Man pages for njtierney/naniar
Data Structures, Summaries, and Visualisations for Missing Data

add_any_missAdd a column describing presence of any missing values
add_label_missingsAdd a column describing if there are any missings in the...
add_label_shadowAdd a column describing whether there is a shadow
add_miss_clusterAdd a column that tells us which "missingness cluster" a row...
add_n_missAdd column containing number of missing data values
add_prop_missAdd column containing proportion of missing data values
add_shadowAdd a shadow column to dataframe
add_shadow_shiftAdd a shadow shifted column to a dataset
add_span_counterAdd a counter variable for a span of dataframe
any-all-na-completeIdentify if there are any or all missing or complete values
any_row_missHelper function to determine whether there are any missings
as_shadowCreate shadows
as_shadow_upsetConvert data into shadow format for doing an upset plot
bind_shadowBind a shadow dataframe to original data
cast_shadowAdd a shadow column to a dataset
cast_shadow_shiftAdd a shadow and a shadow_shift column to a dataset
cast_shadow_shift_labelAdd a shadow column and a shadow shifted column to a dataset
common_na_numbersCommon number values for NA
common_na_stringsCommon string values for NA
draw_keyKey drawing functions
gather_shadowLong form representation of a shadow matrix
geom_miss_pointPlot Missing Data Points
gg_miss_casePlot the number of missings per case (row)
gg_miss_case_cumsumPlot of cumulative sum of missing for cases
gg_miss_fctPlot the number of missings for each variable, broken down by...
gg_miss_spanPlot the number of missings in a given repeating span
gg_miss_upsetPlot the pattern of missingness using an upset plot.
gg_miss_varPlot the number of missings for each variable
gg_miss_var_cumsumPlot of cumulative sum of missing value for each variable
gg_miss_whichPlot which variables contain a missing value
impute_belowImpute data with values shifted 10 percent below range.
impute_below_allImpute data with values shifted 10 percent below range.
impute_below_atScoped variants of 'impute_below'
impute_below_ifScoped variants of 'impute_below'
impute_below.numericImpute numeric values below a range for graphical exploration
impute_factorImpute a factor value into a vector with missing values
impute_fixedImpute a fixed value into a vector with missing values
impute_meanImpute the mean value into a vector with missing values
impute_medianImpute the median value into a vector with missing values
impute_modeImpute the mode value into a vector with missing values
impute_zeroImpute zero into a vector with missing values
is_shadeDetect if this is a shade
label_miss_1dLabel a missing from one column
label_miss_2dlabel_miss_2d
label_missingsIs there a missing value in the row of a dataframe?
mcar_testLittle's missing completely at random (MCAR) test
miss_case_cumsumSummarise the missingness in each case
miss_case_summarySummarise the missingness in each case
miss_case_tableTabulate missings in cases.
miss-pct-prop-defunctProportion of variables containing missings or complete...
miss_prop_summaryProportions of missings in data, variables, and cases.
miss_scan_countSearch and present different kinds of missing values
miss_summaryCollate summary measures from naniar into one tibble
miss_var_cumsumCumulative sum of the number of missings in each variable
miss_var_runFind the number of missing and complete values in a single...
miss_var_spanSummarise the number of missings for a given repeating span...
miss_var_summarySummarise the missingness in each variable
miss_var_tableTabulate the missings in the variables
miss_var_whichWhich variables contain missing values?
nabularConvert data into nabular form by binding shade to it
naniarnaniar: Data Structures, Summaries, and Visualisations for...
naniar-ggprotonaniar-ggproto
n_completeReturn the number of complete values
n_complete_rowReturn a vector of the number of complete values in each row
n_missReturn the number of missing values
n_miss_rowReturn a vector of the number of missing values in each row
n-var-case-completeThe number of variables with complete values
n-var-case-missThe number of variables or cases with missing values
oceanbuoysWest Pacific Tropical Atmosphere Ocean Data, 1993 & 1997.
pct_completeReturn the percent of complete values
pct_missReturn the percent of missing values
pct-miss-complete-casePercentage of cases that contain a missing or complete...
pct-miss-complete-varPercentage of variables containing missings or complete...
pedestrianPedestrian count information around Melbourne for 2016
plotly_helpersPlotly helpers (Convert a geom to a "basic" geom.)
prop_completeReturn the proportion of complete values
prop_complete_rowReturn a vector of the proportion of missing values in each...
prop_missReturn the proportion of missing values
prop-miss-complete-caseProportion of cases that contain a missing or complete...
prop-miss-complete-varProportion of variables containing missings or complete...
prop_miss_rowReturn a vector of the proportion of missing values in each...
recode_shadowAdd special missing values to the shadow matrix
reexportsObjects exported from other packages
replace_na_withReplace NA value with provided value
replace_to_naReplace values with missings
replace_with_naReplace values with missings
replace_with_na_allReplace all values with NA where a certain condition is met
replace_with_na_atReplace specified variables with NA where a certain condition...
replace_with_na_ifReplace values with NA based on some condition, for variables...
riskfactorsThe Behavioral Risk Factor Surveillance System (BRFSS) Survey...
scoped-impute_meanScoped variants of 'impute_mean'
scoped-impute_medianScoped variants of 'impute_median'
set-prop-n-missSet a proportion or number of missing values
shadeCreate new levels of missing
shadow_longReshape shadow data into a long format
shadow_shiftShift missing values to facilitate missing data...
stat_miss_pointstat_miss_point
unbindersUnbind (remove) shadow from data, and vice versa
whereSplit a call into two components with a useful verb name
where_naWhich rows and cols contain missings?
which_are_shadeWhich variables are shades?
which_naWhich elements contain missings?
njtierney/naniar documentation built on March 19, 2024, 9:48 p.m.