Man pages for njtierney/naniar
Data Structures, Summaries, and Visualisations for Missing Data
| 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... |
| 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... |
| 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 a shadow column to dataframe |
| add_shadow_shift | Add a shadow shifted column to a dataset |
| add_span_counter | Add a counter variable for a span of dataframe |
| any-all-na-complete | Identify if there are any or all missing or complete values |
| any_row_miss | Helper function to determine whether there are any missings |
| as_shadow | Create shadows |
| as_shadow_upset | Convert data into shadow format for doing an upset plot |
| bind_shadow | Bind a shadow dataframe to original data |
| 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 |
| common_na_numbers | Common number values for NA |
| common_na_strings | Common string values for NA |
| draw_key | Key drawing functions |
| gather_shadow | Long form representation of a shadow matrix |
| geom_miss_point | Plot Missing Data Points |
| 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... |
| gg_miss_span | Plot the number of missings in a given repeating span |
| gg_miss_upset | Plot the pattern of missingness using an upset plot. |
| 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 |
| impute_below | Impute data with values shifted 10 percent below range. |
| impute_below_all | Impute data with values shifted 10 percent below range. |
| impute_below_at | Scoped variants of 'impute_below' |
| impute_below_if | Scoped variants of 'impute_below' |
| impute_below.numeric | Impute numeric values below a range for graphical exploration |
| impute_factor | Impute a factor value into a vector with missing values |
| impute_fixed | Impute a fixed value into a vector with missing values |
| impute_mean | Impute the mean value into a vector with missing values |
| impute_median | Impute the median value into a vector with missing values |
| impute_mode | Impute the mode value into a vector with missing values |
| impute_zero | Impute zero into a vector with missing values |
| is_shade | Detect if this is a shade |
| 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? |
| mcar_test | Little's missing completely at random (MCAR) test |
| miss_case_cumsum | Summarise the missingness in each case |
| miss_case_summary | Summarise the missingness in each case |
| miss_case_table | Tabulate missings in cases. |
| miss-pct-prop-defunct | Proportion of variables containing missings or complete... |
| 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_cumsum | Cumulative sum of the number of missings in each variable |
| miss_var_run | Find the number of missing and complete values in a single... |
| miss_var_span | Summarise the number of missings for a given repeating span... |
| 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? |
| nabular | Convert data into nabular form by binding shade to it |
| naniar | naniar: Data Structures, Summaries, and Visualisations for... |
| naniar-ggproto | naniar-ggproto |
| n_complete | Return the number of complete values |
| n_complete_row | Return a vector of the number of complete values in each row |
| n_miss | Return the number of missing values |
| n_miss_row | Return a vector of the number of missing values in each row |
| n-var-case-complete | The number of variables with complete values |
| n-var-case-miss | The number of variables or cases with missing values |
| oceanbuoys | West Pacific Tropical Atmosphere Ocean Data, 1993 & 1997. |
| pct_complete | Return the percent of complete values |
| pct_miss | Return the percent of missing values |
| pct-miss-complete-case | Percentage of cases that contain a missing or complete... |
| pct-miss-complete-var | Percentage of variables containing missings or complete... |
| pedestrian | Pedestrian count information around Melbourne for 2016 |
| plotly_helpers | Plotly helpers (Convert a geom to a "basic" geom.) |
| prop_complete | Return the proportion of complete values |
| prop_complete_row | Return a vector of the proportion of missing values in each... |
| prop_miss | Return the proportion of missing values |
| prop-miss-complete-case | Proportion of cases that contain a missing or complete... |
| prop-miss-complete-var | Proportion of variables containing missings or complete... |
| prop_miss_row | Return a vector of the proportion of missing values in each... |
| recode_shadow | Add special missing values to the shadow matrix |
| reexports | Objects exported from other packages |
| replace_na_with | Replace NA value with provided value |
| replace_to_na | Replace values with missings |
| replace_with_na | Replace values with missings |
| replace_with_na_all | Replace all values with NA where a certain condition is met |
| replace_with_na_at | Replace specified variables with NA where a certain condition... |
| replace_with_na_if | Replace values with NA based on some condition, for variables... |
| riskfactors | The Behavioral Risk Factor Surveillance System (BRFSS) Survey... |
| scoped-impute_mean | Scoped variants of 'impute_mean' |
| scoped-impute_median | Scoped variants of 'impute_median' |
| set-prop-n-miss | Set a proportion or number of missing values |
| shade | Create new levels of missing |
| shadow_long | Reshape shadow data into a long format |
| shadow_shift | Shift missing values to facilitate missing data... |
| stat_miss_point | stat_miss_point |
| unbinders | Unbind (remove) shadow from data, and vice versa |
| where | Split a call into two components with a useful verb name |
| where_na | Which rows and cols contain missings? |
| which_are_shade | Which variables are shades? |
| which_na | Which elements contain missings? |
