`shadow_long` throws an error when gathering variables.
siavash-babaei opened this issue · comments
shadow_long throws an error when gathering variables: pivot_longer cannot combine variables!!!
# Library for dealing with missing values
library(naniar)
# Load `oceanbuoys` data
data("oceanbuoys")
# Impute the mean value and track the imputations
ocean_imp_mean <- oceanbuoys |>
naniar::nabular(only_miss = TRUE) |>
naniar::impute_mean_all() |>
naniar::add_label_shadow()
# Gather the imputed data: Throws an error
ocean_imp_mean |>
naniar::shadow_long(humidity, air_temp_c)
#> Error in `tidyr::pivot_longer()`:
#> ! Can't combine `year` <double> and `any_missing` <character>.
#> Backtrace:
#> ▆
#> 1. ├─naniar::shadow_long(ocean_imp_mean, humidity, air_temp_c)
#> 2. │ ├─tidyr::pivot_longer(...)
#> 3. │ └─tidyr:::pivot_longer.data.frame(...)
#> 4. │ └─tidyr::pivot_longer_spec(...)
#> 5. │ └─vctrs::vec_ptype_common(...)
#> 6. └─vctrs (local) `<fn>`()
#> 7. └─vctrs::vec_default_ptype2(...)
#> 8. ├─base::withRestarts(...)
#> 9. │ └─base (local) withOneRestart(expr, restarts[[1L]])
#> 10. │ └─base (local) doWithOneRestart(return(expr), restart)
#> 11. └─vctrs::stop_incompatible_type(...)
#> 12. └─vctrs:::stop_incompatible(...)
#> 13. └─vctrs:::stop_vctrs(...)
#> 14. └─rlang::abort(message, class = c(class, "vctrs_error"), ..., call = vctrs_error_call(call))
# Gather the imputed data: Works like a charm
ocean_imp_mean |>
tidyr::pivot_longer(
cols = c("humidity", "air_temp_c"),
names_to = "variable",
values_to = "value",
) |>
tidyr::pivot_longer(
cols = c("humidity_NA", "air_temp_c_NA"),
names_to = "variable_NA",
values_to = "value_NA",
)
#> # A tibble: 2,944 × 12
#> year latitude longit…¹ sea_t…² wind_ew wind_ns sea_t…³ any_m…⁴ varia…⁵ value
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <fct> <chr> <chr> <dbl>
#> 1 1997 0 -110 27.6 -6.40 5.40 !NA Not Mi… humidi… 79.6
#> 2 1997 0 -110 27.6 -6.40 5.40 !NA Not Mi… humidi… 79.6
#> 3 1997 0 -110 27.6 -6.40 5.40 !NA Not Mi… air_te… 27.1
#> 4 1997 0 -110 27.6 -6.40 5.40 !NA Not Mi… air_te… 27.1
#> 5 1997 0 -110 27.5 -5.30 5.30 !NA Not Mi… humidi… 75.8
#> 6 1997 0 -110 27.5 -5.30 5.30 !NA Not Mi… humidi… 75.8
#> 7 1997 0 -110 27.5 -5.30 5.30 !NA Not Mi… air_te… 27.0
#> 8 1997 0 -110 27.5 -5.30 5.30 !NA Not Mi… air_te… 27.0
#> 9 1997 0 -110 27.6 -5.10 4.5 !NA Not Mi… humidi… 76.5
#> 10 1997 0 -110 27.6 -5.10 4.5 !NA Not Mi… humidi… 76.5
#> # … with 2,934 more rows, 2 more variables: variable_NA <chr>, value_NA <fct>,
#> # and abbreviated variable names ¹longitude, ²sea_temp_c, ³sea_temp_c_NA,
#> # ⁴any_missing, ⁵variable
Thanks for posting this - this is a new error introduced in the latest release, I confirm that I get the same error:
# Library for dealing with missing values
library(naniar)
# Load `oceanbuoys` data
data("oceanbuoys")
# Impute the mean value and track the imputations
ocean_imp_mean <- oceanbuoys |>
naniar::nabular(only_miss = TRUE) |>
naniar::impute_mean_all() |>
naniar::add_label_shadow()
# Gather the imputed data: Throws an error
ocean_imp_mean |>
naniar::shadow_long(humidity, air_temp_c)
#> Error in `tidyr::pivot_longer()`:
#> ! Can't combine `year` <double> and `any_missing` <character>.
