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Bookmark or Share- How do I select rows from a DataFrame based on column values?If multiple arithmetic, logical or comparison operations need to be computed to create a boolean mask to filter df, query() performs faster. For example, for a frame with 80k rows, it's 20% faster 1 and for a frame with 800k rows, it's 2 times faster. 2
- r - Filter by multiple conditions - Stack Overflow@talat answer is great, especially for combining with filters on other columns! say you want to exclude that age range AND filter by country filter(dat, age 80 & country == X) won't work, as it will select ALL X. filter(dat, !between(age, 10, 80) & country == X) will do it. Might need dplyr::between if plyranges or data.table are ...
- Get the first item from an iterable that matches a conditionnext(filter(lambda i: i == 1000, range(100000000))) WARNING: This doesn't work in Python 2, even replacing range with xrange due that filter create a list instead of a iterator (inefficient), and the next function only works with iterators. Default value
- r - OR operator in filter()? - Stack OverflowI want to use the filter() function to find the types that have an x value less than or equal to 4, OR a y value greater than 5.
- Removing NA observations with dplyr::filter () - Stack Overflow[T]his has nothing specifically to do with dplyr::filter() From @Marat Talipov: [A]ny comparison with NA, including NA==NA, will return NA. From a related answer by @farnsy: The == operator does not treat NA's as you would expect it to. Think of NA as meaning "I don't know what's there".
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