S3 method to flatten an npi_results object
Arguments
- df
A data frame containing the results of a call to
npi_search.- cols
If non-NULL, only the named columns specified here will be be flattened and returned along with
npi.- key
A quoted column name from
dfto use as a matching key. The default value is"npi".
Examples
# Flatten all list columns
data(npis)
npi_flatten(npis)
#> # A tibble: 48 × 42
#> npi basic_fi…¹ basic…² basic…³ basic…⁴ basic…⁵ basic…⁶ basic…⁷ basic…⁸
#> <int> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 1194276360 ALYSSA COWNAN PA NO F 2016-1… 2018-0… A
#> 2 1194276360 ALYSSA COWNAN PA NO F 2016-1… 2018-0… A
#> 3 1306849641 MARK MOHRMA… MD NO M 2005-0… 2019-0… A
#> 4 1306849641 MARK MOHRMA… MD NO M 2005-0… 2019-0… A
#> 5 1306849641 MARK MOHRMA… MD NO M 2005-0… 2019-0… A
#> 6 1306849641 MARK MOHRMA… MD NO M 2005-0… 2019-0… A
#> 7 1326403213 RAJEE KRAUSE AGPCNP… NO F 2015-1… 2019-0… A
#> 8 1326403213 RAJEE KRAUSE AGPCNP… NO F 2015-1… 2019-0… A
#> 9 1326403213 RAJEE KRAUSE AGPCNP… NO F 2015-1… 2019-0… A
#> 10 1326403213 RAJEE KRAUSE AGPCNP… NO F 2015-1… 2019-0… A
#> # … with 38 more rows, 33 more variables: basic_name <chr>,
#> # basic_name_prefix <chr>, basic_middle_name <chr>,
#> # basic_organization_name <chr>, basic_organizational_subpart <chr>,
#> # basic_authorized_official_credential <chr>,
#> # basic_authorized_official_first_name <chr>,
#> # basic_authorized_official_last_name <chr>,
#> # basic_authorized_official_middle_name <chr>, …
# Only flatten specified columns
npi_flatten(npis, cols = c("basic", "identifiers"))
#> # A tibble: 12 × 25
#> npi basic_fi…¹ basic…² basic…³ basic…⁴ basic…⁵ basic…⁶ basic…⁷ basic…⁸
#> <int> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 1194276360 ALYSSA COWNAN PA NO F 2016-1… 2018-0… A
#> 2 1306849641 MARK MOHRMA… MD NO M 2005-0… 2019-0… A
#> 3 1326403213 RAJEE KRAUSE AGPCNP… NO F 2015-1… 2019-0… A
#> 4 1346604592 SARAH LOWRY OTR/L YES F 2016-0… 2018-0… A
#> 5 1427454529 YONGHONG TAN NA NO F 2014-1… 2018-1… A
#> 6 1558362566 AMY TIERST… M.D. YES F 2005-0… 2019-0… A
#> 7 1558713628 ROBYN NOHLING FNP-BC… YES F 2016-0… 2018-0… A
#> 8 1639173065 SAKSHI DUA M.D. YES F 2005-0… 2019-0… A
#> 9 1639173065 SAKSHI DUA M.D. YES F 2005-0… 2019-0… A
#> 10 1639173065 SAKSHI DUA M.D. YES F 2005-0… 2019-0… A
#> 11 1790786416 NOAH GOLDMAN M.D. NO M 2005-0… 2018-0… A
#> 12 1962983775 NA NA NA NA NA 2018-0… 2018-0… A
#> # … with 16 more variables: basic_name <chr>, basic_name_prefix <chr>,
#> # basic_middle_name <chr>, basic_organization_name <chr>,
#> # basic_organizational_subpart <chr>,
#> # basic_authorized_official_credential <chr>,
#> # basic_authorized_official_first_name <chr>,
#> # basic_authorized_official_last_name <chr>,
#> # basic_authorized_official_middle_name <chr>, …