Loop through dataframe rows and add value in a new column (R)

Question

I have a dataframe (df) with a column of Latitude (Lat), and I need to match up the corresponding Longitude value (based off relationships in another dataset). New column name is 'Long_matched'.

Here, I am trying to write a new value in the column 'Long_matched' at the corresponding row to latitudes between -33.9238 and -33.9236. The data in 'Lat' has many more decimal places (e.g: -33.9238026666667, -33.9236026666667, etc.). As I will be applying this code to multiple datasets over the same geographical location (hence the long decimals will vary slightly), I want to write Longitude values which fall within a a 0.0002 degree range.

Some attempts of code I have tried include:

df$Long_matched <- ifelse(df$Lat< -33.9236 & df$Lat> -33.9238, 151.2279 , "N/A")

or

df$Long_matched[df$Lat< -33.9236 & df$Lat> -33.9238] <- 151.2279

I think I need to use a for loop to loop through the rows and an if statement, but struggling to figure this out - any help would be appreciated!

Resulting output should look something like this:

Lat                   Long_matched
-33.9238026666667     151.2279
-33.9236026666667     (new long value will go here)

Are you trying to do the comparison between adjacent elements of 'Lat' ? — akrun
– akrun, Commented Jun 7, 2018 at 2:38
Post a few rows of example input. Your code is confusing because your first line modifies df and your second line modifies a different data frame named df_avg... probably you just need to merge(df1, df2)? But very hard to tell without sample inputs and desired output. — Gregor Thomas
– Gregor Thomas, Commented Jun 7, 2018 at 2:39
No, I just want to add a new value in the 'Long_matched' column in the row that matches particular 'Lat' values. I already know what the value I want to add is. — Imogen
– Imogen, Commented Jun 7, 2018 at 2:39
If you use "N/A" the entire column will be coerced to class character. — Rui Barradas
– Rui Barradas, Commented Jun 7, 2018 at 4:18

Melissa Key · Accepted Answer · 2018-06-07 03:38:49Z

Everything said in the comments applies, but here is a trick you can try: In the following code, you will need to replace text with numbers.

Latitude_breaks <- seq(min_latitude, max_latitude, 0.0002) # you need to replace `min_latitude`, `max_latitude`, and `increment` with numbers
Longitude_values <- seq(first, last, increment) # you need to replace `first`, `last` and `increment` with numbers
df <- within(df, {
  # make a categorical version of `Lat`
  Lat_cat <- cut(Lat, Latitude_breaks)
  Long_matched <- Longitude_values[Lat_cat]
})

A few notes:

the values between min_latitude and min_latitude + 1 will be assigned to the values of Longitude marked first.
The length of Latitude_beaks should be one more than the length of Longitude_values.
Values of Lat outside of Latitude_breaks will becomes NAs.

This works by exploiting a nice feature of factors - they are stored as integers. So we can use them to index another vector - in this case, Longitude_values.

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