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I have a variable with the same name as a column in a dataframe:
df <- data.frame(a=c(1,2,3), b=c(4,5,6)) b <- 5 I want to get the rows where df$b == b, but dplyr interprets this as df$b == df$b:
df %>% filter(b == b) # interpreted as df$b == df$b # a b # 1 1 4 # 2 2 5 # 3 3 6 If I change the variable name, it works:
B <- 5 df %>% filter(b == B) # interpreted as df$b == B # a b # 1 2 5 I'm wondering if there is a better way to tell filter that b refers to an outside variable.
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%>% is called the forward pipe operator in R. It provides a mechanism for chaining commands with a new forward-pipe operator, %>%. This operator will forward a value, or the result of an expression, into the next function call/expression. It is defined by the package magrittr (CRAN) and is heavily used by dplyr (CRAN).
The filter() function is used to subset a data frame, retaining all rows that satisfy your conditions. To be retained, the row must produce a value of TRUE for all conditions. Note that when a condition evaluates to NA the row will be dropped, unlike base subsetting with [ .
In this, first, pass your dataframe object to the filter function, then in the condition parameter write the column name in which you want to filter multiple values then put the %in% operator, and then pass a vector containing all the string values which you want in the result.
The filter() method in R is used to subset a data frame based on a provided condition. If a row satisfies the condition, it must produce TRUE . Otherwise, non-satisfying rows will return NA values. Hence, the row will be dropped.
Recently I have found this to be an elegant solution to this problem, although I'm just starting to wrap my head around how it works.
df %>% filter(b == !!b)
which is syntactic sugar for
df %>% filter(b == UQ(b))
A high-level sense of this is that the UQ (un-quote) operation causes its contents to be evaluated before the filter operation, so that it's not evaluated within the data.frame.
This is described in this chapter of Advanced R, on 'quasi-quotation'. This chapter also includes a few solutions to similar problems related to non-standard evaluation (NSE).
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You could use the get function to fetch the value of the variable from the environment.
df %>% filter(b == get("b")) # Note the "" around b If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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