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Recent Releases of naniar

naniar - naniar 1.1.0

New

  • Implement impute_fixed, impute_zero, and impute_factor. notably these do not implement "scoped variants" which were previously implemented - for example, impute_fixed_if etc. This is in favour of using the new across workflow within dplyr, and it is easier to maintain. #261
  • Add digit argument to miss_var_summary to help display %missing data correctly when there is a very small fraction of missingness. #284
  • Implemented impute_mode - resolves #213.
  • geom_miss_point() works with shape argument #290
  • Fix bug with all_complete, which was implemented as !anyNA(x) but should be all(complete.cases(x)).
  • Correctly implement any_na() (and any_miss()) and any_complete(). Rework examples to demonstrate workflow for finding complete variables.

Bug fixes

  • Fix bug with shadow_long not working when gathering variables of mixed type. Fix involves specifying a value transform, which defaults to character. #314
  • Implement Date, POSIXct and POSIXlt methods for impute_below() - #158
  • Provide replacenawith, a complement to replacewithna - #129
  • Fix bug with gg_miss_fct where it used a deprecated function from forcats - #342

Misc

  • Use cli::cli_abort and cli::cli_warn instead of stop and warn (#326)
  • Use expect_snapshot instead of expect_error (#326)

Changes

  • Soft deprecated shadow_shift - #193
  • Soft deprecate miss_case_cumsum() and miss_var_cumsum() - #257

- R
Published by njtierney almost 2 years ago

naniar - naniar 1.0.0

Version 1.0.0 of naniar is to signify that this release is associated with the publication of the associated JSS paper, doi:10.18637/jss.v105.i07. There are also a few small changes that have been implemented in this release, which are described below.

There is still a lot to do in naniar, and this release does not signify that there are no changes upcoming, more so to establish that this is a stable release, and that any changes upcoming will go through a more formal deprecation process and so on.

New

  • The DOI in the CITATION is for a new JSS publication that will be registered after publication on CRAN.
  • Replaced tidyr::gather with tidyr::pivot_longer - resolves #301
  • added set_n_miss and set_prop_miss functions - resolved #298

Bug Fixes

  • Fix bug in gg_miss_var() where a warning appears to due change in how to remove legend #288.

Misc

  • Removed gdtools from naniar as no longer needed 302.
  • added imports, vctrs and cli - which are both free dependencies as they are used within the already used tidyverse already.

- R
Published by njtierney about 3 years ago

naniar - "Spur of the lamp post"

naniar 0.6.0 (2020/08/17) "Spur of the lamp post"

  • Provide warning for replace_with_na when columns provided that don't exist (see #160). Thank you to michael-dewar for their help with this.

Breaking Changes

  • Drop the "nabular" and "shadow" classes (#268) used in nabular() and bind_shadow(). In doing so removes the functions, as_shadow(), is_shadow(), is_nabular(), new_nabular(), new_shadow(). These were mostly used internally and it is not expected that users would have used this functions. If these were used, please file an issue and I can implement them again.

- R
Published by njtierney over 5 years ago

naniar - naniar 0.5.2 (2020/06/28) "Silver Apple"

naniar 0.5.2 (2020/06/28) "Silver Apple"

Minor Changes

  • Improvements to code in miss_var_summary(), miss_var_table(), and prop_miss_var(), resulting in a 3-10x speedup.

- R
Published by njtierney over 5 years ago

naniar - "Uncle Andrew's Applewood Wardrobe"

naniar 0.5.1 (2020/04/10) "Uncle Andrew's Applewood Wardrobe"

Minor Changes

  • Fixes warnings and errors from tibble and subsequent downstream impacts on simputation.

