gg_miss_span is a replacement function to
imputeTS::plotNA.distributionBar(tsNH4, breaksize = 100), which shows the
number of missings in a given span, or breaksize. A default minimal theme
is used, which can be customised as normal for ggplot.
gg_miss_span(data, var, span_every, facet)
| data | data.frame |
|---|---|
| var | a bare unquoted variable name from |
| span_every | integer describing the length of the span to be explored |
| facet | (optional) a single bare variable name, if you want to create a faceted plot. |
ggplot2 showing the number of missings in a span (window, or breaksize)
geom_miss_point() gg_miss_case() gg_miss_case_cumsum gg_miss_fct() gg_miss_var() gg_miss_var_cumsum() gg_miss_which()
#> # A tibble: 13 x 6 #> span_counter n_miss n_complete prop_miss prop_complete n_in_span #> <int> <int> <int> <dbl> <dbl> <int> #> 1 1 0 3000 0 1 3000 #> 2 2 0 3000 0 1 3000 #> 3 3 1 2999 0.000333 1.00 3000 #> 4 4 121 2879 0.0403 0.960 3000 #> 5 5 503 2497 0.168 0.832 3000 #> 6 6 555 2445 0.185 0.815 3000 #> 7 7 190 2810 0.0633 0.937 3000 #> 8 8 0 3000 0 1 3000 #> 9 9 1 2999 0.000333 1.00 3000 #> 10 10 0 3000 0 1 3000 #> 11 11 0 3000 0 1 3000 #> 12 12 745 2255 0.248 0.752 3000 #> 13 13 432 1268 0.254 0.746 1700if (FALSE) { library(ggplot2) gg_miss_span(pedestrian, hourly_counts, span_every = 3000) gg_miss_span(pedestrian, hourly_counts, span_every = 3000, facet = sensor_name) # works with the rest of ggplot gg_miss_span(pedestrian, hourly_counts, span_every = 3000) + labs(x = "custom") gg_miss_span(pedestrian, hourly_counts, span_every = 3000) + theme_dark() }