That message means that from that moment: if you use filter(), the filter() from dplyr will be used, rather than the filter() from base R (stats);; similarly for lag(). (There isn't any conflict between dplyr::filter() and dplyr::lag().). This is usually not an issue - the vast majority of code will work just fine You can use the following syntax to filter data frames by multiple conditions using the dplyr library: Method 1: Filter by Multiple Conditions Using OR. library (dplyr) df %>% filter(col1 == ' A ' | col2 > 90) Method 2: Filter by Multiple Conditions Using AND. library (dplyr) df %>% filter(col1 == ' A ' & col2 > 90) The filter function from dplyr subsets rows of a data frame based on a single or multiple conditions. In this tutorial you will learn how to select rows using Missing: Author Try dplyr::filter (exprCore1, trimws (measure) == "map") and see if you get a different result. – thelatemail. Sep 26, at 1. This code looks fine to me as well. Run dput (exprCore1) in your console and edit the resulting output into your post so we can use the exact same data you are using. – dshkol 1 Answer. We may use if_any (to subset rows where any of the columns have the "Yes") or if_all (only subset rows where all the columns in the selected columns have 'Yes' in that row) filter(if_any(everything(), ~.x == "Yes")) everything () selects all the columns. If we need to apply only on a subset of columns, use either a character vector You can use the following basic syntax in dplyr to filter for rows where a column starts with a certain pattern: library(dplyr) library(stringr) df %>% Missing: Author 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 [HOST] This is described in this chapter of Advanced R, on 'quasi-quotation'. This chapter also
R - rowwise filtering in dplyr - Stack Overflow
I am struggling a little with dplyr because I want to do two things at one and wonder if it is possible. I want to calculate the mean of values and at the same time the mean for the values which have a specific value in an other column Dplyr is a cohesive set of data manipulation functions that will help make your data wrangling as painless as possible. dplyr, at its core, consists of 5 functions, all
Is there a way to filter out multiple values at once using dplyr in R ...
SessionInfo() R version () Platform: x86_wmingw32/x64 (bit) locale: [1] LC_COLLATE=English_Australia LC_CTYPE=English_Australia [3] LC_MONETARY=English_Australia LC_NUMERIC=C [5] LC_TIME=English_Australia attached base packages: [1] stats graphics grDevices It's worth noting that if you are using this filter in a dplyr pipe with other dplyr commands (such as group_by()), you will need to add %>% [HOST]() %>% before you try and filter on [HOST]) because it won't work on tibbles or grouped tibbles or something. Or at least, that has been the experience I have had Using the package dplyr and the function sample_frac it is possible to sample a percentage from every group. What I need is to first sort the elements in every group and then select top x% from every group? There is a function top_n, but here I can only determine the number of rows, and I need a relative value.. For example the How to Filter by Multiple Conditions Using dplyr. You can use the following syntax to filter data frames by multiple conditions using the dplyr 5 1 8. Using either dplyr's filter or subset (preferably filter) I would like to reverse filter the data so I get this: print(dat) i1 i2 node_id. 4 4 8. 4 5 8. 5 1 8. I say reverse filter because instead of filtering or sub-setting like: datfilter(dat,node_id==8) R dplyr filter with a dynamic variable name. 7. Storing filters for dplyr `filter()` in a variable. 5. How to use dynamic arguments in a dplyr filter within function. 7. Dplyr filter using dynamic column name and dynamic value. 0. How to pass variable to filter function within a R function. 2 R lazyeval: pass parameters to dplyr::filter. I think this questions has multiple other variations (eg: here, here and perhaps here) - probably even an answer somewhere. How to provide parameters to the filter function. library (dplyr) library (lazyeval) [HOST] (10) data The simple way to achieve this: Install dplyr package. Run the below code. library(dplyr) dfect(filter(dat,name=='tom'| name=='Lynn'), c('days','name)) Missing: Author