#> Backtrace:
#> ▆
#> 1. ├─naniar::shadow_long(ocean_imp_mean, humidity, air_temp_c)
#> 2. │ ├─tidyr::pivot_longer(...)
#> 3. │ └─tidyr:::pivot_longer.data.frame(...)
#> 4. │ └─tidyr::pivot_longer_spec(...)
#> 5. │ └─vctrs::vec_ptype_common(...)
#> 6. └─vctrs (local) `<fn>`()
#> 7. └─vctrs::vec_default_ptype2(...)
#> 8. ├─base::withRestarts(...)
#> 9. │ └─base (local) withOneRestart(expr, restarts[[1L]])
#> 10. │ └─base (local) doWithOneRestart(return(expr), restart)
#> 11. └─vctrs::stop_incompatible_type(...)
#> 12. └─vctrs:::stop_incompatible(...)
#> 13. └─vctrs:::stop_vctrs(...)
#> 14. └─rlang::abort(message, class = c(class, "vctrs_error"), ..., call = vctrs_error_call(call))Created on 2023-03-30 with reprex v2.0.2
Session info
sessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#> setting value
#> version R version 4.2.2 (2022-10-31)
#> os macOS Ventura 13.2
#> system aarch64, darwin20
#> ui X11
#> language (EN)
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
#> tz Australia/Hobart
#> date 2023-03-30
#> pandoc 2.19.2 @ /Applications/RStudio.app/Contents/Resources/app/quarto/bin/tools/ (via rmarkdown)
#>
#> ─ Packages ───────────────────────────────────────────────────────────────────
#> package * version date (UTC) lib source
#> cli 3.6.0 2023-01-09 [1] CRAN (R 4.2.0)
#> colorspace 2.1-0 2023-01-23 [1] CRAN (R 4.2.0)
#> digest 0.6.31 2022-12-11 [1] CRAN (R 4.2.0)
#> dplyr 1.1.0 2023-01-29 [1] CRAN (R 4.2.1)
#> evaluate 0.20 2023-01-17 [1] CRAN (R 4.2.0)
#> fansi 1.0.4 2023-01-22 [1] CRAN (R 4.2.0)
#> fastmap 1.1.0 2021-01-25 [1] CRAN (R 4.2.0)
#> fs 1.6.1 2023-02-06 [1] CRAN (R 4.2.0)
#> generics 0.1.3 2022-07-05 [1] CRAN (R 4.2.0)
#> ggplot2 3.4.1 2023-02-10 [1] CRAN (R 4.2.0)
#> glue 1.6.2 2022-02-24 [1] CRAN (R 4.2.0)
#> gtable 0.3.1 2022-09-01 [1] CRAN (R 4.2.0)
#> htmltools 0.5.4 2022-12-07 [1] CRAN (R 4.2.0)
#> knitr 1.42 2023-01-25 [1] CRAN (R 4.2.0)
#> lifecycle 1.0.3 2022-10-07 [1] CRAN (R 4.2.0)
#> magrittr 2.0.3 2022-03-30 [1] CRAN (R 4.2.0)
#> munsell 0.5.0 2018-06-12 [1] CRAN (R 4.2.0)
#> naniar * 1.0.0 2023-02-02 [1] CRAN (R 4.2.0)
#> pillar 1.8.1 2022-08-19 [1] CRAN (R 4.2.0)
#> pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.2.0)
#> purrr 1.0.1 2023-01-10 [1] CRAN (R 4.2.0)
#> R.cache 0.16.0 2022-07-21 [1] CRAN (R 4.2.0)
#> R.methodsS3 1.8.2 2022-06-13 [1] CRAN (R 4.2.0)
#> R.oo 1.25.0 2022-06-12 [1] CRAN (R 4.2.0)
#> R.utils 2.12.2 2022-11-11 [1] CRAN (R 4.2.0)
#> R6 2.5.1 2021-08-19 [1] CRAN (R 4.2.0)
#> reprex 2.0.2 2022-08-17 [1] CRAN (R 4.2.0)
#> rlang 1.0.6 2022-09-24 [1] CRAN (R 4.2.0)
#> rmarkdown 2.20 2023-01-19 [1] CRAN (R 4.2.0)
#> rstudioapi 0.14 2022-08-22 [1] CRAN (R 4.2.0)
#> scales 1.2.1 2022-08-20 [1] CRAN (R 4.2.0)
#> sessioninfo 1.2.2 2021-12-06 [1] CRAN (R 4.2.0)
#> styler 1.9.0 2023-01-15 [1] CRAN (R 4.2.0)
#> tibble 3.1.8 2022-07-22 [1] CRAN (R 4.2.0)
#> tidyr 1.3.0 2023-01-24 [1] CRAN (R 4.2.0)
#> tidyselect 1.2.0 2022-10-10 [1] CRAN (R 4.2.0)
#> utf8 1.2.3 2023-01-31 [1] CRAN (R 4.2.0)
#> vctrs 0.5.2 2023-01-23 [1] CRAN (R 4.2.0)
#> visdat 0.6.0 2023-02-02 [1] local
#> withr 2.5.0 2022-03-03 [1] CRAN (R 4.2.0)
#> xfun 0.37 2023-01-31 [1] CRAN (R 4.2.0)
#> yaml 2.3.7 2023-01-23 [1] CRAN (R 4.2.0)
#>
#> [1] /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/library
#>
#> ──────────────────────────────────────────────────────────────────────────────Thanks again for posting this, this will be fixed in an upcoming release.
