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This pull request:
(Note that results may be inacurrate if you branched from an outdated version of the target branch.) |
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Thanks. Tagging @martinparies at Institut Louis Malarde, who may have some feedback. Can install from PR with |
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Complete output below devtools::test()
## ℹ Testing cleanepi
## ✔ | F W S OK | Context
## ⠏ | 0 | check_date_sequence Found the following unrecognised column name:
## `fake_name`! Detected 2 incorrect date sequences at lines: "6, 8".
## i Enter `attr(dat, "report")[["incorrect_date_sequence"]]` to access them, where "dat" is the object used to store the output from this operation.
## ⠹ | 3 | check_date_sequence Detected 2 incorrect date sequences at
## lines: `6, 8`Insufficient number of columns to compare.i Found the following unrecognised column name: fake_name.
## ! Detected 2 incorrect date sequences at lines: "6, 8".
## i Enter `attr(dat, "report")[["incorrect_date_sequence"]]` to access them, where "dat" is the object used to store the output from this operation.
## ✔ | 13 | check_date_sequence
## ⠏ | 0 | clean_data_helpers ! Found 50 <numeric> values that can also be of type <Date> in column case_id.
## ⠋ | 1 | clean_data_helpers i No character column found from the input data.
## ! Found 1 <numeric> value that can also be of type <Date> in column col1.
## ! Found 1 <numeric> value that can also be of type <Date> in column col1.
## ! Found 3 <numeric> values that can also be of type <Date> in column col.
## ✔ | 15 | clean_data_helpers [1.8s]
## ⠏ | 0 | clean_data i Cleaning column names
## i Removing constant columns and empty rows
## i Removing duplicated rows
## i No duplicates were found.
## ⠙ | 1 1 | clean_data i Cleaning column names
## i Replacing missing values with NA
## i Removing constant columns and empty rows
## i Removing duplicated rows
## ⠴ | 2 4 | clean_data i No duplicates were found.
## i Standardizing Date columns
## i Checking subject IDs format
## ! Detected incorrect subject ids at lines: "3, 5, 7".
## i You can use the `correct_subject_ids()` function to correct them.
## i Converting `sex` into numeric
## i Performing dictionary-based cleaning
## i Checking whether date sequences are respected
## ! Detected 2 incorrect date sequences at lines: "6, 8".
## i Enter `attr(dat, "report")[["incorrect_date_sequence"]]` to access them, where "dat" is the object used to store the output from this operation.
## ⠹ | 5 8 | clean_data i No duplicates were found.
## ! Detected incorrect subject ids at lines: "3, 5, 7".
## i You can use the `correct_subject_ids()` function to correct them.
## ⠼ | 6 9 | clean_data 'target_columns' must be provided.i Cleaning column names
## i Removing constant columns and empty rows
## i Removing duplicated rows
## i No duplicates were found.
## i Checking subject IDs format
## ✔ | 7 18 | clean_data
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Warning (test-clean_data.R:11:3): clean_data works as expected with the default parameters
## There was 1 warning in `dplyr::arrange()`.
## i In argument: `..1 = dplyr::pick(target_columns)`.
## Caused by warning:
## ! Using an external vector in selections was deprecated in tidyselect 1.1.0.
## i Please use `all_of()` or `any_of()` instead.
## # Was:
## data %>% select(target_columns)
##
## # Now:
## data %>% select(all_of(target_columns))
##
## See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## Backtrace:
## ▆
## 1. ├─cleanepi::clean_data(data = test_data) at test-clean_data.R:11:3
## 2. │ └─cleanepi::remove_duplicates(data, target_columns = params[["remove_duplicates"]][["target_columns"]]) at cleanepi/R/clean_data.R:189:5
## 3. │ └─cleanepi::find_duplicates(dat, target_columns) at cleanepi/R/find_and_remove_duplicates.R:39:3
## 4. │ └─... %>% ... at cleanepi/R/find_and_remove_duplicates.R:105:3
## 5. ├─dplyr::mutate(., group_id = dplyr::cur_group_id(), .after = "row_id")
## 6. ├─dplyr::group_by(., dplyr::across(dplyr::all_of(target_columns)))
## 7. ├─dplyr::arrange(., dplyr::pick(target_columns))
## 8. └─dplyr:::arrange.data.frame(., dplyr::pick(target_columns))
## 9. └─dplyr:::arrange_rows(.data, dots = dots, locale = .locale)
## 10. ├─dplyr::mutate(data, `:=`("{name}", !!dot), .keep = "none")
## 11. └─dplyr:::mutate.data.frame(data, `:=`("{name}", !!dot), .keep = "none")
## 12. └─dplyr:::mutate_cols(.data, dplyr_quosures(...), by)
## 13. └─dplyr:::signal_warnings(warnings_state, error_call)
##
## Warning (test-clean_data.R:54:3): clean_data works as expected
## There was 1 warning in `dplyr::arrange()`.
## i In argument: `..1 = dplyr::pick(target_columns)`.
## Caused by warning:
## ! Using an external vector in selections was deprecated in tidyselect 1.1.0.
## i Please use `all_of()` or `any_of()` instead.
## # Was:
## data %>% select(target_columns)
##
## # Now:
## data %>% select(all_of(target_columns))
##
## See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## Backtrace:
## ▆
## 1. ├─cleanepi::clean_data(...) at test-clean_data.R:54:3
## 2. │ └─cleanepi::remove_duplicates(data, target_columns = params[["remove_duplicates"]][["target_columns"]]) at cleanepi/R/clean_data.R:189:5
