R change strings into numeric in a data frame

Question

I have a data frame as below and would like to generate another data frame by replacing the characters in the dataframe into numeric according condition.

condition:
GD  5
O   4.5
AV  3
B   2.5

dataframe:
Name    Peter   Paul    Mary    Chan    Jose
Nokia   B       O       O       GD      GD
iPhone  AV      O       O       O       O
Moto    AV      AV      O       O       AV
HTC     B       O       AV      AV      AV

dput:
structure(list(Name = c("Nokia", "iPhone", "Moto", "HTC"), Peter = 
c("B", "AV", "AV", "B"), Paul = c("O", "O", "AV", "O"), Mary = 
c("O", "O", "O", "AV"), Chan = c("GD", "O", "O", "AV"), Jose = 
c("GD", "O", "AV", "AV")), .Names = 
c("Name", "Peter", "Paul", "Mary", "Chan", "Jose"), class = "data.frame", row.names = c(NA, -4L))

desired output:
Name    Peter   Paul    Mary    Chan    Jose
Nokia   2.5     4.5     4.5     5       5
iPhone  3       4.5     4.5     4.5     4.5
Moto    3       3       4.5     4.5     3
HTC     2.5     4.5     3       3       3

Thanks for your help!!!

David Arenburg · Accepted Answer · 2016-11-10 09:25:05Z

7

I'm not sure what is the structure of condition, but assuming it's a named vector as such

condition <- setNames(c(5, 4.5, 3, 2.5), c("GD", "O", "AV", "B"))

I would simply, unlist/match your data set with it and put it back

df[-1] <- condition[match(unlist(df[-1]), names(condition))]
df
#     Name Peter Paul Mary Chan Jose
# 1  Nokia   2.5  4.5  4.5  5.0  5.0
# 2 iPhone   3.0  4.5  4.5  4.5  4.5
# 3   Moto   3.0  3.0  4.5  4.5  3.0
# 4    HTC   2.5  4.5  3.0  3.0  3.0

answered Nov 10, 2016 at 9:25

David Arenburg

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Comments

akrun · Accepted Answer · 2016-11-10 09:24:09Z

3

One option is using match by looping through the columns

df1[-1] <- lapply(df1[-1], function(x) keyval$v2[match(x, keyval$v1)])
df1
#    Name Peter Paul Mary Chan Jose
#1  Nokia   2.5  4.5  4.5  5.0  5.0
#2 iPhone   3.0  4.5  4.5  4.5  4.5
#3   Moto   3.0  3.0  4.5  4.5  3.0
#4    HTC   2.5  4.5  3.0  3.0  3.0

where 'keyval' is a 'data.frame' with 'v1' and 'v2' as the 'key' and 'value' columns.

answered Nov 10, 2016 at 9:24

akrun

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Comments

Sandipan Dey · Accepted Answer · 2016-11-10 11:14:12Z

1

This also works (where cdf is the lookup table):

cbind.data.frame(Name=df[,1], matrix(cdf$value[match(as.matrix(df[-1]), cdf$condition)], 
                                     nrow=nrow(df), dimnames=list(NULL, names(df[-1]))))

with output

    Name Peter Paul Mary Chan Jose
1  Nokia   2.5  4.5  4.5  5.0  5.0
2 iPhone   3.0  4.5  4.5  4.5  4.5
3   Moto   3.0  3.0  4.5  4.5  3.0
4    HTC   2.5  4.5  3.0  3.0  3.0

answered Nov 10, 2016 at 11:14

Sandipan Dey

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