R selecting rows from dataframe using logical indexing: accessing columns by `$` vs `[]` - r

Question

I have a simple R data.frame object df. I am trying to select rows from this dataframe based on logical indexing from a column col in df.
I am coming from the python world where during similar operations i can either choose to select using df[df[col] == 1] or df[df.col == 1] with the same end result.
However, in the R data frame df[df$col == 1] gives an incorrect result compared to df[df[,col] == 1] (confirmed by summary command). I am not able to understand this difference as from links like http://adv-r.had.co.nz/Subsetting.html it seems that either way is ok. Also, str command on df$col and df[, col] shows the same output.
Is there any guidelines about when to use $ vs [] operator ?
Edit:
digging a little deeper and using this question as reference, it seems like the following code works correctly
df[which(df$col == 1), ]
however, not clear how to guard against NA and when to use which

Answer 1

You confused many things.
In
df[,col]
col should be the column number. For example,
col = 2
x = df[,col]
would select the second column and store it to x.
In
df$col
col should be the column name. For example,
df=data.frame(aa=1:5,bb=10:14)
x = df$bb
would select the second column and store it to x. But you cannot write df$2.
Finally,
df[[col]]
is the same as df[,col] if col is a number. If col is a character ("character" in R means the same as string in other languages), then it selects the column with this name. Example:
df=data.frame(aa=1:5,bb=10:14)
foo = "bb"
x = df[[foo]]
y = df[[2]]
z = df[["bb"]]
Now x, y, and z are all contain the copy of the second column of df.
The notation foo[[bar]] is from lists. The notation foo[,bar] is from matrices. Since dataframe has features of both matrix and list, it can use both.

Answer 2

Use $ when you want to select one specific column by name df$col_name.
Use [] when you want to select one or more columns by number:
df[,1] # select column with index 1
df[,1:3]# select columns with indexes 1 to 3
df[,c(1,3:5,7)] # select columns with indexes 1, 3 to 5 and 7.
[[]] is mostly for lists.
EDIT: df[which(df$col == 1), ] works because which function creates a logical vector which checks if the column index is equal to 1 (true) or not (false). This logical vector is passed to df[] and only true value is shown.
Remove rows with NAs (missing values) in data.frame - to find out more about how to deal with missing values. It is always a good practice to exclude missing values from dataset.