## 3. │ └─cleanepi::find_duplicates(dat, target_columns) at cleanepi/R/find_and_remove_duplicates.R:39:3
## 4. │ └─... %>% ... at cleanepi/R/find_and_remove_duplicates.R:105:3
## 5. ├─dplyr::mutate(., group_id = dplyr::cur_group_id(), .after = "row_id")
## 6. ├─dplyr::group_by(., dplyr::across(dplyr::all_of(target_columns)))
## 7. ├─dplyr::arrange(., dplyr::pick(target_columns))
## 8. └─dplyr:::arrange.data.frame(., dplyr::pick(target_columns))
## 9. └─dplyr:::arrange_rows(.data, dots = dots, locale = .locale)
## 10. ├─dplyr::mutate(data, `:=`("{name}", !!dot), .keep = "none")
## 11. └─dplyr:::mutate.data.frame(data, `:=`("{name}", !!dot), .keep = "none")
## 12. └─dplyr:::mutate_cols(.data, dplyr_quosures(...), by)
## 13. └─dplyr:::signal_warnings(warnings_state, error_call)
##
## Warning (test-clean_data.R:54:3): clean_data works as expected
## There was 1 warning in `dplyr::arrange()`.
## i In argument: `..1 = dplyr::pick(target_columns)`.
## Caused by warning:
## ! Using an external vector in selections was deprecated in tidyselect 1.1.0.
## i Please use `all_of()` or `any_of()` instead.
## # Was:
## data %>% select(target_columns)
##
## # Now:
## data %>% select(all_of(target_columns))
##
## See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## Backtrace:
## ▆
## 1. ├─cleanepi::clean_data(...) at test-clean_data.R:54:3
## 2. │ └─cleanepi::check_subject_ids(...) at cleanepi/R/clean_data.R:232:5
## 3. │ └─cleanepi:::check_subject_ids_oness(data, target_columns) at cleanepi/R/standardize_subject_ids.R:55:3
## 4. │ ├─base::suppressMessages(find_duplicates(data, id_col_name)) at cleanepi/R/standardize_subject_ids.R:195:3
## 5. │ │ └─base::withCallingHandlers(...)
## 6. │ └─cleanepi::find_duplicates(data, id_col_name)
## 7. │ └─... %>% ... at cleanepi/R/find_and_remove_duplicates.R:105:3
## 8. ├─dplyr::mutate(., group_id = dplyr::cur_group_id(), .after = "row_id")
## 9. ├─dplyr::group_by(., dplyr::across(dplyr::all_of(target_columns)))
## 10. ├─dplyr::arrange(., dplyr::pick(target_columns))
## 11. └─dplyr:::arrange.data.frame(., dplyr::pick(target_columns))
## 12. └─dplyr:::arrange_rows(.data, dots = dots, locale = .locale)
## 13. ├─dplyr::mutate(data, `:=`("{name}", !!dot), .keep = "none")
## 14. └─dplyr:::mutate.data.frame(data, `:=`("{name}", !!dot), .keep = "none")
## 15. └─dplyr:::mutate_cols(.data, dplyr_quosures(...), by)
## 16. └─dplyr:::signal_warnings(warnings_state, error_call)
##
## Warning (test-clean_data.R:53:1): clean_data works as expected
## Global state has changed:
## `before[[8]]` is length 111
## `after[[8]]` is length 112
## `names(before[[8]])[63:68]`: "pkgType" "printcmd" "prompt" "readr.show_progress" "repos" "rl_word_breaks"
## `names(after[[8]])[63:69]`: "pkgType" "printcmd" "prompt" "readr.default_locale" "readr.show_progress" "repos" "rl_word_breaks"
## `before[[8]]$readr.default_locale` is absent
## `after[[8]]$readr.default_locale` is an S3 object of class <locale>, a list
##
## Warning (test-clean_data.R:73:3): cleaned_data works in a pipable way
## There was 1 warning in `dplyr::arrange()`.
## i In argument: `..1 = dplyr::pick(target_columns)`.
## Caused by warning:
## ! Using an external vector in selections was deprecated in tidyselect 1.1.0.
## i Please use `all_of()` or `any_of()` instead.
## # Was:
## data %>% select(target_columns)
##
## # Now:
## data %>% select(all_of(target_columns))
##
## See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## Backtrace:
## ▆
## 1. ├─... %>% clean_using_dictionary(dictionary = test_dictionary) at test-clean_data.R:73:3
## 2. ├─cleanepi::clean_using_dictionary(., dictionary = test_dictionary)
## 3. │ └─checkmate::assert_data_frame(...) at cleanepi/R/dictionary_based_cleaning.R:38:3
## 4. │ └─checkmate::checkDataFrame(...)
## 5. │ └─... %and% checkListTypes(x, types)
## 6. │ └─base::isTRUE(lhs)
## 7. ├─cleanepi::convert_to_numeric(., target_columns = "sex", lang = "en") at cleanepi/R/dictionary_based_cleaning.R:38:3
## 8. │ └─checkmate::assert_data_frame(...) at cleanepi/R/convert_to_numeric.R:31:3
## 9. │ └─checkmate::checkDataFrame(...)
## 10. │ └─... %and% checkListTypes(x, types)
## 11. │ └─base::isTRUE(lhs)
## 12. ├─cleanepi::check_subject_ids(...) at cleanepi/R/convert_to_numeric.R:31:3
## 13. │ └─checkmate::assert_data_frame(data, null.ok = FALSE) at cleanepi/R/standardize_subject_ids.R:33:3
## 14. │ └─checkmate::checkDataFrame(...)
## 15. │ └─... %and% checkListTypes(x, types)
## 16. │ └─base::isTRUE(lhs)
## 17. ├─cleanepi::standardize_dates(...) at cleanepi/R/standardize_subject_ids.R:33:3
## 18. │ └─checkmate::assert_data_frame(data, null.ok = FALSE, min.cols = 1L) at cleanepi/R/standardize_date.R:115:3
## 19. │ └─checkmate::checkDataFrame(...)
## 20. │ └─... %and% checkListTypes(x, types)
## 21. │ └─base::isTRUE(lhs)
## 22. ├─cleanepi::remove_duplicates(., target_columns = NULL) at cleanepi/R/standardize_date.R:115:3
## 23. │ └─cleanepi::find_duplicates(dat, target_columns) at cleanepi/R/find_and_remove_duplicates.R:39:3
## 24. │ └─... %>% ... at cleanepi/R/find_and_remove_duplicates.R:105:3
## 25. ├─dplyr::mutate(., group_id = dplyr::cur_group_id(), .after = "row_id")
## 26. ├─dplyr::group_by(., dplyr::across(dplyr::all_of(target_columns)))
## 27. ├─dplyr::arrange(., dplyr::pick(target_columns))
## 28. └─dplyr:::arrange.data.frame(., dplyr::pick(target_columns))
## 29. └─dplyr:::arrange_rows(.data, dots = dots, locale = .locale)
## 30. ├─dplyr::mutate(data, `:=`("{name}", !!dot), .keep = "none")
## 31. └─dplyr:::mutate.data.frame(data, `:=`("{name}", !!dot), .keep = "none")
## 32. └─dplyr:::mutate_cols(.data, dplyr_quosures(...), by)
## 33. └─dplyr:::signal_warnings(warnings_state, error_call)
##
## Warning (test-clean_data.R:73:3): cleaned_data works in a pipable way
## There was 1 warning in `dplyr::arrange()`.
## i In argument: `..1 = dplyr::pick(target_columns)`.
## Caused by warning:
## ! Using an external vector in selections was deprecated in tidyselect 1.1.0.
## i Please use `all_of()` or `any_of()` instead.
## # Was:
## data %>% select(target_columns)
##
## # Now:
## data %>% select(all_of(target_columns))
##
## See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## Backtrace:
## ▆
## 1. ├─... %>% clean_using_dictionary(dictionary = test_dictionary) at test-clean_data.R:73:3
## 2. ├─cleanepi::clean_using_dictionary(., dictionary = test_dictionary)
## 3. │ └─checkmate::assert_data_frame(...) at cleanepi/R/dictionary_based_cleaning.R:38:3
## 4. │ └─checkmate::checkDataFrame(...)
## 5. │ └─... %and% checkListTypes(x, types)
## 6. │ └─base::isTRUE(lhs)
## 7. ├─cleanepi::convert_to_numeric(., target_columns = "sex", lang = "en") at cleanepi/R/dictionary_based_cleaning.R:38:3