- R
Published by njtierney almost 6 years ago

naniar - The End of this Story and the Beginning of all of the Others

naniar 0.5.0 (2020/02/20) "The End of this Story and the Beginning of all of the Others"

Breaking Changes

  • The following functions related to calculating the proportion/percentage of missingness were made Defunct and will no longer work:
    • miss_var_prop()
    • complete_var_prop()
    • miss_var_pct()
    • complete_var_pct()
    • miss_case_prop()
    • complete_case_prop()
    • miss_case_pct()
    • complete_case_pct()

Instead use: prop_miss_var(), prop_complete_var(), pct_miss_var(), pct_complete_var(), prop_miss_case(), prop_complete_case(), pct_miss_case(), pct_complete_case(). (see 242)

  • replace_to_na() was made defunct, please use replace_with_na() instead. (see 242)

Minor changes

  • miss_var_cumsum and miss_case_cumsum are now exported
  • use map_dfc instead of map_df
  • Fix various extra warnings and improve test coverage

Bug Fixes

  • Address bug where the number of missings in a row is not calculated properly - see 238 and 232. The solution involved using rowSums(is.na(x)), which was 3 times faster.
  • Resolve bug in gg_miss_fct() where warning is given for non explicit NA values - see 241.
  • skip vdiffr tests on github actions
  • use tibble() not data_frame()

- R
Published by njtierney almost 6 years ago

naniar - The Planting of The Tree

Improvements

  • The geom_miss_point() ggplot2 layer can now be converted into an interactive web-based version by the ggplotly() function in the plotly package. In order for this to work, naniar now exports the geom2trace.GeomMissPoint() function (users should never need to call geom2trace.GeomMissPoint() directly -- ggplotly() calls it for you).
  • adds WORDLIST for spelling thanks to usethis::use_spell_check()
  • fix documentation @seealso bug (#228) (@sfirke)

Dependency fixes

  • Thanks to a PR (#223) from @romainfrancois:

    • This fixes two problems that were identified as part of reverse dependency checks of dplyr 0.8.0 release candidate. https://github.com/tidyverse/dplyr/blob/revdepdplyr080_RC/revdep/problems.md#naniar
    • n() must be imported or prefixed like any other function. In the PR, I've changed 1:n() to dplyr::row_number() as naniar seems to prefix all dplyr functions.
    • updateshadow was only restoring the class attributes, changed so that it restores all attributes, this was causing problems when data was a groupeddf. This likely was a problem before too, but dplyr 0.8.0 is stricter about what is a grouped data frame.

- R
Published by njtierney about 7 years ago

naniar - # naniar 0.4.1 (2018/11/20) "Aslan's Song"

Minor Change

- R
Published by njtierney about 7 years ago

naniar - An Unexpected Meeting

New Feature

  • Add custom label support for missings and not missings with functions add_label_missings and add_label_shadow() and add_any_miss(). So you can now do `addlabelmissings(data, missing = "custommissinglabel", complete = "customcompletelabel")
  • impute_median() and scoped variants
  • any_shade() returns a logical TRUE or FALSE depending on if there are any shade values
  • nabular() an alias for bind_shadow() to tie the nabular term into the work.

  • is_nabular() checks if input is nabular.

  • geom_miss_point() now gains the arguments from shadow_shift()/impute_below() for altering the amount of jitter and proportion below (prop_below).

  • Added two new vignettes, "Exploring Imputed Values", and "Special Missing Values"

  • miss_var_summary and miss_case_summary now no longer provide the cumulative sum of missingness in the summaries - this summary can be added back to the data with the option add_cumsum = TRUE. #186

  • Added gg_miss_upset to replace workflow of: data %>% as_shadow_upset() %>% UpSetR::upset()

Major Change

  • recode_shadow now works! This function allows you to recode your missing values into special missing values. These special missing values are stored in the shadow part of the dataframe, which ends in _NA.
  • implemented shade where appropriate throughout naniar, and also added verifiers, is_shade, are_shade, which_are_shade, and removed which_are_shadow.
  • as_shadow and bind_shadow now return data of class shadow. This will feed into recode_shadow methods for flexibly adding new types of missing data.
  • Note that in the future shadow might be changed to nabble or something similar.

Minor feature

  • Functions add_label_shadow() and add_label_missings() gain arguments so you can only label according to the missingness / shadowy-ness of given variables.
  • new function which_are_shadow(), to tell you which values are shadows.
  • new function long_shadow(), which converts data in shadow/nabular form into a long format suitable for plotting. Related to #165
  • Added tests for miss_scan_count

Minor Changes

  • gg_miss_upset gets a better default presentation by ordering by the largest intersections, and also an improved error message when data with only 1 or no variables have missing values.
  • shadow_shift gains a more informative error message when it doesn't know the class.
  • Changed common_na_string to include escape characters for "?", "", "." so that if they are used in replacement or searching functions they don't return the wildcard results from the characters "?", "", and ".".
  • miss_case_table and miss_var_table now has final column names pct_vars, and pct_cases instead of pct_miss - fixes #178.

