| Title: | Interactive Functions to be Used as Shortcuts in 'RStudio' |
|---|---|
| Description: | 'RStudio' as of recently offers the option to define addins and assign shortcuts to them. This package contains addins for a few most frequently used functions in a data scientist's (at least mine) daily work (like str(), example(), plot(), head(), view(), Desc()). Most of these functions will use the current selection in the editor window and send the specific command to the console while instantly executing it. Assigning shortcuts to these addins will save you quite a few keystrokes. |
| Authors: | Andri Signorell [aut, cre] |
| Maintainer: | Andri Signorell <[email protected]> |
| License: | GPL (>= 2) |
| Version: | 1.12 |
| Built: | 2025-01-28 05:09:53 UTC |
| Source: | https://github.com/andrisignorell/desctoolsaddins |
Places an arrow into a plot. Two additional arrow heads are implemented.
Arrow(x0, y0, x1, y1, col = par("bg"), border = par("fg"), head = 1, cex = 1, lwd = 1, lty = 1)Arrow(x0, y0, x1, y1, col = par("bg"), border = par("fg"), head = 1, cex = 1, lwd = 1, lty = 1)
x0, y0
|
coordinates of points from which to draw. |
x1, y1
|
coordinates of points to which to draw. At least one must the supplied. |
col |
the color of the line and background color of the arrow head. |
border |
color of the arrow head. |
head |
type of head, can be one out of 1:3. |
cex |
extension factor for the arrow head. |
lwd |
line width |
lty |
line type |
Nothing returned
Andri Signorell <[email protected]>
library(DescTools) Canvas() Arrow(1, 1, 0, 0)library(DescTools) Canvas() Arrow(1, 1, 0, 0)
Choose a color by means of the system's color dialog. Nice for looking up RGB-values of any color.
ColorDlg()ColorDlg()
RGB value of the selected color
Andri Signorell <[email protected]>
ColPicker() plots the R-colors in a dense manner and allows to collect colors by using a locator. This can be helpful when some colors should be put together to a palette.
ColPicker(locator = TRUE, ord = c("hsv", "default"), label = c("text", "hex", "dec"), mdim = c(38, 12), newwin = FALSE)ColPicker(locator = TRUE, ord = c("hsv", "default"), label = c("text", "hex", "dec"), mdim = c(38, 12), newwin = FALSE)
locator |
logical, defines if the colors can be selected by mouseclick. Default is TRUE. |
ord |
the order of the colors, can be either defined by hsv-value or by the R internal color-number. Default is the latter. |
label |
label for the colors, can be the colorname (text), the hex-code (#RRGGBB) or the decimal RGB-number |
mdim |
the dimension of the color matrix. Default is 38 rows and 12 columns. |
newwin |
logical, defining if a new graphic device should be used. Default is |
The function plots all the colors but leaves out the grey scales grey() and gray().
Andri Signorell <[email protected]>
ColPicker(locator=FALSE, ord="hsv") ColPicker(locator=FALSE, label="hex")ColPicker(locator=FALSE, ord="hsv") ColPicker(locator=FALSE, label="hex")
Choose a directory interactively.
dir.choose(default = "", caption = "Select directory")dir.choose(default = "", caption = "Select directory")
default |
which directory to show initially. |
caption |
the caption on the selection dialog |
A length-one character vector, character NA if 'Cancel' was selected.
Andri Signorell <[email protected]>
## Not run: dir.choose(getwd(), "Choose a suitable folder") ## End(Not run)## Not run: dir.choose(getwd(), "Choose a suitable folder") ## End(Not run)
Import a file in SPSS, Stata, SAS, Minitab or Systat format interactively.
FileImportDlg(auto_type = TRUE, env = .GlobalEnv)FileImportDlg(auto_type = TRUE, env = .GlobalEnv)
auto_type |
determines if the type dialog should be displayed. Default is |
env |
environment in which the dataset should be created. |
The imported file will be assigned to the given variablename.
