I have to create a dataframe containing data from a list of sensors between certain date period:
DATE SENSOR1 SENSOR2 SENSOR3 SENSOR4
2020-04-20 00:00:00 1015 19.88 95.80 9.020
2020-04-20 00:10:00 1015 19.84 96.10 8.970
2020-04-20 00:20:00 1015 19.84 96.40 9.010
2020-04-20 00:30:00 1015 19.81 96.60 9.210
2020-04-20 00:40:00 1015 19.79 96.80 9.700
2020-04-20 00:50:00 1015 19.81 97.00 8.870
Initially, I create a dataframe with 1 column ( DATE : rows containing all date between specified dates, with 10 minutes intervals). Normally it can have thousands of rows, but in order to reproduce a example we can keep it simple:
periods <- data.frame(DATE = c("2020-04-20 00:00:00","2020-04-20 00:10:00","2020-04-20 00:20:00","2020-04-20 00:30:00","2020-04-20 00:40:00","2020-04-20 00:50:00"))
I have a list of sensor -> ID, so inside for loop I iterate all the sensors, querying my database returning DATE and VALUE from each one. The problem is, a sensor can have 2 or more id's, depending on which date the data is stored.
ID SENSORNAME
1 SENSOR1 <- row that has data from SENSOR1 between 2020-04-20 00:00:00 and 2020-04-20 00:20:00
2 SENSOR2 ...
3 SENSOR3 ...
4 SENSOR4 ...
5 SENSOR1 <- row that has data from SENSOR1 between 2020-04-20 00:30:00 and 2020-04-20 00:50:00
6 SENSOR2 ...
7 SENSOR3 ...
8 SENSOR4 ...
Original code:
for (i in 1:length(sensors$ID)) {
sensor <- dbGetQuery(con, paste0("SELECT DATE, VALUE FROM MEASURES WHERE DATE between '2020-04-20 00:00:00' and '2020-04-20 00:50:00' AND ID= ",sensors$ID[i]," ORDER BY DATE ASC"))
# getting rid of milliseconds
sensor$DATE <- as.character(round_date(sensor$DATE, "minute"))
# Renaming the column with sensor's name
names(sensor) <- c("DATE", sensors$SENSORNAME[i])
periods <- merge(periods,sensor,by="DATE",all = TRUE)
rm(sensor)
}
Since you can't query my database for data, this example can be reproducible by creating 2 data.frames manually
periods <- data.frame(DATE= c("2020-04-20 00:00:00","2020-04-20 00:10:00","2020-04-20 00:20:00","2020-04-20 00:30:00","2020-04-20 00:40:00","2020-04-20 00:50:00"), SENSOR1= c(1015, 1015, 1015, NA, NA, NA), SENSOR2= c(19.88, 19.84, 19.84, NA, NA, NA), SENSOR3= c(95.80, 96.10, 96.40, NA, NA, NA), SENSOR4= c(9.020, 8.970, 9.010, NA, NA, NA))
sensor <- data.frame(DATE= c("2020-04-20 00:00:00","2020-04-20 00:10:00","2020-04-20 00:20:00","2020-04-20 00:30:00","2020-04-20 00:40:00","2020-04-20 00:50:00"), SENSOR1= c(NA, NA, NA, 1010, 1010, 1010))
After the 4th iteration, it starts to add a suffix on column names, looking something like this:
DATE SENSOR1.x SENSOR2.x SENSOR3.x SENSOR4.x SENSOR1.y SENSOR2.y SENSOR3.y SENSOR4.y
2020-04-20 00:00:00 1015 19.88 95.80 9.020 NA NA NA NA
2020-04-20 00:10:00 1015 19.84 96.10 8.970 NA NA NA NA
2020-04-20 00:20:00 1015 19.84 96.40 9.010 NA NA NA NA
2020-04-20 00:30:00 NA NA NA NA 1015 19.81 96.60 9.210
2020-04-20 00:40:00 NA NA NA NA 1015 19.79 96.80 9.700
2020-04-20 00:50:00 NA NA NA NA 1015 19.81 97.00 8.870
Any idea on how to merge this properly, or fixing it after the dataframe is generated?
You can use pivot_longer
from tidyr
to put everything in a column and rbind
everything before using pivot_wider
to put everything back in wide format. You also need to remove NAs using na.omit()
.
library(tidyr)
periods %>%
pivot_longer(-DATE) %>%
rbind(sensor %>%
pivot_longer(-DATE) ) %>%
na.omit() %>%
pivot_wider(names_from = name, values_from = value)
Joining, by = c("DATE", "name", "value")
# A tibble: 6 x 5
DATE SENSOR1 SENSOR2 SENSOR3 SENSOR4
<fct> <dbl> <dbl> <dbl> <dbl>
1 2020-04-20 00:00:00 1015 19.9 95.8 9.02
2 2020-04-20 00:10:00 1015 19.8 96.1 8.97
3 2020-04-20 00:20:00 1015 19.8 96.4 9.01
4 2020-04-20 00:30:00 1010 NA NA NA
5 2020-04-20 00:40:00 1010 NA NA NA
6 2020-04-20 00:50:00 1010 NA NA NA
DATA
periods <- data.frame(DATE= c("2020-04-20 00:00:00","2020-04-20 00:10:00","2020-04-20 00:20:00","2020-04-20 00:30:00","2020-04-20 00:40:00","2020-04-20 00:50:00"), SENSOR1= c(1015, 1015, 1015, NA, NA, NA), SENSOR2= c(19.88, 19.84, 19.84, NA, NA, NA), SENSOR3= c(95.80, 96.10, 96.40, NA, NA, NA), SENSOR4= c(9.020, 8.970, 9.010, NA, NA, NA))
sensor <- data.frame(DATE= c("2020-04-20 00:00:00","2020-04-20 00:10:00","2020-04-20 00:20:00","2020-04-20 00:30:00","2020-04-20 00:40:00","2020-04-20 00:50:00"), SENSOR1= c(NA, NA, NA, 1010, 1010, 1010))
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