CODEWITHSUNDEEP
rfunctionmathlapply
JAG2024
JAG2024

Reputation: 4317

Manipulate function within lapply

This should be an easy question for someone out there...

I have a data frame that looks like this:

df1
 longitude lattitude 10000  5 1.5 1.4 1.3 1.2 1 0.5 0.1 0.001
0 -119.8304  34.44190   107 14   8   8   8   8 7   5   5     1
1 -119.6768  34.41962   107 19   5   5   5   5 5   3   2     1
2 -119.7162  34.41911   107 25   9   8   8   5 4   1   1     1
3 -119.7439  34.44017   107 22   7   7   6   5 5   2   1     1

Which was created by this code:

library(geosphere)

df1 <- data.frame(longitude=c(-119.8304, -119.6768, -119.7162, -119.7439, -120.4406, -119.5296, -120.4198, -119.8221, -119.7269, -120.4252, -120.4573, -120.4581),
              lattitude=c(34.44, 34.42, 34.42, 34.44, 34.64, 34.41, 34.94, 34.44, 34.44, 34.97, 34.65, 34.65))
boundary <- c(10000, 5, 1.5, 1.4, 1.3, 1.2, 1, 0.5, 0.1, 0.001)
names(boundary) <- boundary
df1 <- cbind(df1, lapply(boundary, function(x) rowSums(distm(df1, fun = distHaversine) / 1000 <= x)))

But I need the values in the data frame df1 to be manipulated such that the value in all the columns except latitude and longitude will get divided by pi*x^2 (pi times x squared). Can I use lapply in this case?

The output should be like:

df1
longitude lattitude    10000  5     1.5   1.4 1.3 1.2 1 0.5 0.1 0.001
0 -119.8304  34.44190   0     0.177 1.12  1.29 etc...

Upvotes: 3

Views: 65

Answers (1)

akrun
akrun

Reputation: 887108

We can use setdiff to get the names of the dataset except the 'longitude', 'lattitude' column. Then loop through the subset of columns, do the calculation, and update the dataset

j1 <- setdiff(names(df1), c("longitude", "lattitude"))
df1[j1] <- lapply(df1[j1], function(x) x/(pi*x^2))

Or we can use tidyverse

library(dplyr)
df1 %>%
     mutate_at(vars(-matches("longitude", "lattitude")), funs(./(pi*.^2)))

Upvotes: 2

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