Thank you again for this @siavash-babaei !
This now works, but by default changes value to character, as that is the safest way to have this always succeed. Otherwise you can specify your own coercion function to transform value values. Here's an example:
library(naniar)
aq_shadow <- nabular(airquality)
shadow_long(aq_shadow)
#> # A tibble: 918 × 4
#> variable value variable_NA value_NA
#> <chr> <chr> <chr> <fct>
#> 1 Ozone 41 Ozone_NA !NA
#> 2 Solar.R 190 Solar.R_NA !NA
#> 3 Wind 7.4 Wind_NA !NA
#> 4 Temp 67 Temp_NA !NA
#> 5 Month 5 Month_NA !NA
#> 6 Day 1 Day_NA !NA
#> 7 Ozone 36 Ozone_NA !NA
#> 8 Solar.R 118 Solar.R_NA !NA
#> 9 Wind 8 Wind_NA !NA
#> 10 Temp 72 Temp_NA !NA
#> # ℹ 908 more rows
# then filter only on Ozone and Solar.R
shadow_long(aq_shadow, Ozone, Solar.R)
#> # A tibble: 306 × 4
#> variable value variable_NA value_NA
#> <chr> <chr> <chr> <fct>
#> 1 Ozone 41 Ozone_NA !NA
#> 2 Solar.R 190 Solar.R_NA !NA
#> 3 Ozone 36 Ozone_NA !NA
#> 4 Solar.R 118 Solar.R_NA !NA
#> 5 Ozone 12 Ozone_NA !NA
#> 6 Solar.R 149 Solar.R_NA !NA
#> 7 Ozone 18 Ozone_NA !NA
#> 8 Solar.R 313 Solar.R_NA !NA
#> 9 Ozone <NA> Ozone_NA NA
#> 10 Solar.R <NA> Solar.R_NA NA
#> # ℹ 296 more rows
# ensure `value` is numeric
shadow_long(aq_shadow, fn_value_transform = as.numeric)
#> # A tibble: 918 × 4
#> variable value variable_NA value_NA
#> <chr> <dbl> <chr> <fct>
#> 1 Ozone 41 Ozone_NA !NA
#> 2 Solar.R 190 Solar.R_NA !NA
#> 3 Wind 7.4 Wind_NA !NA
#> 4 Temp 67 Temp_NA !NA
#> 5 Month 5 Month_NA !NA
#> 6 Day 1 Day_NA !NA
#> 7 Ozone 36 Ozone_NA !NA
#> 8 Solar.R 118 Solar.R_NA !NA
#> 9 Wind 8 Wind_NA !NA
#> 10 Temp 72 Temp_NA !NA
#> # ℹ 908 more rows
shadow_long(aq_shadow, Ozone, Solar.R, fn_value_transform = as.numeric)
#> # A tibble: 306 × 4
#> variable value variable_NA value_NA
#> <chr> <dbl> <chr> <fct>
#> 1 Ozone 41 Ozone_NA !NA
#> 2 Solar.R 190 Solar.R_NA !NA
#> 3 Ozone 36 Ozone_NA !NA
#> 4 Solar.R 118 Solar.R_NA !NA
#> 5 Ozone 12 Ozone_NA !NA
#> 6 Solar.R 149 Solar.R_NA !NA
#> 7 Ozone 18 Ozone_NA !NA
#> 8 Solar.R 313 Solar.R_NA !NA
#> 9 Ozone NA Ozone_NA NA
#> 10 Solar.R NA Solar.R_NA NA
#> # ℹ 296 more rowsCreated on 2023-05-01 with reprex v2.0.2
Session info
sessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#> setting value
#> version R version 4.3.0 (2023-04-21)
#> os macOS Ventura 13.2
#> system aarch64, darwin20
#> ui X11
#> language (EN)
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
