# Using the helper functions

The `arcpy` package provides a small number of helper functions to make working with spatial layer geometries and attributes easier. These helper functions are essentially wrappers for the arpcy Data Access module that support simple transfer of information between spatial layers and R data frames.

To demonstrate the helper functions, we'll set up a workspace with a copy of the California County Boundaries shapefile (available on https://data.ca.gov). A copy of this file is included with the `arcpy` package.

    library(arcpy)

    # set workspace
    arcpy$env$workspace = tempdir()
    arcpy$env$scratchWorkspace = tempdir()

    # copy feature for example
    fc = arcpy$management$CopyFeatures(system.file("CA_Counties",
      "CA_Counties_TIGER2016.shp", package = "arcpy"), "CA_Counties")

Reading attribute tables is accomplished using the function `da_read`.

    head(da_read(fc, fields = c("FID", "NAME")))

    ##   FID          NAME
    ## 1   0        Sierra
    ## 2   1    Sacramento
    ## 3   2 Santa Barbara
    ## 4   3     Calaveras
    ## 5   4       Ventura
    ## 6   5   Los Angeles

Tokens are also supported by `arcpy`. If you have the `tibble` package installed, you can read geometry tokens as list columns.

    da_read(fc, fields = c("OID@", "NAME", "SHAPE@TRUECENTROID"))

    ## Loading required namespace: tibble

    ## # A tibble: 58 × 3
    ##    `OID@` NAME          `SHAPE@TRUECENTROID`
    ##     <int> <chr>         <list>
    ##  1      0 Sierra        <list [2]>
    ##  2      1 Sacramento    <list [2]>
    ##  3      2 Santa Barbara <list [2]>
    ##  4      3 Calaveras     <list [2]>
    ##  5      4 Ventura       <list [2]>
    ##  6      5 Los Angeles   <list [2]>
    ##  7      6 Sonoma        <list [2]>
    ##  8      7 Kings         <list [2]>
    ##  9      8 San Diego     <list [2]>
    ## 10      9 Placer        <list [2]>
    ## # ℹ 48 more rows

You can use `da_update` to modify attributes.

    d = da_read(fc, fields = "NAME")
    d["NAME"] = paste(d$NAME, "County, CA")
    da_update(fc, d)

    head(da_read(fc, fields = "NAME"))

    ##                       NAME
    ## 1        Sierra County, CA
    ## 2    Sacramento County, CA
    ## 3 Santa Barbara County, CA
    ## 4     Calaveras County, CA
    ## 5       Ventura County, CA
    ## 6   Los Angeles County, CA

You can also use `da_update` to add additional fields to a table, provided you create the field first.

    d = da_read(fc, c("ALAND", "AWATER"))
    d["FRACLAND"] = d$ALAND / (d$ALAND + d$AWATER)

    arcpy$management$AddField(fc, "FRACLAND", "FLOAT")
    da_update(fc, d["FRACLAND"])

You can use `da_drop` and `da_insert` to remove and add rows, respectively.

    d = da_read(fc)
    # extract second row
    new.d = d[2,]
    # drop second row
    da_drop(fc, 2)
    # add the row back
    da_insert(fc, new.d)

    head(da_read(fc))

    ## # A tibble: 6 × 20
    ##     FID Shape      STATEFP COUNTYFP COUNTYNS GEOID NAME   NAMELSAD LSAD  CLASSFP
    ##   <int> <list>     <chr>   <chr>    <chr>    <chr> <chr>  <chr>    <chr> <chr>
    ## 1     0 <list [2]> 06      091      00277310 06091 Sierr… Sierra … 06    H1
    ## 2     1 <list [2]> 06      083      00277306 06083 Santa… Santa B… 06    H1
    ## 3     2 <list [2]> 06      009      01675885 06009 Calav… Calaver… 06    H1
    ## 4     3 <list [2]> 06      111      00277320 06111 Ventu… Ventura… 06    H1
    ## 5     4 <list [2]> 06      037      00277283 06037 Los A… Los Ang… 06    H1
    ## 6     5 <list [2]> 06      097      01657246 06097 Sonom… Sonoma … 06    H1
    ## # ℹ 10 more variables: MTFCC <chr>, CSAFP <chr>, CBSAFP <chr>, METDIVFP <chr>,
    ## #   FUNCSTAT <chr>, ALAND <dbl>, AWATER <dbl>, INTPTLAT <chr>, INTPTLON <chr>,
    ## #   FRACLAND <dbl>