## 8. │ └─checkmate::assert_data_frame(...) at cleanepi/R/convert_to_numeric.R:31:3
## 9. │ └─checkmate::checkDataFrame(...)
## 10. │ └─... %and% checkListTypes(x, types)
## 11. │ └─base::isTRUE(lhs)
## 12. ├─cleanepi::check_subject_ids(...) at cleanepi/R/convert_to_numeric.R:31:3
## 13. │ └─cleanepi:::check_subject_ids_oness(data, target_columns) at cleanepi/R/standardize_subject_ids.R:55:3
## 14. │ ├─base::suppressMessages(find_duplicates(data, id_col_name)) at cleanepi/R/standardize_subject_ids.R:195:3
## 15. │ │ └─base::withCallingHandlers(...)
## 16. │ └─cleanepi::find_duplicates(data, id_col_name) at cleanepi/R/standardize_subject_ids.R:195:3
## 17. │ └─... %>% ... at cleanepi/R/find_and_remove_duplicates.R:105:3
## 18. ├─dplyr::mutate(., group_id = dplyr::cur_group_id(), .after = "row_id")
## 19. ├─dplyr::group_by(., dplyr::across(dplyr::all_of(target_columns)))
## 20. ├─dplyr::arrange(., dplyr::pick(target_columns))
## 21. └─dplyr:::arrange.data.frame(., dplyr::pick(target_columns))
## 22. └─dplyr:::arrange_rows(.data, dots = dots, locale = .locale)
## 23. ├─dplyr::mutate(data, `:=`("{name}", !!dot), .keep = "none")
## 24. └─dplyr:::mutate.data.frame(data, `:=`("{name}", !!dot), .keep = "none")
## 25. └─dplyr:::mutate_cols(.data, dplyr_quosures(...), by)
## 26. └─dplyr:::signal_warnings(warnings_state, error_call)
##
## Warning (test-clean_data.R:119:3): clean_data fails as expected
## There was 1 warning in `dplyr::arrange()`.
## i In argument: `..1 = dplyr::pick(target_columns)`.
## Caused by warning:
## ! Using an external vector in selections was deprecated in tidyselect 1.1.0.
## i Please use `all_of()` or `any_of()` instead.
## # Was:
## data %>% select(target_columns)
##
## # Now:
## data %>% select(all_of(target_columns))
##
## See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## Backtrace:
## ▆
## 1. ├─testthat::expect_error(...) at test-clean_data.R:119:3
## 2. │ └─testthat:::expect_condition_matching(...)
## 3. │ └─testthat:::quasi_capture(...)
## 4. │ ├─testthat (local) .capture(...)
## 5. │ │ └─base::withCallingHandlers(...)
## 6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
## 7. ├─cleanepi::clean_data(data = test_data, standardize_subject_ids = standardize_subject_ids)
## 8. │ └─cleanepi::remove_duplicates(data, target_columns = params[["remove_duplicates"]][["target_columns"]]) at cleanepi/R/clean_data.R:189:5
## 9. │ └─cleanepi::find_duplicates(dat, target_columns) at cleanepi/R/find_and_remove_duplicates.R:39:3
## 10. │ └─... %>% ... at cleanepi/R/find_and_remove_duplicates.R:105:3
## 11. ├─dplyr::mutate(., group_id = dplyr::cur_group_id(), .after = "row_id")
## 12. ├─dplyr::group_by(., dplyr::across(dplyr::all_of(target_columns)))
## 13. ├─dplyr::arrange(., dplyr::pick(target_columns))
## 14. └─dplyr:::arrange.data.frame(., dplyr::pick(target_columns))
## 15. └─dplyr:::arrange_rows(.data, dots = dots, locale = .locale)
## 16. ├─dplyr::mutate(data, `:=`("{name}", !!dot), .keep = "none")
## 17. └─dplyr:::mutate.data.frame(data, `:=`("{name}", !!dot), .keep = "none")
## 18. └─dplyr:::mutate_cols(.data, dplyr_quosures(...), by)
## 19. └─dplyr:::signal_warnings(warnings_state, error_call)
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## ⠏ | 0 | column_name_standardization Replace column names already existsAssertion on',keep,'failed: usage of 'linelist_tags'
## is only reserved for 'linelist' type of data.Assertion on',keep or rename,'failed: Only the
## column names from the input data can be renamed or
## ✔ | 14 | column_name_standardization
## ⠏ | 0 | convert_numeric_to_date ✔ | 12 | convert_numeric_to_dateke_column_name' not found.
## ⠋ | 1 | convert_to_numeric ! Found 50 <numeric> values that can also be of type <Date> in column case_id.
## ! Found 685.5 numeric values in gender.
## i Please consider the followings:
## * converting characters into numeric, or
## * replacing the numeric values by "NA" using the `replace_missing_values()` function.
## i The following colonne will be converted into numeric: age.
## ⠹ | 3 | convert_to_numeric Found `3750` numeric values in `test`. Consider
## converting characters into numeric or replacing the
## numeric values by `NA` using the
## `replace_missing_values()` function.! Found 685.5 numeric values in gender.
## i Please consider the followings:
## * converting characters into numeric, or
## * replacing the numeric values by "NA" using the `replace_missing_values()` function.
## i The following colonne will be converted into numeric: age.
## ⠼ | 5 | convert_to_numeric ! Found 50 <numeric> values that can also be of type <Date> in column case_id.
## ! Found 685.5 numeric values in gender.
## i Please consider the followings:
## * converting characters into numeric, or
## * replacing the numeric values by "NA" using the `replace_missing_values()` function.
## i The following colonne will be converted into numeric: age.
## ⠇ | 9 | convert_to_numeric Found `3750` numeric values in `test`. Consider
## converting characters into numeric or replacing the
## numeric values by `NA` using the
## `replace_missing_values()` function.i The following colonne will be converted into numeric: age.
## target_columns not specified and could not be
## ✔ | 12 | convert_to_numeric [7.0s] scan_data() function.
## ✔ | 1 | dev-utils
## ⠏ | 0 | dictionary_based_cleaning ! Can not replace the following values found in column gender but not defined in the dictionary: "femme".
## i You can either:
## * correct the misspelled options from the input data, or
## * add them to the dictionary using the `add_to_dictionary()` function.
## ⠹ | 23 | dictionary_based_cleaning Can not replace the following values found in column `gender` but not defined in the dictionary: `femme`.i You can either:
## * correct the misspelled options from the input data, or
## * add them to the dictionary using the `add_to_dictionary()` function.
## ✔ | 35 | dictionary_based_cleaninge'
## ⠏ | 0 | find_and_remove_duplicates ! Found 57 duplicated rows in the dataset.
## i Use `attr(dat, "report")[["duplicated_rows"]]` to access them, where "dat" is the object used to store the output from this operation.
## ⠙ | 1 11 | find_and_remove_duplicates ! Found 57 duplicated rows in the dataset.
## i Use `attr(dat, "report")[["duplicated_rows"]]` to access them, where "dat" is the object used to store the output from this operation.
## ⠼ | 3 22 | find_and_remove_duplicates ! Found 57 duplicated rows in the dataset.
## i Use `attr(dat, "report")[["duplicated_rows"]]` to access them, where "dat" is the object used to store the output from this operation.
## ! Found 57 duplicated rows in the dataset.
## i Use `attr(dat, "report")[["duplicated_rows"]]` to access them, where "dat" is the object used to store the output from this operation.
## ⠦ | 5 32 | find_and_remove_duplicates i No duplicates were found.
## ✔ | 6 34 | find_and_remove_duplicates
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Warning (test-find_and_remove_duplicates.R:6:3): remove_duplicates works with 'linelist_tags'
## There was 1 warning in `dplyr::arrange()`.
## i In argument: `..1 = dplyr::pick(target_columns)`.
## Caused by warning:
## ! Using an external vector in selections was deprecated in tidyselect 1.1.0.
## i Please use `all_of()` or `any_of()` instead.
## # Was:
## data %>% select(target_columns)
##
## # Now:
## data %>% select(all_of(target_columns))
##
## See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## Backtrace:
## ▆
## 1. ├─cleanepi::remove_duplicates(data = data, target_columns = "linelist_tags") at test-find_and_remove_duplicates.R:6:3
