plotting method testing & doc

Author: marcboschmatas

DESCRIPTION

@@ -9,15 +9,18 @@ License: GPL (>= 3)
 BugReports: https://github.com/marcboschmatas/partialling.out/issues
 Suggests: 
     tinytest,
-    tinyplot,
+    tinysnapshot,
     knitr,
     rmarkdown,
     palmerpenguins,
     tinytable,
     fwlplot,
     tsibble,
     units,
-    purrr
+    purrr,
+    fontquiver,
+    rsvg,
+    svglite
 Config/testthat/edition: 3
 Encoding: UTF-8
 Roxygen:list (markdown = TRUE, roclets = c ("namespace", "rd", "srr::srr_stats_roclet"))
@@ -29,5 +32,6 @@ Imports:
     rlang,
     fixest,
     lfe,
-    stats
+    stats,
+    tinyplot
 URL: https://marcboschmatas.github.io/partialling.out/

NAMESPACE

@@ -4,14 +4,18 @@ S3method(partialling_out,felm)
 S3method(partialling_out,fixest)
 S3method(partialling_out,lm)
 export(partialling_out)
+export(plot_partial_residuals)
 import(rlang)
 importFrom(fixest,feols)
 importFrom(glue,glue)
 importFrom(lfe,felm)
 importFrom(lifecycle,deprecated)
+importFrom(stats,aggregate)
 importFrom(stats,as.formula)
 importFrom(stats,coef)
 importFrom(stats,formula)
 importFrom(stats,lm)
 importFrom(stats,resid)
 importFrom(stats,terms)
+importFrom(tinyplot,plt)
+importFrom(tinyplot,plt_add)

R/partialling_out.R

@@ -197,9 +197,9 @@ partialling_out.lm <- function(
     colnames(resdf)[3] <- "weights"
   }
 
-  # give partial_residual class to resdf to make plot method
+  # give partial_residuals class to resdf to make plot method
 
-  resdf <- structure(resdf, class = c("partial_residual", "data.frame"))
+  resdf <- structure(resdf, class = c("partial_residuals", "data.frame"))
 
   return(resdf)
 }
@@ -330,8 +330,8 @@ partialling_out.fixest <- function(
     resdf <- cbind(resdf, weights)
     colnames(resdf)[3] <- "weights"
   }
-  # give partial_residual class to resdf to make plot method
-  resdf <- structure(resdf, class = c("partial_residual", "data.frame"))
+  # give partial_residuals class to resdf to make plot method
+  resdf <- structure(resdf, class = c("partial_residuals", "data.frame"))
 
   return(resdf)
 }
@@ -466,9 +466,9 @@ partialling_out.felm <- function(
     colnames(resdf)[3] <- "weights"
   }
 
-  # give partial_residual class to resdf to make plot method
+  # give partial_residuals class to resdf to make plot method
 
-  resdf <- structure(resdf, class = c("partial_residual", "data.frame"))
+  resdf <- structure(resdf, class = c("partial_residuals", "data.frame"))
 
   return(resdf)
 }

R/plot_partial_residuals.R

@@ -0,0 +1,65 @@
+#' Function for plotting partial residuals
+#' Uses `tinyplot` as backend
+
+# nolint start
+#' @title plot_partial_residuals: scatterplot of partial residuals
+#' @param x a partial_residuals objects from `partialling_out()`
+#' @param add_lm if TRUE, a `lm` will be plotted
+#' @param quantile if TRUE, will plot only the mean values of the quantiles of the mean explanatory variable specified by `probs`
+#' @param probs numeric vector of length one that specifies the number of quantiles to be computed if `quantile` is TRUE.
+#' by default, 0.02, which will give 50 quantiles.
+#' @param ... Any other `tinyplot::plt()` params
+#' @returns invisibly, x
+#' @importFrom tinyplot plt
+#' @importFrom tinyplot plt_add
+#' @importFrom stats aggregate
+#' @examples
+#' \donttest{library(palmerpenguins)
+#' library(fixest)
+#' model <- feols(bill_length_mm ~ bill_depth_mm | species + island,
+#'                data = penguins)
+#' partial_df <- partialling_out(model, penguins, both = TRUE)
+#' plot_partial_residuals(partial_df)
+#' }
+#' @export
+# nolint end
+plot_partial_residuals <- function(
+  x,
+  add_lm = TRUE,
+  quantile = FALSE,
+  probs = .02,
+  ...
+) {
+  fml <- as.formula(paste(colnames(x)[1], "~", colnames(x)[2]))
+  if (!quantile) {
+    tinyplot::plt(fml, data = x, type = "p")
+  } else {
+    x$qnt <- cut(
+      x[[2]],
+      breaks = quantile(x[[2]], probs = seq(0, 1, probs)),
+      include.lowest = TRUE
+    )
+
+    fml_agg <- as.formula(paste0(
+      "cbind(",
+      colnames(x)[1],
+      ", ",
+      colnames(x)[2],
+      ")",
+      " ~ ",
+      "qnt"
+    ))
+
+    res_qnt <- aggregate(
+      fml_agg,
+      data = x,
+      FUN = mean
+    )
+    tinyplot::plt(fml, data = res_qnt, type = "p")
+  }
+
+  if (add_lm) {
+    tinyplot::plt_add(fml, data = x, type = "lm")
+  }
+  invisible(x)
+}

README.Rmd

@@ -72,7 +72,6 @@ The workflow for `partialling.out` is rather simple: first, create a linear or f
 ```{r}
 library(partialling.out)
 library(tinytable)
-library(tinyplot)
 library(palmerpenguins)
 
 model <- lm(bill_length_mm ~ bill_depth_mm + species, data = penguins)

README.md

@@ -89,7 +89,6 @@ linear or fixed effects model.
 ``` r
 library(partialling.out)
 library(tinytable)
-library(tinyplot)
 library(palmerpenguins)
 
 model <- lm(bill_length_mm ~ bill_depth_mm + species, data = penguins)

docs/articles/partialling_out.html

@@ -3,7 +3,7 @@ pkgdown: 2.1.3.9000
 pkgdown_sha: 26cecc444a485bd22cd066612432e94818904b67
 articles:
   partialling_out: partialling_out.html
-last_built: 2025-08-21T09:13Z
+last_built: 2025-08-21T16:52Z
 urls:
   reference: https://marcboschmatas.github.io/partialling.out/reference
   article: https://marcboschmatas.github.io/partialling.out/articles