How to filter for rows across any columns for non zero-CodePudding

I would like to filter my dataframe to obtain all rows that have no zero in any columns.

Here's my dataframe:

df1 = structure(list(item = c(NA, "polygon", NA, NA, NA, NA, NA, "polygon", 
"polygon", "0", NA, "polygon", "polygon"), identity = c("pol", 
"0", NA, NA, NA, NA, "0", "pol", "pol", "0", NA, "pol", "pol"
), unique = c("polx", "0", "0", "0", "0", "0", "0", "polx", "0", 
"0", NA, "polx", "0"), detect = c("ox", "0", "0", "0", "0", "0", 
NA, NA, "ox", "0", NA, "ox", NA), structure = c("hex", "0", "0", 
"0", "0", "0", NA, "hex", "hex", "0", NA, "hex", "hex"), key = c("IUGDG", 
"0", "0", "0", NA, "0", NA, "IUGDG", "IUGDG", "0", NA, "IUGDG", 
"IUGDG"), code = c("adg434kk", "0", "0", "0", NA, "0", NA, "adg434kk", 
"adg434kk", "0", NA, "adg434kk", "adg434kk")), class = "data.frame", row.names = c(NA, 
-13L))

      item identity unique detect structure   key     code
1     <NA>      pol   polx     ox       hex IUGDG adg434kk
2  polygon        0      0      0         0     0        0
3     <NA>     <NA>      0      0         0     0        0
4     <NA>     <NA>      0      0         0     0        0
5     <NA>     <NA>      0      0         0  <NA>     <NA>
6     <NA>     <NA>      0      0         0     0        0
7     <NA>        0      0   <NA>      <NA>  <NA>     <NA>
8  polygon      pol   polx   <NA>       hex IUGDG adg434kk
9  polygon      pol      0     ox       hex IUGDG adg434kk
10       0        0      0      0         0     0        0
11    <NA>     <NA>   <NA>   <NA>      <NA>  <NA>     <NA>
12 polygon      pol   polx     ox       hex IUGDG adg434kk
13 polygon      pol      0   <NA>       hex IUGDG adg434kk

Expected output

      item identity unique detect structure   key     code
1     <NA>      pol   polx     ox       hex IUGDG adg434kk
8  polygon      pol   polx   <NA>       hex IUGDG adg434kk
11    <NA>     <NA>   <NA>   <NA>      <NA>  <NA>     <NA>
12 polygon      pol   polx     ox       hex IUGDG adg434kk

All the attempts I have tried below failed:

df1 %>%
  filter(!if_any(item:code, ~ .x == 0))

df1 %>%
  filter(if_any(item:code, ~ .x != 0))

Using anti_join provides the solution but is there a more direct way?

df2 <- df1 %>%
  filter(if_any(item:code, ~ .x == 0))
anti_join(df1, df2)

Most of the solutions I found is changing 0 to NA but I want to find all rows with 0. Can someone provides a solution using dplyr, that is with piping approach? thanks.

CodePudding user response：

We could use if_all with %in%

library(dplyr)
df1 %>%
  filter(if_all(item:code, ~ !.x  %in% 0))

-output

  item identity unique detect structure   key     code
1    <NA>      pol   polx     ox       hex IUGDG adg434kk
2 polygon      pol   polx   <NA>       hex IUGDG adg434kk
3    <NA>     <NA>   <NA>   <NA>      <NA>  <NA>     <NA>
4 polygon      pol   polx     ox       hex IUGDG adg434kk

Or with if_any with %in%

df1 %>%
    filter(!if_any(item:code, ~ .x %in% 0))
 item identity unique detect structure   key     code
1    <NA>      pol   polx     ox       hex IUGDG adg434kk
2 polygon      pol   polx   <NA>       hex IUGDG adg434kk
3    <NA>     <NA>   <NA>   <NA>      <NA>  <NA>     <NA>
4 polygon      pol   polx     ox       hex IUGDG adg434kk

If we want to use == or !=, make sure that NA values are taken care of

df1 %>%
  filter(!if_any(item:code, ~ .x == 0 & !is.na(.x)))
 item identity unique detect structure   key     code
1    <NA>      pol   polx     ox       hex IUGDG adg434kk
2 polygon      pol   polx   <NA>       hex IUGDG adg434kk
3    <NA>     <NA>   <NA>   <NA>      <NA>  <NA>     <NA>
4 polygon      pol   polx     ox       hex IUGDG adg434kk

The difference is that == or != returns NA when there is an NA whereas %in% returns FALSE for the NA. When there is NA as return value, filter removes those rows. If we create a column, it becomes more clear

> df1 %>%
       mutate(new = if_any(item:code, ~ .x != 0))
      item identity unique detect structure   key     code   new
1     <NA>      pol   polx     ox       hex IUGDG adg434kk  TRUE
2  polygon        0      0      0         0     0        0  TRUE
3     <NA>     <NA>      0      0         0     0        0    NA
4     <NA>     <NA>      0      0         0     0        0    NA
5     <NA>     <NA>      0      0         0  <NA>     <NA>    NA
6     <NA>     <NA>      0      0         0     0        0    NA
7     <NA>        0      0   <NA>      <NA>  <NA>     <NA>    NA
8  polygon      pol   polx   <NA>       hex IUGDG adg434kk  TRUE
9  polygon      pol      0     ox       hex IUGDG adg434kk  TRUE
10       0        0      0      0         0     0        0 FALSE
11    <NA>     <NA>   <NA>   <NA>      <NA>  <NA>     <NA>    NA
12 polygon      pol   polx     ox       hex IUGDG adg434kk  TRUE
13 polygon      pol      0   <NA>       hex IUGDG adg434kk  TRUE

whereas with %in%

> df1 %>% mutate(new = !if_any(item:code, ~ .x %in% 0))
      item identity unique detect structure   key     code   new
1     <NA>      pol   polx     ox       hex IUGDG adg434kk  TRUE
2  polygon        0      0      0         0     0        0 FALSE
3     <NA>     <NA>      0      0         0     0        0 FALSE
4     <NA>     <NA>      0      0         0     0        0 FALSE
5     <NA>     <NA>      0      0         0  <NA>     <NA> FALSE
6     <NA>     <NA>      0      0         0     0        0 FALSE
7     <NA>        0      0   <NA>      <NA>  <NA>     <NA> FALSE
8  polygon      pol   polx   <NA>       hex IUGDG adg434kk  TRUE
9  polygon      pol      0     ox       hex IUGDG adg434kk FALSE
10       0        0      0      0         0     0        0 FALSE
11    <NA>     <NA>   <NA>   <NA>      <NA>  <NA>     <NA>  TRUE
12 polygon      pol   polx     ox       hex IUGDG adg434kk  TRUE
13 polygon      pol      0   <NA>       hex IUGDG adg434kk FALSE