## 2. │ └─cleanepi::find_duplicates(dat, target_columns) at cleanepi/R/find_and_remove_duplicates.R:39:3
## 3. │ └─... %>% ... at cleanepi/R/find_and_remove_duplicates.R:105:3
## 4. ├─dplyr::mutate(., group_id = dplyr::cur_group_id(), .after = "row_id")
## 5. ├─dplyr::group_by(., dplyr::across(dplyr::all_of(target_columns)))
## 6. ├─dplyr::arrange(., dplyr::pick(target_columns))
## 7. └─dplyr:::arrange.data.frame(., dplyr::pick(target_columns))
## 8. └─dplyr:::arrange_rows(.data, dots = dots, locale = .locale)
## 9. ├─dplyr::mutate(data, `:=`("{name}", !!dot), .keep = "none")
## 10. └─dplyr:::mutate.data.frame(data, `:=`("{name}", !!dot), .keep = "none")
## 11. └─dplyr:::mutate_cols(.data, dplyr_quosures(...), by)
## 12. └─dplyr:::signal_warnings(warnings_state, error_call)
##
## Warning (test-find_and_remove_duplicates.R:28:3): remove_duplicates works with 'linelist_tags'
## There was 1 warning in `dplyr::arrange()`.
## i In argument: `..1 = dplyr::pick(target_columns)`.
## Caused by warning:
## ! Using an external vector in selections was deprecated in tidyselect 1.1.0.
## i Please use `all_of()` or `any_of()` instead.
## # Was:
## data %>% select(target_columns)
##
## # Now:
## data %>% select(all_of(target_columns))
##
## See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## Backtrace:
## ▆
## 1. ├─cleanepi::remove_duplicates(...) at test-find_and_remove_duplicates.R:28:3
## 2. │ └─cleanepi::find_duplicates(dat, target_columns) at cleanepi/R/find_and_remove_duplicates.R:39:3
## 3. │ └─... %>% ... at cleanepi/R/find_and_remove_duplicates.R:105:3
## 4. ├─dplyr::mutate(., group_id = dplyr::cur_group_id(), .after = "row_id")
## 5. ├─dplyr::group_by(., dplyr::across(dplyr::all_of(target_columns)))
## 6. ├─dplyr::arrange(., dplyr::pick(target_columns))
## 7. └─dplyr:::arrange.data.frame(., dplyr::pick(target_columns))
## 8. └─dplyr:::arrange_rows(.data, dots = dots, locale = .locale)
## 9. ├─dplyr::mutate(data, `:=`("{name}", !!dot), .keep = "none")
## 10. └─dplyr:::mutate.data.frame(data, `:=`("{name}", !!dot), .keep = "none")
## 11. └─dplyr:::mutate_cols(.data, dplyr_quosures(...), by)
## 12. └─dplyr:::signal_warnings(warnings_state, error_call)
##
## Warning (test-find_and_remove_duplicates.R:50:3): find_duplicates works with a vector of column names
## There was 1 warning in `dplyr::arrange()`.
## i In argument: `..1 = dplyr::pick(target_columns)`.
## Caused by warning:
## ! Using an external vector in selections was deprecated in tidyselect 1.1.0.
## i Please use `all_of()` or `any_of()` instead.
## # Was:
## data %>% select(target_columns)
##
## # Now:
## data %>% select(all_of(target_columns))
##
## See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## Backtrace:
## ▆
## 1. ├─cleanepi::find_duplicates(...) at test-find_and_remove_duplicates.R:50:3
## 2. │ └─... %>% ... at cleanepi/R/find_and_remove_duplicates.R:105:3
## 3. ├─dplyr::mutate(., group_id = dplyr::cur_group_id(), .after = "row_id")
## 4. ├─dplyr::group_by(., dplyr::across(dplyr::all_of(target_columns)))
## 5. ├─dplyr::arrange(., dplyr::pick(target_columns))
## 6. └─dplyr:::arrange.data.frame(., dplyr::pick(target_columns))
## 7. └─dplyr:::arrange_rows(.data, dots = dots, locale = .locale)
## 8. ├─dplyr::mutate(data, `:=`("{name}", !!dot), .keep = "none")
## 9. └─dplyr:::mutate.data.frame(data, `:=`("{name}", !!dot), .keep = "none")
## 10. └─dplyr:::mutate_cols(.data, dplyr_quosures(...), by)
## 11. └─dplyr:::signal_warnings(warnings_state, error_call)
##
## Warning (test-find_and_remove_duplicates.R:64:3): find_duplicates works with 'linelist_tags'
## There was 1 warning in `dplyr::arrange()`.
## i In argument: `..1 = dplyr::pick(target_columns)`.
## Caused by warning:
## ! Using an external vector in selections was deprecated in tidyselect 1.1.0.
## i Please use `all_of()` or `any_of()` instead.
## # Was:
## data %>% select(target_columns)
##
## # Now:
## data %>% select(all_of(target_columns))
##
## See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## Backtrace:
## ▆
## 1. ├─cleanepi::find_duplicates(data = data, target_columns = "linelist_tags") at test-find_and_remove_duplicates.R:64:3
## 2. │ └─... %>% ... at cleanepi/R/find_and_remove_duplicates.R:105:3
## 3. ├─dplyr::mutate(., group_id = dplyr::cur_group_id(), .after = "row_id")
## 4. ├─dplyr::group_by(., dplyr::across(dplyr::all_of(target_columns)))
## 5. ├─dplyr::arrange(., dplyr::pick(target_columns))
## 6. └─dplyr:::arrange.data.frame(., dplyr::pick(target_columns))
## 7. └─dplyr:::arrange_rows(.data, dots = dots, locale = .locale)
## 8. ├─dplyr::mutate(data, `:=`("{name}", !!dot), .keep = "none")
## 9. └─dplyr:::mutate.data.frame(data, `:=`("{name}", !!dot), .keep = "none")
## 10. └─dplyr:::mutate_cols(.data, dplyr_quosures(...), by)
## 11. └─dplyr:::signal_warnings(warnings_state, error_call)
##
## Warning (test-find_and_remove_duplicates.R:78:3): find_duplicates works when target_columns = NULL
## There was 1 warning in `dplyr::arrange()`.
## i In argument: `..1 = dplyr::pick(target_columns)`.
## Caused by warning:
## ! Using an external vector in selections was deprecated in tidyselect 1.1.0.
## i Please use `all_of()` or `any_of()` instead.
## # Was:
## data %>% select(target_columns)
##
## # Now:
## data %>% select(all_of(target_columns))
##
## See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## Backtrace:
## ▆
## 1. ├─cleanepi::find_duplicates(data = data, target_columns = NULL) at test-find_and_remove_duplicates.R:78:3
## 2. │ └─... %>% ... at cleanepi/R/find_and_remove_duplicates.R:105:3
## 3. ├─dplyr::mutate(., group_id = dplyr::cur_group_id(), .after = "row_id")
## 4. ├─dplyr::group_by(., dplyr::across(dplyr::all_of(target_columns)))
## 5. ├─dplyr::arrange(., dplyr::pick(target_columns))
## 6. └─dplyr:::arrange.data.frame(., dplyr::pick(target_columns))
## 7. └─dplyr:::arrange_rows(.data, dots = dots, locale = .locale)
## 8. ├─dplyr::mutate(data, `:=`("{name}", !!dot), .keep = "none")
## 9. └─dplyr:::mutate.data.frame(data, `:=`("{name}", !!dot), .keep = "none")
## 10. └─dplyr:::mutate_cols(.data, dplyr_quosures(...), by)
## 11. └─dplyr:::signal_warnings(warnings_state, error_call)
##
## Warning (test-find_and_remove_duplicates.R:87:3): find_duplicates sends a messages when duplicates are found
## There was 1 warning in `dplyr::arrange()`.
## i In argument: `..1 = dplyr::pick(target_columns)`.
## Caused by warning:
## ! Using an external vector in selections was deprecated in tidyselect 1.1.0.
## i Please use `all_of()` or `any_of()` instead.
## # Was:
## data %>% select(target_columns)
##
## # Now:
## data %>% select(all_of(target_columns))
##
## See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## Backtrace:
## ▆
## 1. ├─testthat::expect_message(...) at test-find_and_remove_duplicates.R:87:3
## 2. │ └─testthat:::expect_condition_matching(...)
## 3. │ └─testthat:::quasi_capture(...)
## 4. │ ├─testthat (local) .capture(...)
## 5. │ │ └─base::withCallingHandlers(...)
## 6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
## 7. ├─cleanepi::find_duplicates(data = data, target_columns = "linelist_tags")
## 8. │ └─... %>% ... at cleanepi/R/find_and_remove_duplicates.R:105:3
## 9. ├─dplyr::mutate(., group_id = dplyr::cur_group_id(), .after = "row_id")
## 10. ├─dplyr::group_by(., dplyr::across(dplyr::all_of(target_columns)))
## 11. ├─dplyr::arrange(., dplyr::pick(target_columns))
## 12. └─dplyr:::arrange.data.frame(., dplyr::pick(target_columns))
## 13. └─dplyr:::arrange_rows(.data, dots = dots, locale = .locale)
## 14. ├─dplyr::mutate(data, `:=`("{name}", !!dot), .keep = "none")
## 15. └─dplyr:::mutate.data.frame(data, `:=`("{name}", !!dot), .keep = "none")
## 16. └─dplyr:::mutate_cols(.data, dplyr_quosures(...), by)
## 17. └─dplyr:::signal_warnings(warnings_state, error_call)
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## ⠏ | 0 | print_report ℹ No duplicates were found.
