CRAN Package Check Results for Package cheese

Last updated on 2020-02-17 22:49:27 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.0.3 3.51 48.54 52.05 OK
r-devel-linux-x86_64-debian-gcc 0.0.3 2.68 36.98 39.66 OK
r-devel-linux-x86_64-fedora-clang 0.0.3 62.85 OK
r-devel-linux-x86_64-fedora-gcc 0.0.3 59.32 OK
r-devel-windows-ix86+x86_64 0.0.3 9.00 54.00 63.00 OK
r-devel-windows-ix86+x86_64-gcc8 0.0.2 15.00 97.00 112.00 ERROR
r-patched-linux-x86_64 0.0.3 2.98 42.89 45.87 OK
r-patched-solaris-x86 0.0.3 92.20 OK
r-release-linux-x86_64 0.0.3 2.87 42.96 45.83 OK
r-release-windows-ix86+x86_64 0.0.2 6.00 65.00 71.00 ERROR
r-release-osx-x86_64 0.0.3 OK
r-oldrel-windows-ix86+x86_64 0.0.3 9.00 76.00 85.00 OK
r-oldrel-osx-x86_64 0.0.3 OK

Check Details

Version: 0.0.2
Check: examples
Result: ERROR
    Running examples in 'cheese-Ex.R' failed
    The error most likely occurred in:
    
    > ### Name: stretch
    > ### Title: Stretch one or variables over many columns by one or more keys
    > ### Aliases: stretch
    >
    > ### ** Examples
    >
    > require(tidyverse)
    Loading required package: tidyverse
    -- Attaching packages --------------------------------------- tidyverse 1.3.0 --
    v ggplot2 3.2.1 v purrr 0.3.3
    v tibble 2.1.3 v dplyr 0.8.3
    v tidyr 1.0.2 v stringr 1.4.0
    v readr 1.3.1 v forcats 0.4.0
    -- Conflicts ------------------------------------------ tidyverse_conflicts() --
    x dplyr::filter() masks stats::filter()
    x dplyr::lag() masks stats::lag()
    >
    > #Make data frame with multiple summary columns
    > temp_summary <-
    +
    + heart_disease %>%
    + group_by(
    + Sex,
    + HeartDisease,
    + BloodSugar
    + ) %>%
    + summarise(
    + Mean = mean(Age, na.rm = TRUE),
    + SD = sd(Age, na.rm = TRUE),
    + Median = median(Age, na.rm = TRUE)
    + ) %>%
    + ungroup()
    >
    > #1) Span summaries for each combination of Sex and BloodSugar
    > temp_summary %>%
    + stretch(
    + keys = c("Sex", "BloodSugar"),
    + keep = "HeartDisease"
    + )
    # A tibble: 2 x 13
     HeartDisease Mean_Female_FAL~ SD_Female_FALSE Median_Female_F~ Mean_Male_FALSE
     <fct> <dbl> <dbl> <dbl> <dbl>
    1 No 54.0 10.4 53.5 50.2
    2 Yes 59.7 3.61 61 55.8
    # ... with 8 more variables: SD_Male_FALSE <dbl>, Median_Male_FALSE <dbl>,
    # Mean_Female_TRUE <dbl>, SD_Female_TRUE <dbl>, Median_Female_TRUE <dbl>,