#> tz America/Los_Angeles
#> date 2023-05-01
#> pandoc 2.19.2 @ /Applications/RStudio.app/Contents/Resources/app/quarto/bin/tools/ (via rmarkdown)
#>
#> ─ Packages ───────────────────────────────────────────────────────────────────
#> package * version date (UTC) lib source
#> cli 3.6.1 2023-03-23 [1] CRAN (R 4.3.0)
#> colorspace 2.1-0 2023-01-23 [1] CRAN (R 4.3.0)
#> digest 0.6.31 2022-12-11 [1] CRAN (R 4.3.0)
#> dplyr 1.1.2 2023-04-20 [1] CRAN (R 4.3.0)
#> evaluate 0.20 2023-01-17 [1] CRAN (R 4.3.0)
#> fansi 1.0.4 2023-01-22 [1] CRAN (R 4.3.0)
#> fastmap 1.1.1 2023-02-24 [1] CRAN (R 4.3.0)
#> fs 1.6.2 2023-04-25 [1] CRAN (R 4.3.0)
#> generics 0.1.3 2022-07-05 [1] CRAN (R 4.3.0)
#> ggplot2 3.4.2 2023-04-03 [1] CRAN (R 4.3.0)
#> glue 1.6.2 2022-02-24 [1] CRAN (R 4.3.0)
#> gtable 0.3.3 2023-03-21 [1] CRAN (R 4.3.0)
#> htmltools 0.5.5 2023-03-23 [1] CRAN (R 4.3.0)
#> knitr 1.42 2023-01-25 [1] CRAN (R 4.3.0)
#> lifecycle 1.0.3 2022-10-07 [1] CRAN (R 4.3.0)
#> magrittr 2.0.3 2022-03-30 [1] CRAN (R 4.3.0)
#> munsell 0.5.0 2018-06-12 [1] CRAN (R 4.3.0)
#> naniar * 1.0.0.9000 2023-05-01 [1] local
#> pillar 1.9.0 2023-03-22 [1] CRAN (R 4.3.0)
#> pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.3.0)
#> purrr 1.0.1 2023-01-10 [1] CRAN (R 4.3.0)
#> R.cache 0.16.0 2022-07-21 [1] CRAN (R 4.3.0)
#> R.methodsS3 1.8.2 2022-06-13 [1] CRAN (R 4.3.0)
#> R.oo 1.25.0 2022-06-12 [1] CRAN (R 4.3.0)
#> R.utils 2.12.2 2022-11-11 [1] CRAN (R 4.3.0)
#> R6 2.5.1 2021-08-19 [1] CRAN (R 4.3.0)
#> reprex 2.0.2 2022-08-17 [1] CRAN (R 4.3.0)
#> rlang 1.1.0 2023-03-14 [1] CRAN (R 4.3.0)
#> rmarkdown 2.21 2023-03-26 [1] CRAN (R 4.3.0)
#> rstudioapi 0.14 2022-08-22 [1] CRAN (R 4.3.0)
#> scales 1.2.1 2022-08-20 [1] CRAN (R 4.3.0)
#> sessioninfo 1.2.2 2021-12-06 [1] CRAN (R 4.3.0)
#> styler 1.9.1 2023-03-04 [1] CRAN (R 4.3.0)
#> tibble 3.2.1 2023-03-20 [1] CRAN (R 4.3.0)
#> tidyr 1.3.0 2023-01-24 [1] CRAN (R 4.3.0)
#> tidyselect 1.2.0 2022-10-10 [1] CRAN (R 4.3.0)
#> utf8 1.2.3 2023-01-31 [1] CRAN (R 4.3.0)
#> vctrs 0.6.2 2023-04-19 [1] CRAN (R 4.3.0)
#> visdat 0.6.0 2023-02-02 [1] CRAN (R 4.3.0)
#> withr 2.5.0 2022-03-03 [1] CRAN (R 4.3.0)
#> xfun 0.39 2023-04-20 [1] CRAN (R 4.3.0)
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#>
#> [1] /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library
#>
#> ──────────────────────────────────────────────────────────────────────────────