## ! Detected incorrect subject ids at lines: "3, 5, 7".
## ℹ You can use the `correct_subject_ids()` function to correct them.
## i Generating html report in '/tmp/RtmpDkZJkD'.
## Could not determine mime type for `/home/bahadzie/R/aarch64-unknown-linux-gnu-library/4.1/reactR/www/react-tools/react-tools.umd.cjs'
## ⠋ | 1 0 | print_report ⠙ | 1 1 | print_report ✖ | 1 2 | print_report
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Error (test-print_report.R:45:3): print_report works
## Error: pandoc document conversion failed with error 63
## Backtrace:
## ▆
## 1. └─cleanepi::print_report(...) at test-print_report.R:45:3
## 2. └─rmarkdown::render(...) at cleanepi/R/print_report.R:114:3
## 3. └─rmarkdown (local) convert(output_file, run_citeproc)
## 4. └─rmarkdown (local) convert_it(output)
## 5. └─rmarkdown (local) convert_fun(...)
## 6. └─rmarkdown:::stop2(...)
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## ⠏ | 0 | remove_constants ! Constant data was removed after 2 iterations.
## i Enter `attr(dat, "report")[["constant_data"]]` for more information, where "dat" represents the object used to store the output from `remove_constants()`.
## ✔ | 43 | remove_constants iterations.
## ⠏ | 0 | replace_missing_values ✔ | 10 | replace_missing_valuesalue character.
## ⠏ | 0 | span ✔ | 37 | span
## ⠏ | 0 | standardize_date i Target columns will be standardized using the following format: "%d/%m/%Y".
## i Target columns will be standardized using the following format: "%d/%m/%Y".
## Need to specify one format if all target columns have the
## ✔ | 24 | standardize_date
## ⠏ | 0 | standardize_subject_ids ! Detected incorrect subject ids at lines: "3, 5, 7".
## i You can use the `correct_subject_ids()` function to correct them.
## ⠴ | 2 4 | standardize_subject_ids Assertion on',data,'failed: input data frame must be
## provided.Assertion on',id_column_name,'failed: Missing value not
## allowed for 'id_column_name'.Assertion on',id_column_name,'failed: Must be a character of
## length 1.Assertion on',nchar,'failed: template sample IDs format
## must be provided.Found 2 duplicated rows in the subject IDs.! Detected incorrect subject ids at lines: "3, 5, 7".
## i You can use the `correct_subject_ids()` function to correct them.
## ⠸ | 4 10 | standardize_subject_ids ! Detected incorrect subject ids at lines: "3, 5, 7".
## i You can use the `correct_subject_ids()` function to correct them.
## ⠏ | 6 14 | standardize_subject_ids ! Detected incorrect subject ids at lines: "3".
## i You can use the `correct_subject_ids()` function to correct them.
## ! Detected incorrect subject ids at lines: "3, 7".
## i You can use the `correct_subject_ids()` function to correct them.
## ⠇ | 8 21 | standardize_subject_ids ! Detected incorrect subject ids at lines: "3, 5, 7".
## i You can use the `correct_subject_ids()` function to correct them.
## ! Detected incorrect subject ids at lines: "3, 5, 7".
## i You can use the `correct_subject_ids()` function to correct them.
## ⠴ | 10 26 | standardize_subject_ids All subject ids in the correction table should be part of the
## subject ids column of the input data.Column in 'correction_table' must be named as 'from' and
## 'to'Missing values found in study_id column at in lines: 7! Detected incorrect subject ids at lines: "3, 5, 7".
## i You can use the `correct_subject_ids()` function to correct them.
## ⠏ | 12 38 | standardize_subject_ids ! Detected incorrect subject ids at lines: "3, 5, 7".
## i You can use the `correct_subject_ids()` function to correct them.
## ✔ | 12 45 | standardize_subject_ids
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Warning (test-standardize_subject_ids.R:5:13): check_subject_ids works as expected when all parameters are
