naniar (version 0.6.0)

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

Description

To summarise the missing values in a time series object it can be useful to calculate the number of missing values in a given time period. miss_var_span takes a data.frame object, a variable, and a span_every argument and returns a dataframe containing the number of missing values within each span.

Usage

miss_var_span(data, var, span_every)

Arguments

data

data.frame

var

bare unquoted variable name of interest.

span_every

integer describing the length of the span to be explored

Value

dataframe with variables n_miss, n_complete, prop_miss, and prop_complete, which describe the number, or proportion of missing or complete values within that given time span.

See Also

pct_miss_case() prop_miss_case() pct_miss_var() prop_miss_var() pct_complete_case() prop_complete_case() pct_complete_var() prop_complete_var() miss_prop_summary() miss_case_summary() miss_case_table() miss_summary() miss_var_prop() miss_var_run() miss_var_span() miss_var_summary() miss_var_table()

Examples

# NOT RUN {
miss_var_span(data = pedestrian,
             var = hourly_counts,
             span_every = 168)

# }
# NOT RUN {
 library(dplyr)
 pedestrian %>%
   group_by(month) %>%
     miss_var_span(var = hourly_counts,
                   span_every = 168)
# }