Generating New Columns by Group But Getting Unknown Results from World Bank Data

Question

I am trying to use a simple dplyr command to group World Bank data and then add all of the country populations for a given year into a new column. No matter what I seem to do I can't get anything except a column of NAs. I've even tried base R aggregate() and nothing seems to work? Not entirely sure what is going on--I converted all of the World Bank data to numeric data but nothing is coming out the other side.

The function I'm using is very similar to this: How to create a new variable that is the sum of a column, by group, in R?

df %>%
  group_by(group) %>%
  mutate(sum = sum(variable)) %>%
  ungroup()

Thank you!

Edit: also, the code works on any other dataset, so I'm not sure what I did wrong.

Do you have NAs in the variable column? Trying sum(variable, na.rm=TRUE) will probably get you over one hurdle but being aware of where those NAs come from is usually important — Dubukay, Jan 13 '22 at 23:25

score 1 · Accepted Answer · answered Jan 14 '22 at 12:55

1

Have you got NA's in your variable column?

If so, try this to get the sum ignoring missing values:

df %>%
  group_by(group) %>%
  mutate(sum = sum(variable, na.rm=TRUE)) %>%
  ungroup()

answered Jan 14 '22 at 12:55

rw2

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This did work! I appreciate it, I was able to try this late last night. – rulesforpower Jan 14 '22 at 15:40

Generating New Columns by Group But Getting Unknown Results from World Bank Data

1 Answers1