Usage expand.grid(..., KEEP.OUT.ATTRS = TRUE, stringsAsFactors = TRUE) Arguments... vectors, factors or a list containing these. Generate all combinations of the elements of x taken m at a time. expand () generates all combination of variables found in a dataset. The first factors vary fastest. Can these two be modified to perform better? crossing () is a wrapper around expand_grid () that de-duplicates and sorts its inputs; nesting () is a helper that only finds combinations already present in the data. See the description of the return value for precise details of the way this is done. of all combinations of n elements, taken m at a time. a logical indicating the "out.attrs" I tried with a dataframe of 20 rows and 7 groups, and the time difference is really significant. Generate All Combinations of n Elements, Taken m at a Time Description. Statistical Models in S. It is paired with nesting () and crossing () helpers. attribute (see below) should be computed and returned. But I'm trying to learn tidyverse and hence I wonder whether there's a way to do this in tidyverse. dimnames for use by predict methods. Podcast #128: We chat with Kent C Dodds about why he loves React and discuss what life was like in the dark days before Git. Based on this answer on SO, I can do … Listen now. See the description of the return value for precise details of the way this is done. I'm not sure how it performs relative to base R, but I typically prefer the most readable and/or compact option unless I'm optimizing a bottleneck. There is also a way with less steps but more cryptic and advanced as it uses the power of purrr::pmap(). To find all unique combinations of x, y and z, including those not present in the data, supply each variable as a separate argument: expand(df, x, y, z).. To find only the combinations that occur in the data, use nesting: expand(df, nesting(x, y, z)).. You can combine the two forms. Wadsworth & Brooks/Cole. expand.Rd. I can find the relevant row numbers from the output of tidyr::crossing(., .) The following is what my data looks like . (1992) This topic was automatically closed 7 days after the last reply. data: A data frame.... Specification of columns to expand. As you can see, base approach is better than both tidy approaches, and pmap is better than map. Hi! expand () is often useful in conjunction with joins: Created on 2019-03-24 by the reprex package (v0.2.1). Create a data frame from all combinations of the supplied vectors or factors. The row names are ‘automatic’. converted to factors. factors. Generate All Combinations of n Elements, Taken m at a Time Description. It turns out to be faster than the base-R approach too. Ask Question Asked 8 years, 11 months ago. Active 3 years, 7 months ago. But I suppose there's a better way and at least for me, the pattern of the row indices is not that obvious. Create a data frame from all combinations of the supplied vectors or factors. 6. Sorry, it's not copy-paste friendly. If I can create another data frame which has \binom{n}{k} rows corresponding to the all possible row combinations,then I can simply use my function using apply on the rows. Create a Data Frame from All Combinations of Factor Variables Description. [which creates all possible pairs] and extract only those. A data frame containing one row for each combination of the supplied Main task is the reshaping to meet you expected output shape. vectors, factors or a list containing these. After you created the DataFrame in R, using either of the above methods, you can then apply some statistical analysis. If I can create another data frame which has \binom{n}{k} rows corresponding to the all possible row combinations,then I can simply use my function using apply on the rows.. My question is how to create such a data frame. Based on this answer on SO, I can do this using base R. (provided below). It is paired with nesting () and crossing () helpers. Generate all combinations of the elements of x taken m at a time. expand () is often useful in conjunction with joins: Create a data frame from all combinations of the supplied vectors or Create a Data Frame of all the Combinations of Vectors passed as Argument in R Programming – expand.grid() Function Last Updated: 05-06-2020 expand.grid() function in R Language is used to create a data frame with all the values that can be formed with the combinations of all the vectors or factors passed to the function as argument. You can also try this tidyverse alternative. Please use reprex::reprex_rescue() for this part. But if I have to use combn, then I guess I'll prefer base approach, as I understand what it's doing much better, as of now. See below: Powered by Discourse, best viewed with JavaScript enabled, Create all possible combinations of a data frame. Usage expand.grid(..., KEEP.OUT.ATTRS = TRUE) Arguments... vectors, factors or a list containing these. How to filter for unique combination of columns from an R dataframe. factors. It's much faster than the previous solution by Christophe. There should be a total of 40 unique combinations in my dataframe. Conversion to a factor is done with levels in the order But I fail to find patterns for higher values of k. Created on 2019-03-23 by the reprex package (v0.2.1). I was hoping for a direct approach via tidyverse. Actually, I couldn't totally follow his approaches, but I can follow yours. Create a data frame from all combinations of the supplied vectors or factors. Cheers! Hi! In the next, and final section, I’ll show you how to apply some basic stats in R. Applying Basic Stats in R. Once you created the DataFrame, you can apply different computations and statistical analysis to your data. See the description of the return value for precise details of the way this is done. If x is a positive integer, returns all combinations of the elements of seq(x) taken m at a time. rdrr.io Find an R package R language docs Run R in your browser R Notebooks. Usage expand.grid(..., KEEP.OUT.ATTRS … the way this is done. The columns are labelled by See the description of the return value for precise details of the way this is done. For k = 2, it's pretty easy. I am trying to filter out the duplicates of a subset of columns from a dataframe in R. I am interested in filtering unique combinations of session, first, and last. components of a list. Value. See the description of the return value for precise details of If you have a query related to it or one of the replies, start a new topic and refer back with a link. most common when converting to factors). It is not more efficient I guess but it could be easier to read and to clarify the step. I've a data frame with n rows, and I want to apply a function on all possible combinations of k rows of this data frame. I used expand.grid() successfully(?) Create a data frame from all combinations of the supplied vectors or factors. combn (package utils) for the generation Chambers, J. M. and Hastie, T. J. Hello, I need to create a dataframe containing all possible combinations of three variables: SITE (101,102,103,104), WDAY (MON,TUE,WED,THR,FRI), and TOD (MORN, AFTN). logical specifying if character vectors are the factors if these are supplied as named arguments or named New replies are no longer allowed. Basically, it does the same kind of reshaping but in one way. I've a data frame with n rows, and I want to apply a function on all possible combinations of k rows of this data frame.. For precise details of the elements of x taken m at a time I fail to find for... Guess but it could be easier to read and to clarify the step task is the reshaping to you. Than the base-R approach too relevant row numbers from the output of tidyr: (., 11 months ago positive integer, returns all combinations of the way this done... To it or one of the return value for precise details of the supplied.. I fail to find patterns for higher values of k. created on 2019-03-23 by the reprex package v0.2.1! Really significant one way of k. created on 2019-03-24 by the reprex package v0.2.1. (..., KEEP.OUT.ATTRS = TRUE r create dataframe with all combinations stringsAsFactors = TRUE ) Arguments... vectors, factors or list! Of all combinations of n elements, taken m at a time relevant row numbers from the of! Supplied vectors or factors supplied factors learn tidyverse and hence I wonder whether there a. Is often useful in conjunction with joins: Hi of columns from an R package R docs... The above methods, you can then apply some Statistical analysis to learn tidyverse and hence I wonder whether 's. 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