    # Mean_Male_TRUE <dbl>, SD_Male_TRUE <dbl>, Median_Male_TRUE <dbl>
    >
    > #2) If "HeartDisease" wasn't fully crossed, use different joining to get only matching groups
    > temp_summary %>%
    + stretch(
    + keys = c("Sex", "BloodSugar"),
    + keep = "HeartDisease",
    + join = inner_join
    + )
    # A tibble: 2 x 13
     HeartDisease Mean_Female_FAL~ SD_Female_FALSE Median_Female_F~ Mean_Male_FALSE
     <fct> <dbl> <dbl> <dbl> <dbl>
    1 No 54.0 10.4 53.5 50.2
    2 Yes 59.7 3.61 61 55.8
    # ... with 8 more variables: SD_Male_FALSE <dbl>, Median_Male_FALSE <dbl>,
    # Mean_Female_TRUE <dbl>, SD_Female_TRUE <dbl>, Median_Female_TRUE <dbl>,
    # Mean_Male_TRUE <dbl>, SD_Male_TRUE <dbl>, Median_Male_TRUE <dbl>
    >
    > #3) Only send two of the summaries
    > temp_summary %>%
    + stretch(
    + keys = c("Sex", "BloodSugar"),
    + keep = "HeartDisease",
    + send = c("Mean", "Median")
    + )
    # A tibble: 2 x 9
     HeartDisease Mean_Female_FAL~ Median_Female_F~ Mean_Male_FALSE
     <fct> <dbl> <dbl> <dbl>
    1 No 54.0 53.5 50.2
    2 Yes 59.7 61 55.8
    # ... with 5 more variables: Median_Male_FALSE <dbl>, Mean_Female_TRUE <dbl>,
    # Median_Female_TRUE <dbl>, Mean_Male_TRUE <dbl>, Median_Male_TRUE <dbl>
    >
    > #4) Clean HTML table with keys spanned over columns
    > result <-
    + temp_summary %>%
    + stretch(
    + keys = c("Sex", "BloodSugar"),
    + keep = "HeartDisease",
    + extract_keys_as_header = TRUE,
    + keep_keys_in_header = FALSE
    + )
    Error: Names must be unique.
    Backtrace:
     x
     1. \-`%>%`(...)
     2. +-base::withVisible(eval(quote(`_fseq`(`_lhs`)), env, env))
     3. \-base::eval(quote(`_fseq`(`_lhs`)), env, env)
     4. \-base::eval(quote(`_fseq`(`_lhs`)), env, env)
     5. \-`_fseq`(`_lhs`)
     6. \-magrittr::freduce(value, `_function_list`)
     7. +-base::withVisible(function_list[[k]](value))
     8. \-function_list[[k]](value)
     9. \-cheese::stretch(...)
     10. \-`%>%`(...)
     11. +-base::withVisible(eval(quote(`_fseq`(`_lhs`)), env, env))
     12. \-base::eval(quote(`_fseq`(`_lhs`)), env, env)
     13. \-base::eval(quote(`_fseq`(`_lhs`)), env, env)
     14. \-cheese:::`_fseq`(`_lhs`)
     15. \-magrittr::freduce(value, `_function_list`)
     16. +-base::withVisible(function_list[[k]](value))
     17. \-function_list[[k]](value)
     18.
    Execution halted
Flavor: r-devel-windows-ix86+x86_64-gcc8

