Subset a Data Frame Based on Value Pairs Stored in Independent Ordered Vectors

Subset a data frame based on value pairs stored in independent ordered vectors

You could try match which an appropriated nomatch argument:

sub <- match(DATA$A, AList, nomatch=-1) == match(DATA$B, BList, nomatch=-2)
sub
# [1]  TRUE FALSE  TRUE FALSE FALSE FALSE

DATA[sub,]
#  A B Value
#1 1 6     9
#3 3 8     2

A paste based approach would also be possible:

sub <- paste(DATA$A, DATA$B, sep=":") %in% paste(AList, BList, sep=":")
sub
# [1]  TRUE FALSE  TRUE FALSE FALSE FALSE

DATA[sub,]
#  A B Value
#1 1 6     9
#3 3 8     2

How to subset columns based on the value in another column in R

I made a subset of your data and came up with the following (could be more elegant but this works):

Individual<-c("A","B","C","D","E")
Age2010<-c(53,22,33,NA,NA)
`weight 2010`<-c(50,NA,65,70,NA)
Age2011<-c(85,23,34,28,64)
Weight2011<-c(100,75,64,NA,90)
df<-as.data.frame(cbind(Individual,Age2010,`weight 2010`,Age2011,Weight2011))
colnames(df)<-str_replace_all(colnames(df)," ", "")  # remove spaces

# create a dataframe for each year (prob could do this using `apply`)
df2010<-df %>% select(Individual, contains("2010")) %>% mutate(year=2010) %>%     rename(weight=weight2010,age=Age2010)
df2011<-df %>% select(Individual, contains("2011")) %>% mutate(year=2011) %>%     rename(weight=Weight2011,age=Age2011)

final<-bind_rows(df2010,df2011)

Of course, you can extend this for the remaining years in your dataset. You will then have a year variable to perform your analyses.

How to create a loop which creates multiple subset dataframes from a larger data frame?

Your code works fine. Just remove list so you create a vector of color names and not a list. If you only want distinct values, use unique.

mydata <- data.frame(x = c(1,2,3), y = c('a','b','c'), z = c('red','red','yellow'))

colors <- unique(mydata$z)

for (i in 1:length(colors)) {
    assign(paste0("mydata_",i), subset(mydata, z == colors[[i]]))
    }

Purging data frame of unwanted rows based on two vector sets

It is best to share a reproducible example, (How to make a great R reproducible example?)

Using the dataset available in base R mtcars and data(mtcars), create two conditional vectors

vectorsetforcol1<- mtcars$mpg[mtcars$mpg<15]
vectorsetforcol2<-unique(mtcars$carb[mtcars$carb==2])

Output condition 1: (mpg < 15)

> mtcars[mtcars$mpg %in% vectorsetforcol1,]
                     mpg cyl disp  hp drat    wt  qsec vs am gear carb
Duster 360          14.3   8  360 245 3.21 3.570 15.84  0  0    3    4
Cadillac Fleetwood  10.4   8  472 205 2.93 5.250 17.98  0  0    3    4
Lincoln Continental 10.4   8  460 215 3.00 5.424 17.82  0  0    3    4
Chrysler Imperial   14.7   8  440 230 3.23 5.345 17.42  0  0    3    4
Camaro Z28          13.3   8  350 245 3.73 3.840 15.41  0  0    3    4

Output condition 2: (carb == 2)

> mtcars[mtcars$carb %in% vectorsetforcol2,]
                   mpg cyl  disp  hp drat    wt  qsec vs am gear carb
Hornet Sportabout 18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
Merc 240D         24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
Merc 230          22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
Honda Civic       30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2
Dodge Challenger  15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2
AMC Javelin       15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2
Pontiac Firebird  19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
Porsche 914-2     26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
Lotus Europa      30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
Volvo 142E        21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2
> 

Combine conditions 1 and 2

> cond.df<-mtcars[(mtcars$mpg %in% vectorsetforcol1 | mtcars$carb %in% vectorsetforcol2  ),]
> cond.df
                     mpg cyl  disp  hp drat    wt  qsec vs am gear carb
Hornet Sportabout   18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
Duster 360          14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
Merc 240D           24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
Merc 230            22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
Cadillac Fleetwood  10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4
Lincoln Continental 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4
Chrysler Imperial   14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
Honda Civic         30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2
Dodge Challenger    15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2
AMC Javelin         15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2
Camaro Z28          13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4
Pontiac Firebird    19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
Porsche 914-2       26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
Lotus Europa        30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
Volvo 142E          21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2
> 

Test condition 1: (NOT(mpg < 15))

The cases where condition 1 is violated are present because they follow condition 2 (carb ==2)

> cond.test.col1<-cond.df[!cond.df$mpg %in% vectorsetforcol1, ]
> cond.test.col1
                   mpg cyl  disp  hp drat    wt  qsec vs am gear carb
Hornet Sportabout 18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
Merc 240D         24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
Merc 230          22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
Honda Civic       30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2
Dodge Challenger  15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2
AMC Javelin       15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2
Pontiac Firebird  19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
Porsche 914-2     26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
Lotus Europa      30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
Volvo 142E        21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2
> 

Test condition 2: (NOT(carb == 2))

The cases where condition 2 is violated are present because they follow condition 1 (mpg <15)

> cond.test.col2<-cond.df[!cond.df$carb %in% vectorsetforcol2, ]
> cond.test.col2
                     mpg cyl disp  hp drat    wt  qsec vs am gear carb
Duster 360          14.3   8  360 245 3.21 3.570 15.84  0  0    3    4
Cadillac Fleetwood  10.4   8  472 205 2.93 5.250 17.98  0  0    3    4
Lincoln Continental 10.4   8  460 215 3.00 5.424 17.82  0  0    3    4
Chrysler Imperial   14.7   8  440 230 3.23 5.345 17.42  0  0    3    4
Camaro Z28          13.3   8  350 245 3.73 3.840 15.41  0  0    3    4

This is the same approach as yours, if you had provided a working example someone would have pointed out the issue...

Make a table showing the 10 largest values of a variable in R?

This should do it...

data <- data[with(data,order(-Score)),]

data <- data[1:10,]

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