Delete row according to a specific values in a column in R

Question

I want to to delete rows in the Conf_mat_Modis_2000 table if values in the column Driver_90_00_Visual either equal 0 or NA. Can someone help me out with that.

dput(Conf_mat_Modis_2000)
structure(list(Driver_90_00_Modis500 = c(100, 200, 200, 100, 
100, 200, 200, 200, 100, 200, 500, 100, 100, 100, 100, 100, 100, 
100, 100, 500, 500, 100, 200, 200, 100, 500, 100, 100, 500, 100, 
100, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 200, 
100, 300, 100, 200, 100, 200, 100, 100, 100, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 200, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 200, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 200, 200, 200, 200, 200, 500, 200, 
200, 500, 500, 500, 500, 200, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 200, 500, 500, 200, 200, 200, 
200, 200, 100, 200, 200, 100, 200, 500, 500, 500, 200, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 
100, 100, 100, 100, 100, 100, 100, 200, 100, 100, 100, 100, 100, 
200, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 
200, 100, 100, 200, 100, 100, 100, 100, 100, 100, 100, 100, 100, 
100, 100, 100, 100, 100, 100, 200, 100, 200, 100, 100, 100, 100, 
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 200, 100, 100, 
200, 100, 100, 100, 100, 100, 100, 100, 100, 500, 100, 100, 100, 
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 500, 100, 100, 
500, 100, 500, 200, 100, 100, 100, 100, 100, 100, 100, 100, 100, 
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 500, 
500, 100, 200, 100, 500, 500, 500, 500, 200, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
200, 200, 200, 100, 500, 500, 500, 100, 200, 100, 100, 100, 200, 
100, 200, 200, 200, 100, 100, 100, 100, 500, 100, 100, 200, 100, 
100, 100, 100, 500, 500, 100, 200, 200, 200, 200, 200, 500, 200, 
200, 200, 200, 200, 200, 200, 200, 200, 500, 100, 200, 200, 500, 
200, 200, 500, 200, 200, 200, 200, 200, 200, 200, 500, 200, 500, 
200, 200, 200, 200, 200, 200, 200, 200, 200, 200, 500, 200, 200, 
200, 200, 100, 200, 200, 200, 200, 200, 200, 200, 200, 100, 200, 
200, 100, 200, 100, 100, 100, 200, 200, 200, 200, 100, 200, 200, 
100, 200, 200, 100, 200, 200, 200, 200, 200, 200, 200, 200, 200, 
200, 200, 200, 200, 200, 200, 100, 200, 200, 200, 200, 200, 200, 
200, 200, 100, 200, 200, 100, 200, 200, 200, 200, 100, 200, 200, 
200, 200, 200, 200, 100, 200, 200, 100, 200, 100, 100, 100, 200, 
100, 100, 100, 100, 200, 100, 500, 100, 100, 100, 500, 100, 200, 
100, 100, 200, 200, 200, 200, 100, 100, 200, 100, 200, 100, 200, 
200, 200, 200, 200, 100, 100, 500, 100, 200, 100, 200, 200, 200, 
100, 100, 200, 100, 100, 200, 100, 200, 200, 200, 100, 200, 100, 
200, 200, 100, 100, 100, 100, 100, 200, 100, 100, 100, 100, 200, 
200, 100, 200, 100, 100, 100, 100, 100, 200, 200, 100, 100, 200, 
200, 100, 200, 100, 200, 200, 200, 200, 200, 100, 200, 200, 200, 
200, 100, 200, 200, 200, 100, 100, 500, 200, 100, 100, 100, 200, 
200, 200, 200, 100, 100, 100, 200, 200, 200, 100, 200, 200, 200, 
200, 200, 200, 200, 200, 200, 200, 200, 200, 100, 500), Driver_90_00_Visual = c(600, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, 500, 200, 200, 200, 200, 
200, 200, 200, 200, 200, NA, 200, NA, 200, 200, 200, NA, NA, 
NA, NA, NA, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, 500, 500, 500, 500, 500, NA, 500, 500, 500, 500, 500, 500, 
500, 200, 200, 300, 200, 200, NA, 300, 200, 200, NA, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, NA, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 500, 
500, 500, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, NA, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
NA, NA, NA, NA, NA, NA, 200, 200, NA, 200, 200, NA, NA, 200, 
NA, NA, NA, 200, NA, 200, 500, NA, 200, 200, NA, 500, NA, 200, 
NA, NA, NA, NA, NA, NA, 200, 200, 500, NA, NA, 200, NA, NA, NA, 
200, NA, NA, 200, 200, 200, NA, NA, NA, 200, NA, 200, 200, NA, 
200, NA, NA, NA, NA, 200, 200, 200, NA, NA, NA, NA, NA, NA, 200, 
NA, NA, 500, NA, NA, NA, NA, NA, 500, NA, NA, NA, NA, NA, 200, 
200, NA, 500, NA, NA, NA, NA, 200, 500, NA, 500, 200, 500, NA, 
NA, NA, 200, NA, 500, 500, NA, NA, NA, NA, 500, 200, 500, NA, 
NA, 200, 200, 200, 200, 200, 200, 500, 500, 500, 500, NA, 500, 
200, 200, 200, 500, 500, 200, 500, 500, 200, 200, NA, NA, 200, 
200, 200, 200, 200, 200, 200, 200, 200, 200, NA, 500, 500, NA, 
NA, NA, 500, NA, NA, NA, NA, NA, NA, NA, NA, 500, 500, NA, NA, 
NA, NA, 500, 500, NA, NA, NA, NA, NA, 500, NA, 200, NA, NA, NA, 
NA, NA, 500, NA, 500, NA, NA, NA, NA, 500, NA, NA, 600, 600, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
500, 500, NA, 500, 500, 500, 500, 500, 500, 500, 500, 500, 500, 
500, NA, NA, NA, 500, 500, NA, NA, 500, 500, 500, 500, 500, 500, 
500, 600, 500, 500, 500, 200, 200, 200, NA, 200, NA, 500, 500, 
200, 200, 200, 200, NA, 200, 200, 200, 200, 200, 200, 200, 200, 
200, NA, 999, 999, NA, 500, 999, 200, 200, 200, 500, 200, 500, 
200, 200, 200, 200, 200, 200, 500, 200, 200, 200, 200, 200, 200, 
200, 200, 200, 200, 200, 500, 500, 500, 500, 500, 500, NA, 500, 
500, 500, 500, 500, 500, 200, 500, 500, 500, 500, 200, 500, 500, 
200, 500, 200, 500, 200, 200, 200, 500, NA, 500, 200, 200, 200, 
500, 500, 500, 200, 500, 500, 200, 500, 200, 200, 500, 200, 200, 
200, 500, 200, 200, NA, NA, NA, 200, 200, 500, 200, 200, 200, 
500, 200, 200, 200, 200, 500, 200, 200, 200, 200, 200, 200, 500, 
200, 200, 500, 200, 200, 500, 200, 500, 200, 200, 500, 200, 500, 
200, 200, 200, 200, 200, 200, 200, 500, 200, 200, 200, 200, 200, 
200, NA, 200, NA, 200, 200, 200, 200, 200, 200, 200, NA, NA, 
200, 200, 200, 500, 200, 500, 200, 500, 200, 200, 300, 300, 300, 
500, 200, 500, 200, 500, 500, 500, NA, 500, 200, 500, NA, 500, 
500, 200, 200, 500, 200, 200, 200, 200, 500, 500, 200, 500, 200, 
NA, 500)), .Names = c("Driver_90_00_Modis500", "Driver_90_00_Visual"
), class = "data.frame", row.names = c(NA, -1081L))

