Find a pin in any board registered using board_register().

pin_find(text = NULL, board = NULL, name = NULL, extended = FALSE,
  ...)

Arguments

text

The text to find in the pin description or name.

board

The board name used to find the pin.

name

The exact name of the pin to match when searching.

extended

Should additional board-specific columns be shown?

...

Additional parameters.

Details

pin_find() allows you to discover new resources or retrieve pins you've previously created with pin().

The pins package comes with a CRAN packages board which allows searching all CRAN packages; however, you can add additional boards to search from like Kaggle, Github and RStudio Connect.

For 'local' and 'packages' boards, the 'text' parameter searches the title and description of a pin using a regular expression. Other boards search in different ways, most of them are just partial matches, please refer to their documentation to understand how other boards search for pins.

Once you find a pin, you can retrieve with pin_get("pin-name").

Examples

library(pins) # retrieve pins pin_find()
#> # A tibble: 18,941 x 4 #> name description type board #> <chr> <chr> <chr> <chr> #> 1 A3/housing "Boston Housing Prices from A3 package." table packa… #> 2 A3/multifuncti… "Ecosystem Multifunctionality from A3 package." table packa… #> 3 aaSEA/AAindex "A data frame of 533 amino acid properties from… table packa… #> 4 aaSEA/corSubFi… "A data frame of correlated sites from aaSEA pa… table packa… #> 5 aaSEA/Cruciani "A data frame of 3 Cruciani properties for 20 a… table packa… #> 6 aaSEA/Fasgai "A data frame of six Fasgai vectors for 20 amin… table packa… #> 7 aaSEA/Kidera "A data frame of 10 Kidera factors for 20 amino… table packa… #> 8 abc.data/musig… "A set of objects used to estimate the populati… table packa… #> 9 abc.data/ppc "Data to illustrate the posterior predictive ch… table packa… #> 10 ABC.RAP/annota… "annotation file for the 450k probes from ABC.R… table packa… #> # … with 18,931 more rows
# search pins related to 'cars' pin_find("cars")
#> # A tibble: 40 x 4 #> name description type board #> <chr> <chr> <chr> <chr> #> 1 bestNormalize/a… Prices of 6,283 cars listed on Autotrader from… table packa… #> 2 BSDA/Jdpower Number of problems reported per 100 cars in 19… table packa… #> 3 BSDA/Marked Percent of marked cars in 65 police department… table packa… #> 4 BSDA/Supercar Top speeds attained by five makes of supercars… table packa… #> 5 caret/cars Kelly Blue Book resale data for 2005 model yea… table packa… #> 6 CornerstoneR/ca… Data from carstats from CornerstoneR package. table packa… #> 7 DAAG/Cars93.sum… A Summary of the Cars93 Data set from DAAG pac… table packa… #> 8 DAAG/modelcars Model Car Data from DAAG package. table packa… #> 9 DAAG/toycars Toy Cars Data from DAAG package. table packa… #> 10 dobson/Cars Cars data from table 8.1 from dobson package. table packa… #> # … with 30 more rows
# search pins related to 'seattle' in the 'packages' board pin_find("seattle", board = "packages")
#> # A tibble: 6 x 4 #> name description type board #> <chr> <chr> <chr> <chr> #> 1 hpiR/ex_sales Subset of Seattle Home Sales from hpiR packag… table packa… #> 2 hpiR/seattle_sales Seattle Home Sales from hpiR package. table packa… #> 3 latticeExtra/Seat… Daily Rainfall and Temperature at the Seattle… table packa… #> 4 microsynth/seattl… Data for a crime intervention in Seattle, Was… table packa… #> 5 vegawidget/data_s… Example dataset: Seattle daily weather from v… table packa… #> 6 vegawidget/data_s… Example dataset: Seattle hourly temperatures … table packa…
# search pins related to 'london' in the 'packages' board pin_find("london", board = "packages")
#> # A tibble: 30 x 4 #> name description type board #> <chr> <chr> <chr> <chr> #> 1 bsamGP/London.Mortality Daily Moratlity in London from bsamGP … table packa… #> 2 DAAG/poxetc Deaths from various causes, in London … table packa… #> 3 DAAG/whoops Deaths from whooping cough, in London … table packa… #> 4 epimdr/meas Bi-weekly measles incidence in London … table packa… #> 5 ev.trawl/hourly_bloomsb… Hourly measurements of 6 air pollutant… table packa… #> 6 extremis/lse Selected Stocks from the London Stock … table packa… #> 7 geofacet/london_afford london_afford from geofacet package. table packa… #> 8 HistData/Arbuthnot Arbuthnot's data on male and female bi… table packa… #> 9 HistData/Cholera William Farr's Data on Cholera in Lond… table packa… #> 10 jomo/ExamScores Exam results for six inner London Educ… table packa… #> # … with 20 more rows
# \donttest{ # retrieve 'hpiR/seattle_sales' pin pin_get("hpiR/seattle_sales")
#> # A tibble: 43,313 x 16 #> pinx sale_id sale_price sale_date use_type area lot_sf wfnt bldg_grade #> <chr> <chr> <int> <date> <chr> <int> <int> <dbl> <int> #> 1 ..00… 2013..… 289000 2013-02-06 sfr 79 9295 0 7 #> 2 ..00… 2013..… 356000 2013-07-11 sfr 18 6000 0 6 #> 3 ..00… 2010..… 333500 2010-12-29 sfr 79 7200 0 8 #> 4 ..00… 2016..… 577200 2016-03-17 sfr 79 7200 0 8 #> 5 ..00… 2012..… 237000 2012-05-02 sfr 79 5662 0 7 #> 6 ..00… 2014..… 347500 2014-03-11 sfr 79 5830 0 7 #> 7 ..00… 2012..… 429000 2012-09-20 sfr 18 12700 0 7 #> 8 ..00… 2015..… 653295 2015-07-21 sfr 79 7000 0 7 #> 9 ..00… 2014..… 427650 2014-02-19 townhou… 79 3072 0 7 #> 10 ..00… 2015..… 488737 2015-03-19 townhou… 79 3072 0 7 #> # … with 43,303 more rows, and 7 more variables: tot_sf <int>, beds <int>, #> # baths <dbl>, age <int>, eff_age <int>, longitude <dbl>, latitude <dbl>
# retrieve 'bsamGP/London.Mortality' pin pin_get("bsamGP/London.Mortality")
#> # A tibble: 5,113 x 7 #> date tmean tmin tmax dewp rh death #> <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <int> #> 1 1993-01-01 4.63 1.57 7.67 2.39 79.4 233 #> 2 1993-01-02 -0.168 -2.76 2.40 -1.50 85.9 228 #> 3 1993-01-03 -0.875 -5.16 3.40 -5.22 69.4 228 #> 4 1993-01-04 2.48 -1.99 6.94 2.04 88.2 223 #> 5 1993-01-05 7.45 3.45 11.4 8.63 94.0 246 #> 6 1993-01-06 9.95 7.78 12.1 10.1 90.0 242 #> 7 1993-01-07 6.98 2.92 11.0 5.93 93.6 226 #> 8 1993-01-08 7.34 3.43 11.2 0.177 67.0 218 #> 9 1993-01-09 7.91 3.65 12.2 8.93 84.8 212 #> 10 1993-01-10 9.92 7.79 12.1 9.63 89.4 218 #> # … with 5,103 more rows
# }