Breaking Changes

  • Deprecated old names of the scalar missingness summaries, in favour of a more consistent syntax #171. The old the and new are:

|oldnames |newnames | |:--------------------|:--------------------| |miss_case_pct |pct_miss_case | |miss_case_prop |prop_miss_case | |miss_var_pct |pct_miss_var | |miss_var_prop |prop_miss_var | |complete_case_pct |pct_complete_case | |complete_case_prop |prop_complete_case | |complete_var_pct |pct_complete_var | |complete_var_prop |prop_complete_var |

These old names will be made defunct in 0.5.0, and removed completely in 0.6.0.

  • impute_below has changed to be an alias of shadow_shift - that is it operates on a single vector. impute_below_all operates on all columns in a dataframe (as specified in #159)

Bug fix

  • Ensured that miss_scan_count actually return'd something.
  • gg_miss_var(airquality) now prints the ggplot - a typo meant that this did not print the plot

- R
Published by njtierney over 7 years ago

naniar - Strawberry's Adventure

This release is a patch to remove a package imported but not used.

Minor Change

This is a patch release that removes tidyselect from the package Imports, as it is unnecessary. Fixes #174 naniar_0.3.1.tar.gz

- R
Published by njtierney over 7 years ago

naniar - Digory and his Uncle Are Both in Trouble

New Features

  • Added all_miss() / all_na() equivalent to all(is.na(x))
  • Added any_complete() equivalent to all(complete.cases(x))
  • Added any_miss() equivalent to anyNA(x)
  • Added common_na_numbers and finalised common_na_strings - to provide a list of commonly used NA values #168
  • Added miss_var_which, to lists the variable names with missings
  • Added as_shadow_upset which gets the data into a format suitable for plotting as an UpSetR plot:

r airquality %>% as_shadow_upset() %>% UpSetR::upset()

  • Added some imputation functions to assist with exploring missingness structure and visualisation:

    • impute_below Perfoms as for shadow_shift, but performs on all columns. This means that it imputes missing values 10% below the range of the data (powered by shadow_shift), to facilitate graphical exloration of the data. Closes #145 There are also scoped variants that work for specific named columns: impute_below_at, and for columns that satisfy some predicate function: impute_below_if.
    • impute_mean, imputes the mean value, and scoped variants impute_mean_at, and impute_mean_if.

  • impute_below and shadow_shift gain arguments prop_below and jitter to control the degree of shift, and also the extent of jitter.

  • Added complete_{case/var}_{pct/prop}, which complement miss_{var/case}_{pct/prop} #150

  • Added unbind_shadow and unbind_data as helpers to remove shadow columns from data, and data from shadows, respectively.

  • Added is_shadow and are_shadow to determine if something contains a shadow column. simimlar to rlang::is_na and rland::are_na, is_shadow this returns a logical vector of length 1, and are_shadow returns a logical vector of length of the number of names of a data.frame. This might be revisited at a later point (see any_shade in add_label_shadow).

  • Aesthetics now map as expected in geommisspoint(). This means you can write things like geom_miss_point(aes(colour = Month)) and it works appropriately. Fixed by Luke Smith in Pull request #144, fixing #137.

Minor Changes

  • miss_var_summary and miss_case_summary now return use order = TRUE by default, so cases and variables with the most missings are presented in descending order. Fixes #163

  • Changes for Visualisation:

    • Changed the default colours used in gg_miss_case and gg_miss_var to lorikeet purple (from ochRe package: https://github.com/ropenscilabs/ochRe)
    • gg_miss_case
    • The y axis label is now ...
    • Default presentation is with order_cases = TRUE.
    • Gains a show_pct option to be consistent with gg_miss_var #153
    • gg_miss_which is rotated 90 degrees so it is easier to read variable names
    • gg_miss_fct uses a minimal theme and tilts the axis labels #118.

