How to pass a dataframe column as an argument in a function using piping?

I'm messing around with the built-in dataset economics in R, and I'm trying to pass a dataframe column as an argument in a function that uses piping (dplyr, %>%). But I'm experiencing some seemingly strange problems. Somehow I can't successfully pass a column name as an argument to the function top_n() within my custom function. Here's how I would subset the 5 countries with the biggest population without a custom functon:

Code 1:

library(dplyr)

df_econ <- economics
df_top_5 <- df_econ %>% top_n(5, pop)
df_top_5

Output 1:

2014-12-01  12122.0 320201  5.0 12.6    8688
2015-01-01  12080.8 320367  5.5 13.4    8979
2015-02-01  12095.9 320534  5.7 13.1    8705
2015-03-01  12161.5 320707  5.2 12.2    8575
2015-04-01  12158.9 320887  5.6 11.7    8549

Wrapped into a custom function, it could look like this:

Code 2:

library(dplyr)

# data
data(economics)
df_econ <- economics

# custom function
fxtop <- function(df, number, column){

  tops <- df %>% top_n(number, column)
  return(tops)
}

# build a df using custom function
df_top_5 <- fxtop(df=df_econ, number=5, column='pop')
df_top_5

Output 2:

1967-07-01  507.4   198712  12.5    4.5 2944
1967-08-01  510.5   198911  12.5    4.7 2945
1967-09-01  516.3   199113  11.7    4.6 2958
1967-10-01  512.9   199311  12.5    4.9 3143
1967-11-01  518.1   199498  12.5    4.7 3066
1967-12-01  525.8   199657  12.1    4.8 3018
1968-01-01  531.5   199808  11.7    5.1 2878
1968-02-01  534.2   199920  12.2    4.5 3001
1968-03-01  544.9   200056  11.6    4.1 2877
1968-04-01  544.6   200208  12.2    4.6 2709

This output has 10 rows and not 5 as expected. I suspect that the argument number=5 is simply ignored and that the number that is actually used is defaulted to 10. The data does not seem to be sorted by 'pop' either.

What I've tried so far:

Attempt 1: hard-code pop and number within the custom function:

library(dplyr)

# data
data(economics)
df_econ <- economics

# custom function
fxtop <- function(df, number, column){

  tops <- df %>% top_n(5, pop)
  return(tops)
}

# build a df using custom function
df_top_5 <- fxtop(df=df_econ, number=5, column='pop')
df_top_5

Attempt 1: Output:

2014-12-01  12122.0 320201  5.0 12.6    8688
2015-01-01  12080.8 320367  5.5 13.4    8979
2015-02-01  12095.9 320534  5.7 13.1    8705
2015-03-01  12161.5 320707  5.2 12.2    8575
2015-04-01  12158.9 320887  5.6 11.7    8549

Attempt 1: Comment

This is the desired output!

Let's see what happens when I'm passing the variables through the function

Attempt 2: pass variables as object instead of string:

library(dplyr)

# data
data(economics)
df_econ <- economics

# custom function
fxtop <- function(df, number, column){

  tops <- df %>% top_n(5, column)
  return(tops)
}

# build a df using custom function
df_top_5 <- fxtop(df=df_econ, number=5, column='pop')
df_top_5

Attempt 2: Output:

Now the output is the same as in the first example. Both variables are seemingly ignored.

So, any suggestions?