## provided
## There was 1 warning in `dplyr::arrange()`.
## i In argument: `..1 = dplyr::pick(target_columns)`.
## Caused by warning:
## ! Using an external vector in selections was deprecated in tidyselect 1.1.0.
## i Please use `all_of()` or `any_of()` instead.
## # Was:
## data %>% select(target_columns)
##
## # Now:
## data %>% select(all_of(target_columns))
##
## See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## Backtrace:
## ▆
## 1. ├─cleanepi::check_subject_ids(...) at test-standardize_subject_ids.R:5:13
## 2. │ └─cleanepi:::check_subject_ids_oness(data, target_columns) at cleanepi/R/standardize_subject_ids.R:55:3
## 3. │ ├─base::suppressMessages(find_duplicates(data, id_col_name)) at cleanepi/R/standardize_subject_ids.R:195:3
## 4. │ │ └─base::withCallingHandlers(...)
## 5. │ └─cleanepi::find_duplicates(data, id_col_name) at cleanepi/R/standardize_subject_ids.R:195:3
## 6. │ └─... %>% ... at cleanepi/R/find_and_remove_duplicates.R:105:3
## 7. ├─dplyr::mutate(., group_id = dplyr::cur_group_id(), .after = "row_id")
## 8. ├─dplyr::group_by(., dplyr::across(dplyr::all_of(target_columns)))
## 9. ├─dplyr::arrange(., dplyr::pick(target_columns))
## 10. └─dplyr:::arrange.data.frame(., dplyr::pick(target_columns))
## 11. └─dplyr:::arrange_rows(.data, dots = dots, locale = .locale)
## 12. ├─dplyr::mutate(data, `:=`("{name}", !!dot), .keep = "none")
## 13. └─dplyr:::mutate.data.frame(data, `:=`("{name}", !!dot), .keep = "none")
## 14. └─dplyr:::mutate_cols(.data, dplyr_quosures(...), by)
## 15. └─dplyr:::signal_warnings(warnings_state, error_call)
##
## Warning (test-standardize_subject_ids.R:21:3): check_subject_ids fails as expected
## There was 1 warning in `dplyr::arrange()`.
## i In argument: `..1 = dplyr::pick(target_columns)`.
## Caused by warning:
## ! Using an external vector in selections was deprecated in tidyselect 1.1.0.
## i Please use `all_of()` or `any_of()` instead.
## # Was:
## data %>% select(target_columns)
##
## # Now:
## data %>% select(all_of(target_columns))
##
## See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## Backtrace:
## ▆
## 1. ├─testthat::expect_message(...) at test-standardize_subject_ids.R:21:3
## 2. │ └─testthat:::expect_condition_matching(...)
## 3. │ └─testthat:::quasi_capture(...)
## 4. │ ├─testthat (local) .capture(...)
## 5. │ │ └─base::withCallingHandlers(...)
## 6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
## 7. ├─cleanepi::check_subject_ids(...)
## 8. │ └─cleanepi:::check_subject_ids_oness(data, target_columns) at cleanepi/R/standardize_subject_ids.R:55:3
## 9. │ ├─base::suppressMessages(find_duplicates(data, id_col_name)) at cleanepi/R/standardize_subject_ids.R:195:3
## 10. │ │ └─base::withCallingHandlers(...)
## 11. │ └─cleanepi::find_duplicates(data, id_col_name) at cleanepi/R/standardize_subject_ids.R:195:3
## 12. │ └─... %>% ... at cleanepi/R/find_and_remove_duplicates.R:105:3
## 13. ├─dplyr::mutate(., group_id = dplyr::cur_group_id(), .after = "row_id")
## 14. ├─dplyr::group_by(., dplyr::across(dplyr::all_of(target_columns)))
## 15. ├─dplyr::arrange(., dplyr::pick(target_columns))
## 16. └─dplyr:::arrange.data.frame(., dplyr::pick(target_columns))
## 17. └─dplyr:::arrange_rows(.data, dots = dots, locale = .locale)
## 18. ├─dplyr::mutate(data, `:=`("{name}", !!dot), .keep = "none")
## 19. └─dplyr:::mutate.data.frame(data, `:=`("{name}", !!dot), .keep = "none")
## 20. └─dplyr:::mutate_cols(.data, dplyr_quosures(...), by)
## 21. └─dplyr:::signal_warnings(warnings_state, error_call)
##
## Warning (test-standardize_subject_ids.R:94:3): check_subject_ids sends a message when duplicated IDs are found
## There was 1 warning in `dplyr::arrange()`.
## i In argument: `..1 = dplyr::pick(target_columns)`.
## Caused by warning:
## ! Using an external vector in selections was deprecated in tidyselect 1.1.0.
## i Please use `all_of()` or `any_of()` instead.
## # Was:
## data %>% select(target_columns)
##
## # Now:
## data %>% select(all_of(target_columns))
##
## See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## Backtrace:
## ▆
## 1. ├─testthat::expect_message(...) at test-standardize_subject_ids.R:94:3
## 2. │ └─testthat:::expect_condition_matching(...)
## 3. │ └─testthat:::quasi_capture(...)
## 4. │ ├─testthat (local) .capture(...)
## 5. │ │ └─base::withCallingHandlers(...)
## 6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
## 7. ├─cleanepi::check_subject_ids(...)
## 8. │ └─cleanepi:::check_subject_ids_oness(data, target_columns) at cleanepi/R/standardize_subject_ids.R:55:3
## 9. │ ├─base::suppressMessages(find_duplicates(data, id_col_name)) at cleanepi/R/standardize_subject_ids.R:195:3
## 10. │ │ └─base::withCallingHandlers(...)
## 11. │ └─cleanepi::find_duplicates(data, id_col_name) at cleanepi/R/standardize_subject_ids.R:195:3
## 12. │ └─... %>% ... at cleanepi/R/find_and_remove_duplicates.R:105:3
## 13. ├─dplyr::mutate(., group_id = dplyr::cur_group_id(), .after = "row_id")
## 14. ├─dplyr::group_by(., dplyr::across(dplyr::all_of(target_columns)))
## 15. ├─dplyr::arrange(., dplyr::pick(target_columns))
## 16. └─dplyr:::arrange.data.frame(., dplyr::pick(target_columns))
## 17. └─dplyr:::arrange_rows(.data, dots = dots, locale = .locale)
## 18. ├─dplyr::mutate(data, `:=`("{name}", !!dot), .keep = "none")
## 19. └─dplyr:::mutate.data.frame(data, `:=`("{name}", !!dot), .keep = "none")
## 20. └─dplyr:::mutate_cols(.data, dplyr_quosures(...), by)
## 21. └─dplyr:::signal_warnings(warnings_state, error_call)
##
## Warning (test-standardize_subject_ids.R:106:3): check_subject_ids sends a message when duplicated IDs are found
## There was 1 warning in `dplyr::arrange()`.
## i In argument: `..1 = dplyr::pick(target_columns)`.
## Caused by warning:
## ! Using an external vector in selections was deprecated in tidyselect 1.1.0.
## i Please use `all_of()` or `any_of()` instead.
## # Was:
## data %>% select(target_columns)
##
## # Now:
## data %>% select(all_of(target_columns))
##
## See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## Backtrace:
## ▆
## 1. ├─testthat::expect_message(...) at test-standardize_subject_ids.R:106:3
## 2. │ └─testthat:::expect_condition_matching(...)
## 3. │ └─testthat:::quasi_capture(...)
## 4. │ ├─testthat (local) .capture(...)
## 5. │ │ └─base::withCallingHandlers(...)
## 6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
## 7. ├─cleanepi::check_subject_ids(...)
## 8. │ └─cleanepi:::check_subject_ids_oness(data, target_columns) at cleanepi/R/standardize_subject_ids.R:55:3
## 9. │ ├─base::suppressMessages(find_duplicates(data, id_col_name)) at cleanepi/R/standardize_subject_ids.R:195:3
## 10. │ │ └─base::withCallingHandlers(...)
## 11. │ └─cleanepi::find_duplicates(data, id_col_name) at cleanepi/R/standardize_subject_ids.R:195:3
## 12. │ └─... %>% ... at cleanepi/R/find_and_remove_duplicates.R:105:3
## 13. ├─dplyr::mutate(., group_id = dplyr::cur_group_id(), .after = "row_id")
## 14. ├─dplyr::group_by(., dplyr::across(dplyr::all_of(target_columns)))
## 15. ├─dplyr::arrange(., dplyr::pick(target_columns))
## 16. └─dplyr:::arrange.data.frame(., dplyr::pick(target_columns))
## 17. └─dplyr:::arrange_rows(.data, dots = dots, locale = .locale)
## 18. ├─dplyr::mutate(data, `:=`("{name}", !!dot), .keep = "none")
## 19. └─dplyr:::mutate.data.frame(data, `:=`("{name}", !!dot), .keep = "none")
## 20. └─dplyr:::mutate_cols(.data, dplyr_quosures(...), by)
## 21. └─dplyr:::signal_warnings(warnings_state, error_call)
##
## Warning (test-standardize_subject_ids.R:122:3): check_subject_ids when the id column is numeric
## There was 1 warning in `dplyr::arrange()`.
## i In argument: `..1 = dplyr::pick(target_columns)`.
## Caused by warning:
## ! Using an external vector in selections was deprecated in tidyselect 1.1.0.
## i Please use `all_of()` or `any_of()` instead.