Version: 0.0.2
Check: re-building of vignette outputs
Result: WARN
    Error(s) in re-building vignettes:
    --- re-building 'cheese.Rmd' using rmarkdown
    Quitting from lines 149-163 (cheese.Rmd)
    Error: processing vignette 'cheese.Rmd' failed with diagnostics:
    Names must be unique.
    --- failed re-building 'cheese.Rmd'
    
    SUMMARY: processing the following file failed:
     'cheese.Rmd'
    
    Error: Vignette re-building failed.
    Execution halted
Flavors: r-devel-windows-ix86+x86_64-gcc8, r-release-windows-ix86+x86_64

Version: 0.0.2
Check: examples
Result: ERROR
    Running examples in 'cheese-Ex.R' failed
    The error most likely occurred in:
    
    > ### Name: stretch
    > ### Title: Stretch one or variables over many columns by one or more keys
    > ### Aliases: stretch
    >
    > ### ** Examples
    >
    > require(tidyverse)
    Loading required package: tidyverse
    -- Attaching packages --------------------------------------- tidyverse 1.3.0 --
    v ggplot2 3.2.1 v purrr 0.3.3
    v tibble 2.1.3 v dplyr 0.8.4
    v tidyr 1.0.2 v stringr 1.4.0
    v readr 1.3.1 v forcats 0.4.0
    -- Conflicts ------------------------------------------ tidyverse_conflicts() --
    x dplyr::filter() masks stats::filter()
    x dplyr::lag() masks stats::lag()
    >
    > #Make data frame with multiple summary columns
    > temp_summary <-
    +
    + heart_disease %>%
    + group_by(
    + Sex,
    + HeartDisease,
    + BloodSugar
    + ) %>%
    + summarise(
    + Mean = mean(Age, na.rm = TRUE),
    + SD = sd(Age, na.rm = TRUE),
    + Median = median(Age, na.rm = TRUE)
    + ) %>%
    + ungroup()
    >
    > #1) Span summaries for each combination of Sex and BloodSugar
    > temp_summary %>%
    + stretch(
    + keys = c("Sex", "BloodSugar"),
    + keep = "HeartDisease"
    + )
    # A tibble: 2 x 13
     HeartDisease Mean_Female_FAL~ SD_Female_FALSE Median_Female_F~ Mean_Male_FALSE
     <fct> <dbl> <dbl> <dbl> <dbl>
    1 No 54.0 10.4 53.5 50.2
    2 Yes 59.7 3.61 61 55.8
    # ... with 8 more variables: SD_Male_FALSE <dbl>, Median_Male_FALSE <dbl>,
    # Mean_Female_TRUE <dbl>, SD_Female_TRUE <dbl>, Median_Female_TRUE <dbl>,
    # Mean_Male_TRUE <dbl>, SD_Male_TRUE <dbl>, Median_Male_TRUE <dbl>
    >
    > #2) If "HeartDisease" wasn't fully crossed, use different joining to get only matching groups
    > temp_summary %>%
    + stretch(
    + keys = c("Sex", "BloodSugar"),
    + keep = "HeartDisease",
    + join = inner_join
    + )
    # A tibble: 2 x 13
     HeartDisease Mean_Female_FAL~ SD_Female_FALSE Median_Female_F~ Mean_Male_FALSE
     <fct> <dbl> <dbl> <dbl> <dbl>
    1 No 54.0 10.4 53.5 50.2
    2 Yes 59.7 3.61 61 55.8
    # ... with 8 more variables: SD_Male_FALSE <dbl>, Median_Male_FALSE <dbl>,
    # Mean_Female_TRUE <dbl>, SD_Female_TRUE <dbl>, Median_Female_TRUE <dbl>,
    # Mean_Male_TRUE <dbl>, SD_Male_TRUE <dbl>, Median_Male_TRUE <dbl>
    >
    > #3) Only send two of the summaries
    > temp_summary %>%
    + stretch(
    + keys = c("Sex", "BloodSugar"),
    + keep = "HeartDisease",
    + send = c("Mean", "Median")
    + )
    # A tibble: 2 x 9
     HeartDisease Mean_Female_FAL~ Median_Female_F~ Mean_Male_FALSE
     <fct> <dbl> <dbl> <dbl>
    1 No 54.0 53.5 50.2
    2 Yes 59.7 61 55.8
    # ... with 5 more variables: Median_Male_FALSE <dbl>, Mean_Female_TRUE <dbl>,
    # Median_Female_TRUE <dbl>, Mean_Male_TRUE <dbl>, Median_Male_TRUE <dbl>
    >
    > #4) Clean HTML table with keys spanned over columns
    > result <-
    + temp_summary %>%
    + stretch(
    + keys = c("Sex", "BloodSugar"),
    + keep = "HeartDisease",
    + extract_keys_as_header = TRUE,
    + keep_keys_in_header = FALSE
    + )
    Error: Names must be unique.
    Backtrace:
     x
     1. \-`%>%`(...)
     2. +-base::withVisible(eval(quote(`_fseq`(`_lhs`)), env, env))
     3. \-base::eval(quote(`_fseq`(`_lhs`)), env, env)
     4. \-base::eval(quote(`_fseq`(`_lhs`)), env, env)
     5. \-`_fseq`(`_lhs`)
     6. \-magrittr::freduce(value, `_function_list`)
     7. +-base::withVisible(function_list[[k]](value))
     8. \-function_list[[k]](value)
     9. \-cheese::stretch(...)
     10. \-`%>%`(...)
     11. +-base::withVisible(eval(quote(`_fseq`(`_lhs`)), env, env))
     12. \-base::eval(quote(`_fseq`(`_lhs`)), env, env)
     13. \-base::eval(quote(`_fseq`(`_lhs`)), env, env)
     14. \-cheese:::`_fseq`(`_lhs`)
     15. \-magrittr::freduce(value, `_function_list`)
     16. +-base::withVisible(function_list[[k]](value))
     17. \-function_list[[k]](value)
     18.
    Execution halted
Flavor: r-release-windows-ix86+x86_64