R filtering/selecting data by POSIXct time and a condition

Question

I have made measurements of temperature in a high time resolution of 10 minutes on different urban Tree species, whose reactions should be compared. Therefore I am researching especially periods of heat. The Task that I fail to do on my Dataset is to choose complete days from a maximum value. E.G. Days where there is one measurement above 30 °C should be subsetted from my Dataframe completely. Below you find a reproducible example that should illustrate my problem:

In my Measurings Dataframe I have calculated a column indicating wether the individual Measurement is above or below 30°C. I wanted to use that column to tell other functions wether they should pick a day or not to produce a New Dataframe. When anytime of the day the value is above 30 ° C i want to include it by Date from 00:00 to 23:59 in that New Dataframe for further analyses.

start <- as.POSIXct("2018-05-18 00:00", tz = "CET")
tseq <- seq(from = start, length.out = 1000, by = "hours")

Measurings <- data.frame(
  Time = tseq,
  Temp = sample(20:35,1000, replace = TRUE),
  Variable1 = sample(1:200,1000, replace = TRUE),
  Variable2 = sample(300:800,1000, replace = TRUE)
)

Measurings$heat30 <- ifelse(Measurings$Temp > 30,"heat", "normal")

Measurings$otheroption30 <- ifelse(Measurings$Temp > 30,"1", "0")

The example is yielding a Dataframe analog to the structure of my Data:

head(Measurings)

                 Time Temp Variable1 Variable2 heat30 otheroption30
1 2018-05-18 00:00:00   28        56       377 normal             0
2 2018-05-18 01:00:00   23        65       408 normal             0
3 2018-05-18 02:00:00   29        78       324 normal             0
4 2018-05-18 03:00:00   24       157       432 normal             0
5 2018-05-18 04:00:00   32       129       794   heat             1
6 2018-05-18 05:00:00   25        27       574 normal             0

So how do I subset to get a New Dataframe where all the days are taken where at least one entry is indicated as "heat"?

I know that for example dplyr:filter could filter the individual entries (row 5 in the head of the example). But how could I tell to take all the day 2018-05-18?

I am quite new to analyzing Data with R so I would appreciate any suggestions on a working solution to my problem. dplyris what I have been using for quite some tasks, but I am open to whatever works.

Thanks a lot, Konrad

Answer 1

Below is one possible solution using the dataset provided in the question. Please note that this is not a great example as all days will probably include at least one observation marked as over 30 °C (i.e. there will be no days to filter out in this dataset but the code should do the job with the actual one).

# import packages
library(dplyr)
library(stringr)

# break the time stamp into Day and Hour
time_df <- as_data_frame(str_split(Measurings$Time, " ", simplify = T))

# name the columns
names(time_df) <- c("Day", "Hour")

# create a new measurement data frame with separate Day and Hour columns
new_measurings_df <- bind_cols(time_df, Measurings[-1])

# form the new data frame by filtering the days marked as heat
new_df <- new_measurings_df %>%
  filter(Day %in% new_measurings_df$Day[new_measurings_df$heat30 == "heat"])

To be more precise, you are creating a random sample of 1000 observations varying between 20 to 35 for temperature across 40 days. As a result, it is very likely that every single day will have at least one observation marked as over 30 °C in your example. Additionally, it is always a good practice to set seed to ensure reproducibility.

Answer 2

Create variable which specify which day (droping hours, minutes etc.). Iterate over unique dates and take only such subsets which in heat30 contains "heat" at least once:

Measurings <- Measurings %>% mutate(Time2 = format(Time, "%Y-%m-%d"))

res <- NULL
newdf <- lapply(unique(Measurings$Time2), function(x){

  ss <- Measurings %>% filter(Time2 == x) %>% select(heat30) %>% pull(heat30) # take heat30 vector
  rr <- Measurings %>% filter(Time2 == x) # select date x

  # check if heat30 vector contains heat value at least once, if so bind that subset 
  if(any(ss == "heat")){
    res <- rbind(res, rr)
  }
  return(res)

}) %>% bind_rows()