## # Was:
## data %>% select(target_columns)
##
## # Now:
## data %>% select(all_of(target_columns))
##
## See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## Backtrace:
## ▆
## 1. ├─cleanepi::check_subject_ids(data = data, target_columns = "case_id") at test-standardize_subject_ids.R:122:3
## 2. │ └─cleanepi:::check_subject_ids_oness(data, target_columns) at cleanepi/R/standardize_subject_ids.R:55:3
## 3. │ ├─base::suppressMessages(find_duplicates(data, id_col_name)) at cleanepi/R/standardize_subject_ids.R:195:3
## 4. │ │ └─base::withCallingHandlers(...)
## 5. │ └─cleanepi::find_duplicates(data, id_col_name) at cleanepi/R/standardize_subject_ids.R:195:3
## 6. │ └─... %>% ... at cleanepi/R/find_and_remove_duplicates.R:105:3
## 7. ├─dplyr::mutate(., group_id = dplyr::cur_group_id(), .after = "row_id")
## 8. ├─dplyr::group_by(., dplyr::across(dplyr::all_of(target_columns)))
## 9. ├─dplyr::arrange(., dplyr::pick(target_columns))
## 10. └─dplyr:::arrange.data.frame(., dplyr::pick(target_columns))
## 11. └─dplyr:::arrange_rows(.data, dots = dots, locale = .locale)
## 12. ├─dplyr::mutate(data, `:=`("{name}", !!dot), .keep = "none")
## 13. └─dplyr:::mutate.data.frame(data, `:=`("{name}", !!dot), .keep = "none")
## 14. └─dplyr:::mutate_cols(.data, dplyr_quosures(...), by)
## 15. └─dplyr:::signal_warnings(warnings_state, error_call)
##
## Warning (test-standardize_subject_ids.R:131:3): check_subject_ids works when relying on the nchar argument
## There was 1 warning in `dplyr::arrange()`.
## i In argument: `..1 = dplyr::pick(target_columns)`.
## Caused by warning:
## ! Using an external vector in selections was deprecated in tidyselect 1.1.0.
## i Please use `all_of()` or `any_of()` instead.
## # Was:
## data %>% select(target_columns)
##
## # Now:
## data %>% select(all_of(target_columns))
##
## See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## Backtrace:
## ▆
## 1. ├─cleanepi::check_subject_ids(...) at test-standardize_subject_ids.R:131:3
## 2. │ └─cleanepi:::check_subject_ids_oness(data, target_columns) at cleanepi/R/standardize_subject_ids.R:55:3
## 3. │ ├─base::suppressMessages(find_duplicates(data, id_col_name)) at cleanepi/R/standardize_subject_ids.R:195:3
## 4. │ │ └─base::withCallingHandlers(...)
## 5. │ └─cleanepi::find_duplicates(data, id_col_name) at cleanepi/R/standardize_subject_ids.R:195:3
## 6. │ └─... %>% ... at cleanepi/R/find_and_remove_duplicates.R:105:3
## 7. ├─dplyr::mutate(., group_id = dplyr::cur_group_id(), .after = "row_id")
## 8. ├─dplyr::group_by(., dplyr::across(dplyr::all_of(target_columns)))
## 9. ├─dplyr::arrange(., dplyr::pick(target_columns))
## 10. └─dplyr:::arrange.data.frame(., dplyr::pick(target_columns))
## 11. └─dplyr:::arrange_rows(.data, dots = dots, locale = .locale)
## 12. ├─dplyr::mutate(data, `:=`("{name}", !!dot), .keep = "none")
## 13. └─dplyr:::mutate.data.frame(data, `:=`("{name}", !!dot), .keep = "none")
## 14. └─dplyr:::mutate_cols(.data, dplyr_quosures(...), by)
## 15. └─dplyr:::signal_warnings(warnings_state, error_call)
##
## Warning (test-standardize_subject_ids.R:143:3): check_subject_ids works when relying on the nchar argument
## There was 1 warning in `dplyr::arrange()`.
## i In argument: `..1 = dplyr::pick(target_columns)`.
## Caused by warning:
## ! Using an external vector in selections was deprecated in tidyselect 1.1.0.
## i Please use `all_of()` or `any_of()` instead.
## # Was:
## data %>% select(target_columns)
##
## # Now:
## data %>% select(all_of(target_columns))
##
## See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## Backtrace:
## ▆
## 1. ├─cleanepi::check_subject_ids(...) at test-standardize_subject_ids.R:143:3
## 2. │ └─cleanepi:::check_subject_ids_oness(data, target_columns) at cleanepi/R/standardize_subject_ids.R:55:3
## 3. │ ├─base::suppressMessages(find_duplicates(data, id_col_name)) at cleanepi/R/standardize_subject_ids.R:195:3
## 4. │ │ └─base::withCallingHandlers(...)
## 5. │ └─cleanepi::find_duplicates(data, id_col_name) at cleanepi/R/standardize_subject_ids.R:195:3
## 6. │ └─... %>% ... at cleanepi/R/find_and_remove_duplicates.R:105:3
## 7. ├─dplyr::mutate(., group_id = dplyr::cur_group_id(), .after = "row_id")
## 8. ├─dplyr::group_by(., dplyr::across(dplyr::all_of(target_columns)))
## 9. ├─dplyr::arrange(., dplyr::pick(target_columns))
## 10. └─dplyr:::arrange.data.frame(., dplyr::pick(target_columns))
## 11. └─dplyr:::arrange_rows(.data, dots = dots, locale = .locale)
## 12. ├─dplyr::mutate(data, `:=`("{name}", !!dot), .keep = "none")
## 13. └─dplyr:::mutate.data.frame(data, `:=`("{name}", !!dot), .keep = "none")
## 14. └─dplyr:::mutate_cols(.data, dplyr_quosures(...), by)
## 15. └─dplyr:::signal_warnings(warnings_state, error_call)
##
## Warning (test-standardize_subject_ids.R:156:3): check_subject_ids works when relying on the nchar argument
## There was 1 warning in `dplyr::arrange()`.
## i In argument: `..1 = dplyr::pick(target_columns)`.
## Caused by warning:
## ! Using an external vector in selections was deprecated in tidyselect 1.1.0.
## i Please use `all_of()` or `any_of()` instead.
## # Was:
## data %>% select(target_columns)
##
## # Now:
## data %>% select(all_of(target_columns))
##
## See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## Backtrace:
## ▆
## 1. ├─cleanepi::check_subject_ids(...) at test-standardize_subject_ids.R:156:3
## 2. │ └─cleanepi:::check_subject_ids_oness(data, target_columns) at cleanepi/R/standardize_subject_ids.R:55:3
## 3. │ ├─base::suppressMessages(find_duplicates(data, id_col_name)) at cleanepi/R/standardize_subject_ids.R:195:3
## 4. │ │ └─base::withCallingHandlers(...)
## 5. │ └─cleanepi::find_duplicates(data, id_col_name) at cleanepi/R/standardize_subject_ids.R:195:3
## 6. │ └─... %>% ... at cleanepi/R/find_and_remove_duplicates.R:105:3
## 7. ├─dplyr::mutate(., group_id = dplyr::cur_group_id(), .after = "row_id")
## 8. ├─dplyr::group_by(., dplyr::across(dplyr::all_of(target_columns)))
## 9. ├─dplyr::arrange(., dplyr::pick(target_columns))
## 10. └─dplyr:::arrange.data.frame(., dplyr::pick(target_columns))
## 11. └─dplyr:::arrange_rows(.data, dots = dots, locale = .locale)
## 12. ├─dplyr::mutate(data, `:=`("{name}", !!dot), .keep = "none")
## 13. └─dplyr:::mutate.data.frame(data, `:=`("{name}", !!dot), .keep = "none")
## 14. └─dplyr:::mutate_cols(.data, dplyr_quosures(...), by)
## 15. └─dplyr:::signal_warnings(warnings_state, error_call)
##
## Warning (test-standardize_subject_ids.R:176:3): correct_subject_ids works as expected
## There was 1 warning in `dplyr::arrange()`.
## i In argument: `..1 = dplyr::pick(target_columns)`.
## Caused by warning:
## ! Using an external vector in selections was deprecated in tidyselect 1.1.0.
## i Please use `all_of()` or `any_of()` instead.
## # Was:
## data %>% select(target_columns)
##
## # Now:
## data %>% select(all_of(target_columns))
##
## See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## Backtrace:
## ▆
## 1. ├─cleanepi::check_subject_ids(...) at test-standardize_subject_ids.R:176:3
## 2. │ └─cleanepi:::check_subject_ids_oness(data, target_columns) at cleanepi/R/standardize_subject_ids.R:55:3
## 3. │ ├─base::suppressMessages(find_duplicates(data, id_col_name)) at cleanepi/R/standardize_subject_ids.R:195:3
## 4. │ │ └─base::withCallingHandlers(...)
## 5. │ └─cleanepi::find_duplicates(data, id_col_name) at cleanepi/R/standardize_subject_ids.R:195:3
## 6. │ └─... %>% ... at cleanepi/R/find_and_remove_duplicates.R:105:3
## 7. ├─dplyr::mutate(., group_id = dplyr::cur_group_id(), .after = "row_id")
## 8. ├─dplyr::group_by(., dplyr::across(dplyr::all_of(target_columns)))
## 9. ├─dplyr::arrange(., dplyr::pick(target_columns))
## 10. └─dplyr:::arrange.data.frame(., dplyr::pick(target_columns))
## 11. └─dplyr:::arrange_rows(.data, dots = dots, locale = .locale)
## 12. ├─dplyr::mutate(data, `:=`("{name}", !!dot), .keep = "none")
## 13. └─dplyr:::mutate.data.frame(data, `:=`("{name}", !!dot), .keep = "none")
## 14. └─dplyr:::mutate_cols(.data, dplyr_quosures(...), by)
## 15. └─dplyr:::signal_warnings(warnings_state, error_call)
##
## Warning (test-standardize_subject_ids.R:193:3): correct_subject_ids works as expected
## There was 1 warning in `dplyr::arrange()`.