  • imported is_na and are_na from rlang.

  • Added common_na_strings, a list of common NA values #168.

  • Added some detail on alternative methods for replacing with NA in the vignette "replacing values with NA".

- R
Published by njtierney over 7 years ago

naniar - CRAN 0.1.0 Release "The Founding of naniar"

"The Founding of naniar the first version on CRAN! The name is taken from Chapter 9 of The Magician's Nephew. Below is the updated NEWS file

naniar 0.1.0 (2017/08/09) "The Founding of naniar"

=========================

  • This is the first release of naniar onto CRAN, updates to naniar will happen reasonably regularly after this approximately every 1-2 months

naniar 0.0.9.9995 (2017/08/07)

=========================

Name change

  • After careful consideration, I have changed back to naniar

Major Change

  • three new functions : miss_case_cumsum / miss_var_cumsum / replace_to_na
  • two new visualisations : gg_var_cumsum & gg_case_cumsum

New Feature

  • group_by is now respected by the following functions:
    • miss_case_cumsum()
    • miss_case_summary()
    • miss_case_table()
    • miss_prop_summary()
    • miss_var_cumsum()
    • miss_var_run()
    • miss_var_span()
    • miss_var_summary()
    • miss_var_table()

Minor changes

  • Reviewed documentation for all functions and improved wording, grammar, and style.
  • Converted roxygen to roxygen markdown
  • updated vignettes and readme
  • added a new vignette "naniar-visualisation", to give a quick overview of the visualisations provided with naniar.
  • changed label_missing* to label_miss to be more consistent with the rest of naniar
  • Add pct and prop helpers (#78)
  • removed miss_df_pct - this was literally the same as pct_miss or prop_miss.
  • break larger files into smaller, more manageable files (#83)
  • gg_miss_var gets a show_pct argument to show the percentage of missing values (Thanks Jennifer for the helpful feedback! :))

Minor changes

  • miss_var_summary & miss_case_summary now have consistent output (one was ordered by n_missing, not the other).
  • prevent error in miss_case_pct
  • enquo_x is now x (as adviced by Hadley)
  • Now has ByteCompile to TRUE
  • add Colin to auth

narnia 0.0.9.9400 (2017/07/24)

=========================

new features

  • replace_to_na is a complement to tidyr::replace_na and replaces a specified value from a variable to NA.
  • gg_miss_fct returns a heatmap of the number of missings per variable for each level of a factor. This feature was very kindly contributed by Colin Fay.
  • gg_miss_ functions now return a ggplot object, which behave as such. gg_miss_ basic themes can be overriden with ggplot functions. This fix was very kindly contributed by Colin Fay.
  • removed defunct functions as per #63
  • made add_* functions handle bare unqouted names where appropriate as per #61
  • added tests for the add_* family
  • got the svgs generated from vdiffr, thanks @karawoo!

breaking changes

  • changed geom_missing_point() to geom_miss_point(), to keep consistent with the rest of the functions in naniar.

narnia 0.0.8.9100 (2017/06/23)

=========================

new features

  • updated datasets brfss and tao as per #59

narnia 0.0.7.9992 (2017/06/22)

=========================

new features

  • add_label_missings()
  • add_label_shadow()
  • cast_shadow()
  • cast_shadow_shift()

  • cast_shadow_shift_label()

  • added github issue / contribution / pull request guides

  • ts generic functions are now miss_var_span and miss_var_run, and gg_miss_span and work on data.frame's, as opposed to just ts objects.

  • add_shadow_shift() adds a column of shadowshifted values to the current dataframe, adding "shift" as a suffix

  • cast_shadow() - acts like bind_shadow() but allows for specifying which columns to add

  • shadow_shift now has a method for factors - powered by forcats::fct_explicit_na() #3

bug fixes

  • shadow_shift.numeric works when there is no variance (#37)

name changes

  • changed is_na function to label_na
  • renamed most files to have tidy-miss-[topic]
  • gg_missing_* is changed to gg_miss_* to fit with other syntax

Removed functions

  • Removed old functions miss_cat, shadow_df and shadow_cat, as they are no longer needed, and have been superceded by label_missing_2d, as_shadow, and is_na.

minor changes

  • drastically reduced the size of the pedestrian dataset, consider 4 sensor locations, just for 2016.

