Nothing
## ---- fig.width=7-------------------------------------------------------------
library(padr)
coffee
## ---- fig.width=7, message = FALSE--------------------------------------------
library(ggplot2); library(dplyr)
coffee %>%
thicken('day') %>%
group_by(time_stamp_day) %>%
summarise(day_amount = sum(amount)) %>%
pad() %>%
fill_by_value() %>%
ggplot(aes(time_stamp_day, day_amount)) + geom_line()
## -----------------------------------------------------------------------------
coffee2 <- coffee %>% thicken('day')
coffee2$time_stamp %>% get_interval()
coffee2$time_stamp_day %>% get_interval()
## -----------------------------------------------------------------------------
to_thicken <- data.frame(day_var = as.Date(c('2016-08-12', '2016-08-13',
'2016-08-26', '2016-08-29')))
to_thicken %>% thicken(interval = "week")
to_thicken %>% thicken(interval = "4 days")
## -----------------------------------------------------------------------------
head(emergency)
## -----------------------------------------------------------------------------
emergency %>% filter(title == 'EMS: OVERDOSE') %>%
thicken('day',
start_val = as.POSIXct('2015-12-11 08:00:00', tz = 'EST'),
colname = 'daystart') %>%
group_by(daystart) %>%
summarise(nr_od = n()) %>%
head()
## -----------------------------------------------------------------------------
account <- data.frame(day = as.Date(c('2016-10-21', '2016-10-23', '2016-10-26')),
balance = c(304.46, 414.76, 378.98))
account %>% pad()
## -----------------------------------------------------------------------------
account %>% pad() %>% tidyr::fill(balance)
## -----------------------------------------------------------------------------
account %>% pad('hour', start_val = as.POSIXct('2016-10-20 22:00:00')) %>% head()
## -----------------------------------------------------------------------------
grouping_df <- data.frame(
group = rep(c("A", "B"), c(3, 3)),
date = as.Date(c("2017-10-02", "2017-10-04", "2017-10-06", "2017-10-01",
"2017-10-03", "2017-10-04")),
value = rep(2, 6)
)
grouping_df %>%
pad(group = "group")
## -----------------------------------------------------------------------------
grouping_df %>%
group_by(group) %>%
do(pad(.))
## -----------------------------------------------------------------------------
counts <- data.frame(x = as.Date(c('2016-11-21', '2016-11-23', '2016-11-24')),
y = c(2, 4, 4)) %>% pad
counts %>% fill_by_value()
counts %>% fill_by_value(value = 42)
counts %>% fill_by_function(fun = mean)
counts %>% fill_by_prevalent()
## ---- fig.width=7-------------------------------------------------------------
emergency %>%
thicken("hour", "h") %>%
count(h) %>%
slice(1:24) %>%
mutate(h_center = center_interval(h)) %>%
ggplot(aes(h_center, n)) + geom_bar(stat = "identity")
## ---- message=FALSE-----------------------------------------------------------
emergency %>%
filter(title == "EMS: HEAD INJURY") %>%
thicken("6 hour", "hour6") %>%
count(hour6) %>%
pad() %>%
fill_by_value() %>%
mutate(hour6_fmt =
format_interval(hour6, start_format = "%Hh", sep = "-")) %>%
ggplot(aes(hour6_fmt, n)) +
geom_boxplot()
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