Removing One Table from Another in R

Removing one table from another in R

We can use anti_join

library(dplyr)
anti_join(A, B, by = c('Col1', 'Col2'))

How to delete rows in one table, based on the values of another table

A possible approach with base R:

tab1[tab1$UserID %in% tab2$UserID[!tab2$Admin],]

which gives:

  UserID AssigID Score           TimeStamp TimeOnTask
2  12254   23956    22 2017-11-18 13:16:00        256
3  12644   23956    74 2012-12-17 13:18:00        365
4  11257   23957    45 2012-10-10 13:29:00        102
5  12667   23958    25 2012-11-10 13:40:00        109

What this does:

• tab2$UserID[!tab2$Admin] gives a vector of user ID's that are not an Admin. The !tab2$Admin part makes sure only the ID's that are not an Admin are selected.
• with tab1$UserID %in% ... you select only the user ID's from tab1 that are in the vector from the first step. This returns a logical vector with which you subsequently subset tab1

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Used data:

tab1 <- structure(list(UserID = c(14532L, 12254L, 12644L, 11257L, 12667L),
                       AssigID = c(23956L, 23956L, 23956L, 23957L, 23958L),
                       Score = c(52L, 22L, 74L, 45L, 25L),
                       TimeStamp = structure(c(1510402260, 1511007360, 1355746680, 1349868540, 1352551200), class = c("POSIXct", "POSIXt"), tzone = ""),
                       TimeOnTask = c(401L, 256L, 365L, 102L, 109L)),
                  .Names = c("UserID", "AssigID", "Score", "TimeStamp", "TimeOnTask"), row.names = c(NA, -5L), class = "data.frame")
tab2 <- structure(list(UserID = c(14532L, 12254L, 12644L, 11257L, 12667L),
                       Admin = c(TRUE, FALSE, FALSE, FALSE, FALSE)),
                  .Names = c("UserID", "Admin"), class = "data.frame", row.names = c(NA, -5L))

R: How to remove values from a table that appear in another table?

There's a bunch of ways to do this.

Base R subset solution (as noted by Balter above):

M4M3.new <- M4M3[!(M4M3$gene_id %in% M4F4$gene_id),]

Base R set union solution:

M4M3.new <- setdiff(M4M3, M4F4)

Dplyr solution

M4M3.new <- dplyr::anti_join(M4M3, 
                             M4F4, 
                             by = c("gene_id" = "gene_id"))

Edit: All appeared to work tested on the following dataset:

tst1 <- data.frame(gene_id = seq(1:10), 
                   sample_1 = rep("M4", 10), 
                   sample_2 = c(rep("M3", 6), rep("F4", 4)), 
                   other_values = sample(1:10, 10, replace = T),
                   other_values2 = rep("OK", 10))

M4M3 <- tst1[tst1$sample_1 == "M4" & tst1$sample_2  == "M3",]
M4F4 <- tst1[tst1$sample_1 == "M4" & tst1$sample_2  == "F4",]

Remove rows in data.table according to another data.table

Use an anti-join:

dtA[!dtB, on=.(date, company, value)]

This matches all records in dtA that are not found in dtB using the columns in on.

Delete rows that exist in another data frame?

You need the %in% operator. So,

df1[!(df1$name %in% df2$name),]

should give you what you want.

• df1$name %in% df2$name tests whether the values in df1$name are in df2$name
• The ! operator reverses the result.

Removing specific groups in R in data.table

Just use your group_vector with %in% operator.

data[group %in% group_vector]

   group values
1:  1001     10
2:  2800     23
3:  3230     32
4:  4600     34  

Removing data from one dataframe that exists in another dataframe R

Base R Solution

list_one[!list_one$letters %in% list_two$letters2,]

gives you:

  letters numbers
2       b       2
5       e       5

Explanation:

> list_one$letters %in% list_two$letters2
[1]  TRUE FALSE  TRUE  TRUE FALSE

This gives you a vector of LENGTH == length(list_one$letters) with TRUE/FALSE Values. ! negates this vector. So you end up with FALSE/TRUE values if the value is present in list_two$letters2.

If you have questions about how to select rows from a data.frame enter

?`[.data.frame`

to the console and read it.

Remove rows in one dataframe if they are present in another dataframe

In Base R

df[-match(df2$ASV, df$ASV),]

or even

 dplyr::anti_join(df, df2)

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