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Asked: 2026-05-31T14:06:05+00:00

I’m a R beginner and having difficulty with the following pretty simple problem; I

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I’m a R beginner and having difficulty with the following pretty simple problem;
I have two data frames ( All_df, Bad_df) and want to generate a third such that
All_df – Bad_df = Good_df

> All_df
Row# Originator Recipient  Date          Time
4    1          6          2000-05-16   16:15:00
7    2          7          2000-05-16   16:25:00
22   2          4          2000-07-04   18:05:00
25   2          9          2000-08-07   05:23:00
10   3          2          2000-06-17   18:07:00
13   4          8          2000-06-21   06:49:00 

> Bad_df
Row# Originator    Recipient       Date     Time
4    2             6         2000-05-16 16:15:00
7    2             7         2000-05-16 16:25:00
22   6             4         2000-07-04 18:05:00
25   12            9         2000-08-07 05:23:00
10   30            2         2000-06-17 18:07:00
13   32            8         2000-06-21 06:49:00 



I want to generate Good_df  similar to this:

> Good_df
Row#    Originator Recipient       Date     Time
4        1         6               2000-05-16   16:15:00
10       3         2               2000-06-17   18:07:00
13       4         8               2000-06-21   06:49:00

Essentially I need a function which searches All_df$ Originator for values that appear in Bad_df$ Originator, eliminating any matches before returning the remaining values to the Good_df.

I have tried 

Good_df <-subset(All_df, Originator %in% Bad_df$Originator)

however nrows of each df looks a little off!

> nrow(All_df)
[1] 26,032
> nrow(Bad_df)
[1] 1,452
> nrow(Good_df)
[1] 12,395

Any assistance would be greatly appreciated.

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1 Answer

  1. Editorial Team

    Quite intuitively,

    Good_df <-subset(All_df, Originator %in% Bad_df$Originator)

    gives you the subset of All_df for bad originators. What you want is to negate your filter to get the subset of good (or non-bad) originators, using the ! operator:

    Good_df <-subset(All_df, ! Originator %in% Bad_df$Originator)

    If you are uncomfortable with the precedency rule, you can add a set of parenthesis:

    Good_df <-subset(All_df, !(Originator %in% Bad_df$Originator))
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