## i In argument: `..1 = dplyr::pick(target_columns)`.
## Caused by warning:
## ! Using an external vector in selections was deprecated in tidyselect 1.1.0.
## i Please use `all_of()` or `any_of()` instead.
## # Was:
## data %>% select(target_columns)
##
## # Now:
## data %>% select(all_of(target_columns))
##
## See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## Backtrace:
## ▆
## 1. ├─cleanepi::correct_subject_ids(...) at test-standardize_subject_ids.R:193:3
## 2. │ └─cleanepi:::check_subject_ids_oness(data, target_columns) at cleanepi/R/standardize_subject_ids.R:166:3
## 3. │ ├─base::suppressMessages(find_duplicates(data, id_col_name)) at cleanepi/R/standardize_subject_ids.R:195:3
## 4. │ │ └─base::withCallingHandlers(...)
## 5. │ └─cleanepi::find_duplicates(data, id_col_name) at cleanepi/R/standardize_subject_ids.R:195:3
## 6. │ └─... %>% ... at cleanepi/R/find_and_remove_duplicates.R:105:3
## 7. ├─dplyr::mutate(., group_id = dplyr::cur_group_id(), .after = "row_id")
## 8. ├─dplyr::group_by(., dplyr::across(dplyr::all_of(target_columns)))
## 9. ├─dplyr::arrange(., dplyr::pick(target_columns))
## 10. └─dplyr:::arrange.data.frame(., dplyr::pick(target_columns))
## 11. └─dplyr:::arrange_rows(.data, dots = dots, locale = .locale)
## 12. ├─dplyr::mutate(data, `:=`("{name}", !!dot), .keep = "none")
## 13. └─dplyr:::mutate.data.frame(data, `:=`("{name}", !!dot), .keep = "none")
## 14. └─dplyr:::mutate_cols(.data, dplyr_quosures(...), by)
## 15. └─dplyr:::signal_warnings(warnings_state, error_call)
##
## Warning (test-standardize_subject_ids.R:241:3): check_subject_ids fails as expected
## There was 1 warning in `dplyr::arrange()`.
## i In argument: `..1 = dplyr::pick(target_columns)`.
## Caused by warning:
## ! Using an external vector in selections was deprecated in tidyselect 1.1.0.
## i Please use `all_of()` or `any_of()` instead.
## # Was:
## data %>% select(target_columns)
##
## # Now:
## data %>% select(all_of(target_columns))
##
## See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## Backtrace:
## ▆
## 1. ├─testthat::expect_message(...) at test-standardize_subject_ids.R:241:3
## 2. │ └─testthat:::expect_condition_matching(...)
## 3. │ └─testthat:::quasi_capture(...)
## 4. │ ├─testthat (local) .capture(...)
## 5. │ │ └─base::withCallingHandlers(...)
## 6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
## 7. ├─cleanepi::check_subject_ids(...)
## 8. │ └─cleanepi:::check_subject_ids_oness(data, target_columns) at cleanepi/R/standardize_subject_ids.R:55:3
## 9. │ ├─base::suppressMessages(find_duplicates(data, id_col_name)) at cleanepi/R/standardize_subject_ids.R:195:3
## 10. │ │ └─base::withCallingHandlers(...)
## 11. │ └─cleanepi::find_duplicates(data, id_col_name) at cleanepi/R/standardize_subject_ids.R:195:3
## 12. │ └─... %>% ... at cleanepi/R/find_and_remove_duplicates.R:105:3
## 13. ├─dplyr::mutate(., group_id = dplyr::cur_group_id(), .after = "row_id")
## 14. ├─dplyr::group_by(., dplyr::across(dplyr::all_of(target_columns)))
## 15. ├─dplyr::arrange(., dplyr::pick(target_columns))
## 16. └─dplyr:::arrange.data.frame(., dplyr::pick(target_columns))
## 17. └─dplyr:::arrange_rows(.data, dots = dots, locale = .locale)
## 18. ├─dplyr::mutate(data, `:=`("{name}", !!dot), .keep = "none")
## 19. └─dplyr:::mutate.data.frame(data, `:=`("{name}", !!dot), .keep = "none")
## 20. └─dplyr:::mutate_cols(.data, dplyr_quosures(...), by)
## 21. └─dplyr:::signal_warnings(warnings_state, error_call)
##
## Warning (test-standardize_subject_ids.R:257:3): check_subject_ids works when relying on the nchar argument
## There was 1 warning in `dplyr::arrange()`.
## i In argument: `..1 = dplyr::pick(target_columns)`.
## Caused by warning:
## ! Using an external vector in selections was deprecated in tidyselect 1.1.0.
## i Please use `all_of()` or `any_of()` instead.
## # Was:
## data %>% select(target_columns)
##
## # Now:
## data %>% select(all_of(target_columns))
##
## See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## Backtrace:
## ▆
## 1. ├─cleanepi::check_subject_ids(...) at test-standardize_subject_ids.R:257:3
## 2. │ └─cleanepi:::check_subject_ids_oness(data, target_columns) at cleanepi/R/standardize_subject_ids.R:55:3
## 3. │ ├─base::suppressMessages(find_duplicates(data, id_col_name)) at cleanepi/R/standardize_subject_ids.R:195:3
## 4. │ │ └─base::withCallingHandlers(...)
## 5. │ └─cleanepi::find_duplicates(data, id_col_name) at cleanepi/R/standardize_subject_ids.R:195:3
## 6. │ └─... %>% ... at cleanepi/R/find_and_remove_duplicates.R:105:3
## 7. ├─dplyr::mutate(., group_id = dplyr::cur_group_id(), .after = "row_id")
## 8. ├─dplyr::group_by(., dplyr::across(dplyr::all_of(target_columns)))
## 9. ├─dplyr::arrange(., dplyr::pick(target_columns))
## 10. └─dplyr:::arrange.data.frame(., dplyr::pick(target_columns))
## 11. └─dplyr:::arrange_rows(.data, dots = dots, locale = .locale)
## 12. ├─dplyr::mutate(data, `:=`("{name}", !!dot), .keep = "none")
## 13. └─dplyr:::mutate.data.frame(data, `:=`("{name}", !!dot), .keep = "none")
## 14. └─dplyr:::mutate_cols(.data, dplyr_quosures(...), by)
## 15. └─dplyr:::signal_warnings(warnings_state, error_call)
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## ⠏ | 0 | utils Assertion on',target_columns,'failed: all specified target
## columns will be ignored because they are either empty or
## constant.Assertion on',keep,'failed: usage of 'linelist_tags'
## ⠼ | 15 | utils ✔ | 32 | utilsnames indices are out of bound.
##
## ══ Results ═══════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════════
## Duration: 14.2 s
##
## ── Failed tests ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
## Error (test-print_report.R:45:3): print_report works
## Error: pandoc document conversion failed with error 63
## Backtrace:
## ▆
## 1. └─cleanepi::print_report(...) at test-print_report.R:45:3
## 2. └─rmarkdown::render(...) at cleanepi/R/print_report.R:114:3
## 3. └─rmarkdown (local) convert(output_file, run_citeproc)
## 4. └─rmarkdown (local) convert_it(output)
## 5. └─rmarkdown (local) convert_fun(...)
## 6. └─rmarkdown:::stop2(...)
##
## [ FAIL 1 | WARN 25 | SKIP 0 | PASS 347 ] |
bahadzie
reviewed
Nov 14, 2024
bahadzie
reviewed
Nov 14, 2024
| @@ -1,9 +1,11 @@ | |||
| #' Check date time frame | |||
| #' | |||
| #' @param first_date A Date object specifying the first valid date. | |||
| #' The arbitrary default value is fifty years before the `last_date`. | |||
| #' The arbitrary default value is fifty years before the \code{last_date}. | |||
| #' This can also be a character in ISO8601 format i.e. "2024-12-31". | |||
| #' @param last_date A Date object specifying the last valid date. | |||
There was a problem hiding this comment.
What other datatype can it be? Here you are indicating that it can also be character without saying what it usually is.
There was a problem hiding this comment.
I have mentioned on line 3 that it's supposed to be a <Date> object, the second option being <character>.
Do you think this needs to be updated with more details?
bahadzie
reviewed
Nov 14, 2024
Thanks @bahadzie for the review |
bahadzie
reviewed
Nov 14, 2024
|
This pull request:
(Note that results may be inacurrate if you branched from an outdated version of the target branch.) |
|
This pull request:
(Note that results may be inacurrate if you branched from an outdated version of the target branch.) |
|
This pull request:
(Note that results may be inacurrate if you branched from an outdated version of the target branch.) |
…m main functions instead
|
This pull request:
(Note that results may be inacurrate if you branched from an outdated version of the target branch.) |
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