@beginneR, with `Conf_mat_Modis_2000$Driver_90_00_Visual` instead of just `Driver_90_00_Visual`... — Cath, Oct 30 '14 at 08:53
Maybe start going through an R tutorial to learn more about subsetting if you haven't done that yet. It's quite essential — talat, Oct 30 '14 at 08:55
The best practice before posting a question is to use Google first — David Arenburg, Oct 30 '14 at 09:04

KFB · Accepted Answer · 2014-10-30T09:04:00.193

0

Assume df is your data frame, could do

df[!(df$Driver_90_00_Visual %in% c(0, NA)),]

With reference to the comments:

df_is_na <- df[df$Driver_90_00_Visual != 0 & !is.na(df$Driver_90_00_Visual),]
df_NA <- df[!(df$Driver_90_00_Visual %in% c(0, NA)),]
identical(df_is_na, df_NA)
# [1] TRUE

edited Oct 30 '14 at 09:04

answered Oct 30 '14 at 08:56

KFB

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NA is usually tested for with `is.na()` instead of `... == NA` – talat Oct 30 '14 at 08:57
It works using the OP's dataset. – KFB Oct 30 '14 at 08:59
1

I'm just saying that it's perhaps not considered "good practice" (even though it might work here) – talat Oct 30 '14 at 09:00
1

Check section 8.1.4 of http://www.burns-stat.com/pages/Tutor/R_inferno.pdf – talat Oct 30 '14 at 09:25

Delete row according to a specific values in a column in R

1 Answers1