New features

  • New dataset, pedestrian - contains hourly counts of pedestrians
  • First pass at time series missing data summaries and plots:
    • miss_ts_run(): return the number of missings / complete in a single run
    • miss_ts_summary(): return the number of missings in a given time period
    • gg_miss_ts(): plot the number of missings in a given time period

Name changes

  • renamed package from naniar to narnia - I had to explain the spelling a few times when I was introducing the package and I realised that I should change the name. Fortunately it isn't on CRAN yet.

naniar 0.0.6.9100 (2017/03/21)

=========================

  • Added prop_miss and the complement prop_complete. Where n_miss returns the number of missing values, prop_miss returns the proportion of missing values. Likewise, prop_complete returns the proportion of complete values.

Defunct functions

  • As stated in 0.0.5.9000, to address Issue #38, I am moving towards the format misstypevalue/fun, because it makes more sense to me when tabbing through functions.

The left hand side functions have been made defunct in favour of the right hand side. - percent_missing_case() --> miss_case_pct() - percent_missing_var() --> miss_var_pct() - percent_missing_df() --> miss_df_pct() - summary_missing_case() --> miss_case_summary() - summary_missing_var() --> miss_var_summary() - table_missing_case() --> miss_case_table() - table_missing_var() --> miss_var_table()

naniar 0.0.5.9000 (2016/01/08)

=========================

Deprecated functions

  • To address Issue #38, I am moving towards the format misstypevalue/fun, because it makes more sense to me when tabbing through functions.
  • miss_* = I want to explore missing values
  • miss_case_* = I want to explore missing cases
  • miss_case_pct = I want to find the percentage of cases containing a missing value
  • miss_case_summary = I want to find the number / percentage of missings in each case miss_case_table = I want a tabulation of the number / percentage of cases missing

This is more consistent and easier to reason with.

Thus, I have renamed the following functions: - percent_missing_case() --> miss_case_pct() - percent_missing_var() --> miss_var_pct() - percent_missing_df() --> miss_df_pct() - summary_missing_case() --> miss_case_summary() - summary_missing_var() --> miss_var_summary() - table_missing_case() --> miss_case_table() - table_missing_var() --> miss_var_table()

These will be made defunct in the next release, 0.0.6.9000 ("The Wood Between Worlds").

naniar 0.0.4.9000 (2016/12/31)

=========================

New features

  • n_complete is a complement to n_miss, and counts the number of complete values in a vector, matrix, or dataframe.

Bug fixes

  • shadow_shift now handles cases where there is only 1 complete value in a vector.

Other changes

  • added much more comprehensive testing with testthat.

naniar 0.0.3.9901 (2016/12/18)

=========================

After a burst of effort on this package I have done some refactoring and thought hard about where this package is going to go. This meant that I had to make the decision to rename the package from ggmissing to naniar. The name may strike you as strange but it reflects the fact that there are many changes happening, and that we will be working on creating a nice utopia (like Narnia by CS Lewis) that helps us make it easier to work with missing data

New Features (under development)

  • add_n_miss and add_prop_miss are helpers that add columns to a dataframe containing the number and proportion of missing values. An example has been provided to use decision trees to explore missing data structure as in Tierney et al

  • geom_miss_point() now supports transparency, thanks to @seasmith (Luke Smith)

  • more shadows. These are mainly around bind_shadow and gather_shadow, which are helper functions to assist with creating

Bug fixes

  • geom_missing_point() broke after the new release of ggplot2 2.2.0, but this is now fixed by ensuring that it inherits from GeomPoint, rather than just a new Geom. Thanks to Mitchell O'hara-Wild for his help with this.

  • missing data summaries table_missing_var and table_missing_case also now return more sensible numbers and variable names. It is possible these function names will change in the future, as these are kind of verbose.

  • semantic versioning was incorrectly entered in the DESCRIPTION file as 0.2.9000, so I changed it to 0.0.2.9000, and then to 0.0.3.9000 now to indicate the new changes, hopefully this won't come back to bite me later. I think I accidentally did this with visdat at some point as well. Live and learn.

