
## tidyr way:
fish_encounters %>%
pivot_wider(names_from = station, values_from = seen)
## tidyfst way:
fish_encounters %>%
wider_dt(name = "station",value = "seen")
# if no keeped groups are selected, use all except for name and value columns
```
If you want to fill with 0s, use:
```{r}
fish_encounters %>%
wider_dt(name = "station",value = "seen",fill = 0)
```
Note that the parameter of `name` and `value` should always be provided and should be explicit called (with the parameter names attached).
## More complicated example
This example comes from data.table (<https://rdatatable.gitlab.io/data.table/articles/datatable-reshape.html>), and has been used in tidyr too. We'll try to do it in tidyfst in this example.
If we have a data.frame as below:
```{r}
family <- fread("family_id age_mother dob_child1 dob_child2 dob_child3 gender_child1 gender_child2 gender_child3
1 30 1998-11-26 2000-01-29 NA 1 2 NA
2 27 1996-06-22 NA NA 2 NA NA
3 26 2002-07-11 2004-04-05 2007-09-02 2 2 1
4 32 2004-10-10 2009-08-27 2012-07-21 1 1 1
5 29 2000-12-05 2005-02-28 NA 2 1 NA")
family
```
And want to reshape the data.table to be like this:
```{r}
# family_id age_mother child dob gender
# <int> <int> <char> <char> <char>
# 1: 1 30 child1 1998-11-26 1
# 2: 1 30 child2 2000-01-29 2
# 3: 1 30 child3 <NA> <NA>
# 4: 2 27 child1 1996-06-22 2
# 5: 2 27 child2 <NA> <NA>
# 6: 2 27 child3 <NA> <NA>
# 7: 3 26 child1 2002-07-11 2
# 8: 3 26 child2 2004-04-05 2
# 9: 3 26 child3 2007-09-02 1
# 10: 4 32 child1 2004-10-10 1
# 11: 4 32 child2 2009-08-27 1
# 12: 4 32 child3 2012-07-21 1
# 13: 5 29 child1 2000-12-05 2
# 14: 5 29 child2 2005-02-28 1
# 15: 5 29 child3 <NA> <NA>
```
The `data.table::dcast` and `tidyr::pivot_longer` could transfer it in one step, however, not so easy to understand. Here we'll do it step by step to see what actually happens in this transfer.
```{r,warning=FALSE}
family %>%
longer_dt(1:2) %>%
separate_dt("name",into = c("class","child")) %>%
wider_dt(-"class|value",
name = "class",
value = "value")
```
In such a process, we could find that we actually get a longer table, then separate it, and wider it later. *tidyfst* is not going to support the complicated transfer in one step, because it might be easier to implement, but much harder to understand 3 procedures in 1 step. If you still prefer that way, use `data.table::dcast` and `tidyr::pivot_longer` instead.