从包含特定列中的字符串的数据框中删除行

Question

So I'm cleaning up a huge data file in R and an example is as shown:

ID       Score
1001       4
1002       2
1003       h
1004       v
1005       3

Because the class of Score column is "character", I want to use the as.numeric function to convert 4,20 and 30 to numeric values. But since the data is dirty (contains unreasonable strings like h, v), I get the message:

NAs introduced by coercion.

When i run the following:

as.numeric(df$Score)

So what i want to do now is to remove the rows in the dataframe that contains strings with letters so that i would obtain:

ID       Score
1001       4
1002       2
1005       3

Answer 1

There are multiple ways you can do this :

Convert to numeric and remove NA values

subset(df, !is.na(as.numeric(Score)))

#    ID Score
#1 1001     4
#2 1002    20
#5 1005    30

Or with grepl find if there are any non-numeric characters in them and remove them

subset(df, !grepl('\\D', Score))

This can be done with grep as well.

df[grep('\\D', df$Score, invert = TRUE), ]

data

df <- structure(list(ID = 1001:1005, Score = c("4", "20", "h", "v", 
"30")), class = "data.frame", row.names = c(NA, -5L))

Answer 2

You may use the str_detect in the tidyverse package, as follows:

df[str_detect(df$Score, "\\d"),]

or

df %>% filter(str_detect(df$Score, "\\d"))

Both produce the output:

#    ID Score
#1 1001     4
#2 1002    20
#5 1005    30

Hope it helps.