Consider the following DataSet;
scd <- read.table(text = "
2019-04-01 10:00:00 | 2019-04-01 12:00:00 | 10
2019-04-02 10:00:00 | 2019-04-02 12:00:00 | 5
2019-04-03 13:00:00 | 2019-04-03 15:00:00 | 7
2019-04-04 16:00:00 | 2019-04-04 19:00:00 | 5
2019-04-05 10:00:00 | 2019-04-05 12:00:00 | 6
2019-04-06 10:00:00 | 2019-04-06 12:00:00 | 5", sep = "|")
colnames(scd) <- c('start_date_ts', 'end_date_ts', 'people_count')
The above code consists of start date and end date with time, with the assumption that for each hour, I can expect a count increase mentioned in the people count column.
For Example, take Row 1, it says that from 10 AM to 12PM, I can expect count to increase by 10.
2019-04-01 10:00:00 = 10 + Actual Data
2019-04-01 11:00:00 = 10 + Actual Data
2019-04-01 12:00:00 = 10 + Actual Data
Actual Data;
fc_data <- read.table(text = "
2019-04-01 10:00:00 | 10
2019-04-01 12:00:00 | 5
2019-04-04 19:00:00 | 5
2019-04-05 12:00:00 | 6
2019-04-06 08:00:00 | 3", sep = "|")
colnames(fc_data) <- c('pred_t', 'fpc')
I am expecting the following outcome; (from the fc_data)
Row 1 - 10 + 10 = 20
Row 2 - 5 + 10 = 15
Row 3 - 5 + 5 = 10
Row 4 - 6 + 6 = 12
Row 5 - 3 + 0 = 3
I want the code to run through each row and match with the start and end time and provide me with the output provided above.
My Approach;
fc_data$events_pc <- with(fc_data, ifelse(fc_data$pred_t == scd$start_date_ts | fc_data$pred_t == scd$end_date_ts &
fc_data$pred_t == scd$end_date_ts,
fc_data$fpc + scd$people_count, fc_data$fpc + 0))
Although, I get some of the rows added up, the others actually don't match up. I have searched the Stack for some information, but, I am unable to find any. Any inputs will be very helpful.
We can use mapply
and match the start_date_ts
and end_date_ts
from scd
with pred_t
, get the corresponding people_count
and add it to fpc
.
mapply(function(x, y) {
inds <- x >= scd$start_date_ts & x <= scd$end_date_ts
if (any(inds))
y + scd$people_count[inds]
else
y
}, fc_data$pred_t, fc_data$fpc)
#[1] 20 15 10 12 3
Make sure the date-time variable are in POSIXct
format, if they are not you need to change them.
fc_data$pred_t <- as.POSIXct(fc_data$pred_t)
scd[1:2] <- lapply(scd[1:2], as.POSIXct)
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