Other changes

  • gathered related functions into single R files rather than leaving them in their own.

  • correctly imported the %>% operator from magrittr, and removed a lot of chaff around @importFrom - really don't need to use @importFrom that often.

ggmissing 0.0.2.9000 (2016/07/29)

=========================

New Feature (under development)

  • geom_missing_point() now works in a way that we expect! Thanks to Miles McBain for working out how to get this to work.

ggmissing 0.0.1.9000 (2016/07/29)

=========================

New Feature (under development)

  • tidy summaries for missing data:
    • percent_missing_df returns the percentage of missing data for a data.frame
    • percent_missing_var the percentage of variables that contain missing values
    • percent_missing_case the percentage of cases that contain missing values.
    • table_missing_var table of missing information for variables
    • table_missing_case table of missing information for cases
    • summary_missing_var summary of missing information for variables (counts, percentages)
    • summary_missing_case summary of missing information for variables (counts, percentages)
  • ggmissingcol: plot the missingness in each variable
  • ggmissingrow: plot the missingness in each case
  • ggmissingwhich: plot which columns contain missing data.

- R
Published by njtierney over 8 years ago

naniar - The Wrong Door

naniar 0.0.4.9000 (2016/12/31)

New features

  • n_complete is a complement to n_miss, and counts the number of complete values in a vector, matrix, or dataframe.

Bug fixes

  • shadow_shift now handles cases where there is only 1 complete value in a vector.

Other changes

  • added much more comprehensive testing with testthat.

naniar 0.0.3.9901 (2016/12/18)

New features

  • add_n_miss and add_prop_miss are helpers that add columns to a dataframe containing the number and proportion of missing values. An example has been provided to use decision trees to explore missing data structure as in Tierney et al
  • geom_miss_point() now supports transparency, thanks to @seasmith (Luke Smith)

naniar 0.0.3.9000 (2016/12/18)

After a burst of effort on this package I have done some refactoring and thought hard about where this package is going to go. This meant that I had to make the decision to rename the package from ggmissing to naniar. The name may strike you as strange but it reflects the fact that there are many changes happening, and that we will be working on creating a nice utopia (like Narnia by CS Lewis) that helps us make it easier to work with missing data

New Features (under development)

  • more shadows. These are mainly around bind_shadow and gather_shadow, which are helper functions to assist with creating

Bug fixes

  • geom_missing_point() broke after the new release of ggplot2 2.2.0, but this is now fixed by ensuring that it inherits from GeomPoint, rather than just a new Geom. Thanks to Mitchell O'hara-Wild for his help with this.
  • missing data summaries table_missing_var and table_missing_case also now return more sensible numbers and variable names. It is possible these function names will change in the future, as these are kind of verbose.
  • semantic versioning was incorrectly entered in the DESCRIPTION file as 0.2.9000, so I changed it to 0.0.2.9000, and then to 0.0.3.9000 now to indicate the new changes, hopefully this won't come back to bite me later. I think I accidentally did this with visdat at some point as well. Live and learn.

Other changes

  • gathered related functions into single R files rather than leaving them in their own.
  • correctly imported the %>% operator from magrittr, and removed a lot of chaff around @importFrom - really don't need to use @importFrom that often.

ggmissing 0.0.2.9000 (2016/07/29)

New Feature (under development)

  • geom_missing_point() now works in a way that we expect! Thanks to Miles McBain for working out how to get this to work.

ggmissing 0.0.1.9000 (2016/07/29)

New Feature (under development)

  • tidy summaries for missing data:
    • percent_missing_df returns the percentage of missing data for a data.frame
    • percent_missing_var the percentage of variables that contain missing values
    • percent_missing_case the percentage of cases that contain missing values.
    • table_missing_var table of missing information for variables
    • table_missing_case table of missing information for cases
    • summary_missing_var summary of missing information for variables (counts, percentages)
    • summary_missing_case summary of missing information for variables (counts, percentages)
  • ggmissingcol: plot the missingness in each variable
  • ggmissingrow: plot the missingness in each case
  • ggmissingwhich: plot which columns contain missing data.

- R
Published by njtierney about 9 years ago