Andri Signorell <[email protected]>
read.dta(), read.spss(), read.systat(), read.ssd()
Handling of pathnames is tedious in Windows because of the backslashes, that prevent simple pasting of a copied path into the source code. FileOpenDlg() displays the FileOpen-Dialog for picking a file interactively. When done, backslashes in the returned path will be replaced by simple slashes as used in R path definitions. The edited path is returned.
FileOpenDlg(fmt = NULL)FileOpenDlg(fmt = NULL)
fmt |
the format, in which the filename parts should be returned. This can be defined quite flexible containing the elements path, filename and ext (file extension) enclosed by %. |
There are 2 predefined formats that can be addressed with fmt = 1 resp. fmt = 2.
1 will return the path enclosed by a typical read.table(...) command, 2 will do the same with load(...).
character string containing the path (also present in the clipboard)
Andri Signorell <[email protected]>
## Not run: # choose a file fn <- FileOpenDlg() print(gettextf("You chose the file: %s ", fn)) # the path and filename can as well be nested in a command, # done here to build a read.table command that can be well inserted into the code: FileOpenDlg(fmt="d.%fname% <- read.table(file = \"%path%\%fname%.%fxt%\", header = TRUE, sep = \";\", na.strings = c(\"NA\",\"NULL\"), strip.white = TRUE)") # go to your editor and paste... ## End(Not run)## Not run: # choose a file fn <- FileOpenDlg() print(gettextf("You chose the file: %s ", fn)) # the path and filename can as well be nested in a command, # done here to build a read.table command that can be well inserted into the code: FileOpenDlg(fmt="d.%fname% <- read.table(file = \"%path%\%fname%.%fxt%\", header = TRUE, sep = \";\", na.strings = c(\"NA\",\"NULL\"), strip.white = TRUE)") # go to your editor and paste... ## End(Not run)
ModelDlg() allows to compose model formulas based on the variablenames of a data.frame. The available variables can be filtered and sorted, which is helpful to keep the overview. Additional orientation is provided by the comments with which variables can be assigned. (See Label()). The labels will be displayed below the variable list.
The model dialog can also be used to edit an already existing formula. Simply select the model formula (including the data argument) and start the dialog.
ModelDlg(x, ...)ModelDlg(x, ...)
x |
the data frame containing the variables for the model. |
... |
further arguments to be passed to the default function. |
In the model dialog, the variablenames (extended with their class) of the selected data.frame are listed on the right, from where they can be inserted in the model box by clicking on a button between the two boxes. Clicking on the + button will use + to concatenate the variablenames.
The same applies analogously to * and :. inserts the chunk poly(<varname>, 2), the grade of the polynom can easily be changed in the formula edit field afterwards.
Any criteria for the variablename can be entered in the filterbox. The filter will be dynamically applied to the list. In order to get rid of the filter just empty the filterbox.
After clicking on ok, the formula temperature ~ area + driver + delivery_min, data=d.pizza will be inserted on the cursor position.
An already constructed formula can also be provided to the function. The model dialog will separate the single parts and populate the according textboxes.
the model formula
Andri Signorell <[email protected]>
## Not run: ModelDlg(d.pizza) ## End(Not run)## Not run: ModelDlg(d.pizza) ## End(Not run)
Controlling MS Word with RStudio has many convenient advantages. We can quickly create some reports on the fly and also use bookmarks to create dynamically updatable report chunks such as tables or graphics. Here we implement a set of functions to handle bookmarks in MS Word.
