My goal is to find the minimum and maximum daily temperatures and add them to a data frame. My current data frame looks like the following:
ROW DATE_TIME TEMP (DEG C)
1 5/1/1999 4.6
2 5/1/1999 3.8
3 5/1/1999 2.9
I am attempting to get the daily range of temperature using this data, but the main issue I run into is having "non-standard" dates. The dataset I'm using is several thousand data points long, so I would like to have a code that does max-min for every 24 rows in order to get the daily variation in temperature.
Thank you!
If you want to calculate it using a running window you can use the function gtools::running() and set the by() and width() arguments to 24.
require(tidyverse)
require(gtools)
set.seed(123)
df <- data.frame(row = c(seq(1, 24*5, by = 1)),
date = as.Date(c(
rep(c("02/25/92"), 24),
rep(c("02/26/92"), 24),
rep(c("02/27/92"), 24),
rep(c("02/28/92"), 24),
rep(c("02/29/92"), 24)),
format = "%m/%d/%y"),
temp = rnorm(24*5, mean = 5, sd = 5))
#Function to calculate the min. and max. of a vector/column
MinMaxFunction <- function(x) {
return(data.frame(min = min(x, na.rm = TRUE),
max = max(x, na.rm = TRUE)))
}
#Calculating the running min. max.
dfRunningMean <- running(df$temp,
fun = MinMaxFunction,
by = 24,
width = 24) %>%
t() %>%
as.data.frame()
dfRunningMean
min max
1:24 -4.833086 13.93457
25:48 -3.433467 15.84478
49:72 -6.545844 15.25042
73:96 -1.103589 11.80326
97:120 -3.33971 15.93666
Or, you can do it with the tidyverse approach, and calculate the min./max. for each date.
require(tidyverse)
df %>%
group_by(date) %>%
summarise(min = min(temp, na.rm = TRUE),
max = max(temp, na.rm = TRUE))
date min max
<date> <dbl> <dbl>
1 1992-02-25 -4.83 13.9
2 1992-02-26 -3.43 15.8
3 1992-02-27 -6.55 15.3
4 1992-02-28 -1.10 11.8
5 1992-02-29 -3.34 15.9