## Visualisation

Visualise missing data

geom_miss_point()

geom_miss_point

gg_miss_case()

Plot the number of missings per case (row)

gg_miss_case_cumsum()

Plot of cumulative sum of missing for cases

gg_miss_fct()

Plot the number of missings for each variable, broken down by a factor

gg_miss_span()

Plot the number of missings in a given repeating span

gg_miss_var()

Plot the number of missings for each variable

gg_miss_var_cumsum()

Plot of cumulative sum of missing value for each variable

gg_miss_which()

Plot which variables contain a missing value

## Data structures for missing data

Creation and Manipulation of Shadow Matrices

as_shadow()

as_shadow(<data.frame>)

as_shadow_upset()

Convert data into shadow format for doing an upset plot

bind_shadow()

Bind a shadow dataframe to original data

gather_shadow()

Long form representation of a shadow matrix

shadow_shift()

Shift missing values to facilitate missing data exploration/visualisation

shadow_shift(<numeric>)

Shift (impute) numeric values for graphical exploration

## Numerical Summaries

Provide tidy data frame summaries of missingness

miss_case_pct() complete_case_pct()

Percentage of cases that contain a missing or complete values.

miss_case_prop() complete_case_prop()

Proportion of cases that contain a missing or complete values.

miss_var_pct() complete_var_pct()

Percentage of variables containing missings or complete values

miss_var_prop() complete_var_prop()

Proportion of variables containing missings or complete values

miss_case_summary()

Summarise the missingness in each case

miss_case_table()

Tabulate missings in cases.

miss_prop_summary()

Proportions of missings in data, variables, and cases.

miss_scan_count()

Search and present different kinds of missing values

miss_summary()

Collate summary measures from naniar into one tibble

miss_var_run()

Find the number of missing and complete values in a single run

miss_var_span()

Summarise the number of missings for a given repeating span on a variable

miss_var_summary()

Summarise the missingness in each variable

miss_var_table()

Tabulate the missings in the variables

miss_var_which()

Which variables contain missing values?

## Handy helpers

Handy helpers

n_miss()

Return the number of missing values

n_complete()

Return the number of complete values

prop_miss()

Return the proportion of missing values

prop_complete()

Return the proportion of complete values

pct_miss()

Return the percent of missing values

pct_complete()

Return the percent of complete values

Add missing data summaries/tool columns

add_any_miss()

Add a column describing presence of any missing values

add_label_missings()

Add a column describing if there are any missings in the dataset

add_label_shadow()

Add a column describing whether there is a shadow

add_miss_cluster()

Add a column that tells us which "missingness cluster" a row belongs to

add_n_miss()

Add column containing number of missing data values

add_prop_miss()

Add column containing proportion of missing data values

add_shadow()

add_shadow_shift()

Add a shadow shifted column to a dataset

add_span_counter()

Add a counter variable for a span of dataframe

Add shadow information to the dataframe while reducing it to the variables of interest

cast_shadow()

Add a shadow column to a dataset

cast_shadow_shift()

Add a shadow and a shadow_shift column to a dataset

cast_shadow_shift_label()

Add a shadow column and a shadow shifted column to a dataset

## Misc helpers

Misc helpers

all_row_complete()

Helper function to determine whether all rows are complete

all_row_miss()

Helper function to determine whether all rows are missing

any_row_miss()

Helper function to determine whether there are any missings

label_miss_1d()

Label a missing from one column

label_miss_2d()

label_miss_2d

label_missings()

Is there a missing value in the row of a dataframe?

where_na()

Which rows and cols contain missings?

which_na()

Which elements contain missings?