ToWrd() ToWrdWithBookmark() WrdBookmarks() CreateBookmark() SelectBookmark() UpdateBookmark() DeleteBookmark() RenameBookmark(name, newname, wrd = DescToolsOptions("lastWord")) RecreateBookmarkChunk()ToWrd() ToWrdWithBookmark() WrdBookmarks() CreateBookmark() SelectBookmark() UpdateBookmark() DeleteBookmark() RenameBookmark(name, newname, wrd = DescToolsOptions("lastWord")) RecreateBookmarkChunk()
name |
the name of the bookmark. |
newname |
the new name of the bookmark. |
wrd |
the pointer to a word instance. Can be a new one, created by |
WrdBookmarks() returns a data frame with all bookmarks in the current document (given by a handle created with GetCurrWrd() or GetNewWrd() and stored in DescToolsOptions("lastWord")), containing the bookmark's name, its id and type ("text", "plot", "other"), as well as the page number in the document where it starts.
> DescToolsAddIns::WrdBookmarks()
id name pagenr type
1 2 bmt182295322 1 text
2 3 bmp937470551 1 plot
ToWrd() directly sends the evaluation of the selected object in the source panel to the current Word instance. The function is generic and acts in dependency on the selected object. So far there are interfaces for characters, tables, models. Note that the inserted text is no longer updateable; as soon as it is inserted in the Word document the connection to it is lost.
ToWrdWithBookmark() inserts the object in the Word document and defines a bookmark that covers the whole range of the inserted object (including tables or graphics). Then the selected command chunk in the Rstudio source pane is enclosed in brackets and the name of the new defined bookmark is therein inserted as meta tag. If the R-code is later changed, the output in Word can simply be refreshed by selecting the code chunk in RStudio (including the meta tag) and click on the menu UpdateBookmark() (of course it's convenient to have a shortcut defined for that).
CreateBookmark() creates a bookmark at the current cursor position in a in an open Word document, using the currently selected text in RStudio as name. SelectBookmark(), DeleteBookmark() behave analogously.
RecreateBookmarkChunk() recreates the selected chunks in RStudio by inserting a bookmark if not existing and updating it with the result.
With the BookmarkDlg() there's an interactive support for handling bookmarks. Found bookmarks are presented in a sortable and filterable listbox. Selecting, deleting and renaming (not yet implemented) the selected bookmark is supported.
Andri Signorell <[email protected]>
The function PlotPar() plots the typically used parameters and their values.
PlotPar() PlotPch(col = NULL, bg = NULL, newwin = FALSE) PlotMar()PlotPar() PlotPch(col = NULL, bg = NULL, newwin = FALSE) PlotMar()
col |
the default plotting color for |
bg |
The color to be used for the background of the plot symbols. Default is |
newwin |
logical, defining if a new graphic device should be used. Default is |
PlotPch() will display the plot characters as defined by pch in all plots in a dialog.
PlotMar() plots the margins.
Andri Signorell <[email protected]>
PlotPar() PlotPch()PlotPar() PlotPch()
A simply great new feature in RStudio is the option to define add-ins and bind shortcuts to them.
This package includes add-ins for some of the most frequently used functions
in a data scientist's (at least mine) daily work (like str(), example(), plot(), head(), view(), Desc()).
Most of these functions use the current selection in RStudios source panel and send the specific command to the console
where it is executed immediately.
Assigning shortcuts to these add-ins saves you tons of keystrokes and brings a breeze of liberating and brake-releasing GUI-interaction into your R-life.
