Questions about Spatial Join in R - r

Question

I'm running into some trouble while attempting a spatial join between a shapefile and a data table in csv.
Here's what my data looks like:
Point Shapefile's attribute data (StudentID):
ID Address Long Lat
123.00 street long lat
456.00 street long lat
789.01 street long lat
223.00 street long lat
412.02 street long lat
Data Table (Table):
ID Name Age School
123.00 name age school
456.00 name age school
789.01 name age school
223.00 name age school
412.02 name age school
Important note: StudentID contains roughly 500 records, while the Table only has 250. Some records in StudentID will NOT be matched.
Problem 1:
I have an excel file, which I converted to csv for importing into R. While running the join, I noticed that some of my data format changed in the ID column (so 123.00 would become 123; 456.00 to 456; 789.01 is the same). However, when I opened csv file in notepad the formatting is correct. I tried reading the table as a .txt file, but no luck. Does anyone know why this happens and what are some ways to overcome this?
Because I couldn't join the data based on an exact match, I decided to try a partial join because the IDS are unique regardless of the last 2 digits, which led me to Problem 2...
Problem 2:
Here is what I used to join the two:
StudentID#data = data.frame(StudentID#data, data[charmatch(StudentID#data$ID,Table$ID,])
This joined the data, but also, as expected, returned rows with NAs. I used na.omit to remove the rows and the resulting data contained all the ones that matched. However, in the shapefile, ALL of my points are still there. Why did those dots remain when the records have been removed?

Answer 1

Problem 1:
Excel sometimes exports floating values using a comma , as decimal separator. This can lead to problems in csv imports. Make sure that excel uses points . for decimal separators, or specify the separator in importing, i.e. read.csv('file.csv', sep=';').
Problem 2:
If you want to remove points with na values from a shapefile, you need a logical vector to select the rows you dont want anymore. Here is an example of how this could look like (assuming your shapefile was named student_points)
student_points <- student_points[!is.na(student_points#data$age), ]