NewObject() FileOpen() FileBrowserOpen() FileSaveAs() GetExcelRange(env = .GlobalEnv, header = FALSE, echo = TRUE) GetExcelRangeH(env = .GlobalEnv) GetExcelTable(env = .GlobalEnv) XLView() IntView() Edit() FlushToSource() Select() Str() Str1() Abstract() Head() Some() Summary() Cat() Desc() Example() Info() Unclass() Plot() PlotD() SetArrow() InspectPnt() Enquote() EnquoteS() RemoveDuplicates() SortAsc() SortDesc() Shuffle() EvalEnquote() FlipBackSlash()NewObject() FileOpen() FileBrowserOpen() FileSaveAs() GetExcelRange(env = .GlobalEnv, header = FALSE, echo = TRUE) GetExcelRangeH(env = .GlobalEnv) GetExcelTable(env = .GlobalEnv) XLView() IntView() Edit() FlushToSource() Select() Str() Str1() Abstract() Head() Some() Summary() Cat() Desc() Example() Info() Unclass() Plot() PlotD() SetArrow() InspectPnt() Enquote() EnquoteS() RemoveDuplicates() SortAsc() SortDesc() Shuffle() EvalEnquote() FlipBackSlash()
env |
Environment for GetExcelRange to write the data. GlobalEnv is default. |
header |
logical determining if the import from XL should use a header or not |
echo |
should the function return an echo |
The following add-ins are available:
NewObject:
starts the good old internal editor and allows to enter values. In dependence of the initial selection in the code panel different objects will be returned. If the selection was m the code for a matrix will be created, if the selection is d then the code for a data.frame will be returned and a c will be interpreted as vector. Default is m. Note that column names can be defined within the editor, but not rownames (don't ask me why ...).
FileOpen:
get the path of a file to open and insert in code. (See also: Select())
FileBrowserOpen:
get a selected path and opens the systems filebrowser with the according directory.
FileImport:
display the import file dialog for importing SAS, SPSS, Stata, Systat and MiniTab files. (See FileImportDlg())
FileSaveAs:
display a file dialog, get the desired path and filename and save the selected object in the given place.
Several file types are supported csv/xlsx for data.frames, text/binary for other objects.
GetXLRange:
run DescTools command XLGetRange() by taking the current selection as name for the imported data and replace the current selection by the used code.
GetXLTable:
run DescTools command XLGetRange() by taking the current 3-fold selection as data matrix, rownames and columnnames and replace the current selection by the structure code.
XLView:
view selected object in MS-Excel, which makes sense for data.frames.
IntView:
view selected object with internal viewer (here again: only data.frames)
Edit:
run R-command fix() on the current selection. This is nice for editing data frames interactively.
FlushToSource:
run dput on the current selection and replace the selection with the result.
Select:
select or pick things interactively. This function as well evaluates the current selection. If the selection corresponds to pch a dialog for selecting point characters will be displayed. If it's col the ColPicker() dialog will be displayed. If it's any of path, fn, file the FileOpen() dialog will be displayed. In all other case the SelectVarDlg() on the current selection will be run. This can be used to select variablenames of a data.frame by mouse click or the levels of a factor (all depending on the class of the selected object). The variable names will be returned as string, enquoted and separated by a comma.
Str, Str1:
run DescTools command Str() on the current selection, Str1() shows only the first level ;
Abstract:
run DescTools command Abstract() (a less technical description than str(), meant for using with data.frames) on the current selection
Head:
run R-command head() on the current selection
Some:
run DescTools command Some() on the current selection
Summary:
run R-command summary() on the current selection
Cat:
run R-command cat(..., sep="\n") on the current selection
Desc:
run DescTools command Desc() on the current selection
Example:
run R-command example() on the current selection
Info:
print object properties of the currently selected object
Unclass:
run R-command unclass() on the current selection
Plot:
run plot() on the current selection
PlotD:
run plot(Desc()) on the current selection
SetArrow:
place an arrow in a plot and insert code into source file
InspectPnt:
Lauch IdentifyA(... , poly=TRUE) with the current selection as argument and returns the selected points on the plot.
BuildModel:
display dialog for building up a model formula interactively by point and click. (See ModelDlg())
Enquote, EnquoteS:
split the selected text in the source panel using line breaks as separators, enquote the sections using either double or single quotation marks, and paste them separated by comma.
RemoveDuplicates:
remove all the duplicates (by row) of the selected text.
SortAsc, SortDesc, Shuffle:
sorts the selected text by row in ascending, descending, resp. random order.
EvalEnquote:
evaluates the selection before enquoting the parts and paste them separated by comma. This can be used to enquote factors.
FlipBackSlash:
Handling backslashes in pathnames can be really annoying on Windows. This function replaces all backslashes in the selected text by simple slashes. In the first step all backlashes are replaced by slashes, in further applications of the function, flipflops are performed between slashes and backslashes. The option ReplaceDoubleSlash controls whether double slashes should be replaced by simple ones.
It's cool to set this command to the keyboard shortcut: Ctrl+Shift+/
As soon as the package is loaded once, the AddIns will be listed in RStudios AddIns listbox:
The keyboard shortcuts can then be assigned by clicking on the menu Tools | Modify Keyboard Shortcuts... and scroll down to the Addin scope:
Andri Signorell <[email protected]>
if (interactive()){ Str() }if (interactive()){ Str() }
SelectVarDlg() is a GUI utility, which brings up a dialog and lets the user select elements (either variables of a data.frame or
levels of a factor) by point and click in a listbox. The list of selected items is written to the clipboard so
that the code can afterwards easily be pasted in the source file.
This function is best used together with the package DescToolsAddIns, with which the functions can be assigned to a keystroke in RStudio.
SelectVarDlg(x, ...) ## Default S3 method: SelectVarDlg(x, useIndex = FALSE, ...) ## S3 method for class 'factor' SelectVarDlg(x, ...) ## S3 method for class 'data.frame' SelectVarDlg(x, ...)SelectVarDlg(x, ...) ## Default S3 method: SelectVarDlg(x, useIndex = FALSE, ...) ## S3 method for class 'factor' SelectVarDlg(x, ...) ## S3 method for class 'data.frame' SelectVarDlg(x, ...)
x |
the object containing the elements to be selected. x can be a data.frame, a factor or any other vector. |
useIndex |
defines, if the enquoted variablenames (default) or the index values should be returned. |
... |
further arguments to be passed to the default function. |
When working with big data.frames with many variables it is often tedious to build subsets by typing the
columnnames. Here is where the function comes in offering a "point and click" approach for selecting the interesting
columns.
When x is a data.frame the columnnames are listed,
when x is a factor the according levels are listed and in all other cases the list is filled with the unique elements of x.
SelectVarDlg() checks for an option "selkey" for defining the selection keywords, defined as a list of this structure:
file |
the keywords to be interpreted as a filename, defaults to c("fn","file","filename") |
dir |
the keywords to be interpreted as a directory name, defaults to c("path","dir")
|
col |
the keywords to be interpreted as a color, defaults to c("col","color")
|
pch
|
the keywords to be interpreted as a point character, defaults to c("pch")
|
It can be set with
options(selkey = list(file=c("fn","file","filename"),
dir=c("path","dir", "dirname"),
col=c("color", "col"),
pch=c("pch"))
)
A comma separated list with the selected values enquoted is returned invisibly as well as written to clipboard for easy inserting the text in an editor afterwards.
Andri Signorell <[email protected]>
## Not run: SelectVarDlg(x = d.pizza$driver) SelectVarDlg(x = d.pizza, useIndex=TRUE) SelectVarDlg(d.pizza$driver) x <- replicate(10, paste(sample(LETTERS, 5, replace = TRUE), collapse="")) SelectVarDlg(x) ## End(Not run)## Not run: SelectVarDlg(x = d.pizza$driver) SelectVarDlg(x = d.pizza, useIndex=TRUE) SelectVarDlg(d.pizza$driver) x <- replicate(10, paste(sample(LETTERS, 5, replace = TRUE), collapse="")) SelectVarDlg(x) ## End(Not run)
Use RStudio's manipulator to explore a data.frame by dynamically creating xy-scatterplots, boxplots and others. Numerical descriptions can as well be produced on the fly.
Xplore(x)Xplore(x)
x |
the data.frame to be explored. |
This function helps to get rid of the afterwards superfluous R-code created while exploring a dataset.
Andri Signorell <[email protected]>
## Not run: Xplore(d.pizza) ## End(Not run)## Not run: Xplore(d.pizza) ## End(Not run)