In R, How to Subset a Data.Frame by Values from Another Data.Frame

subset a column in data frame based on another data frame/list

We can use %in% to get a logical vector and subset the rows of the 'table1' based on that.

subset(table1, gene_ID %in% accessions40$V1)

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A better option would be data.table

library(data.table)
setDT(table1)[gene_ID %chin% accessions40$V1]

Or use filter from dplyr

library(dplyr)
table1 %>%
      filter(gene_ID %in% accessions40$V1)

Subset of dataframe based on values in another dataframe

As mentioned in the comments there were whitespaces in the data hence it didn't match. We can use trimws to remove the whitespace and then try to subset it.

df2[trimws(df2$relevantcolumn) %in% trimws(df1), ]

Or if df1 is dataframe

df2[trimws(df2$relevantcolumn) %in% trimws(df1$relevant_column), ]

R: Filter a dataframe based on another dataframe

If you are only wanting to keep the rownames in e that occur in pf (or that don't occur, then use !rownames(e)), then you can just filter on the rownames:

library(tidyverse)

e %>% 
  filter(rownames(e) %in% rownames(pf))

Another possibility is to create a rownames column for both dataframes. Then, we can do the semi_join on the rownames (i.e., rn). Then, convert the rn column back to the rownames.

library(tidyverse)

list(e, pf) %>% 
  map(~ .x %>% 
        as.data.frame %>%
        rownames_to_column('rn')) %>% 
  reduce(full_join, by = 'rn') %>%
  column_to_rownames('rn')

Output

        JHU_113_2.CEL JHU_144.CEL JHU_173.CEL JHU_176R.CEL JHU_182.CEL JHU_186.CEL JHU_187.CEL JHU_188.CEL JHU_203.CEL
2315374       6.28274     6.79161     6.11265      6.13997     6.68056     6.48156     6.45415     6.04542     5.99176
2315376       5.81678     5.71165     6.02794      5.37082     5.95527     5.75999     5.87863     5.54830     6.35571
2315587       8.88557     8.95699     8.36898      8.28993     8.41361     8.64980     8.74305     8.31915     8.43548
2315588       6.28650     6.66750     6.07503      6.76625     6.19819     6.84260     6.13916     6.40219     6.45059
2315591       6.97515     6.61705     6.51994      6.74982     6.60917     6.55182     6.62240     6.44394     5.76592
2315595       5.94179     5.39178     5.09497      4.96199     2.96431     4.95204     5.00979     4.06493     5.38048
2315598       4.99420     5.56888     5.57912      5.43960     5.19249     5.87991     5.60540     5.09513     5.43618
2315603       7.67845     7.90005     7.47594      6.75087     7.62805     8.00069     7.34296     6.81338     7.52014
2315604       6.20952     6.59687     6.14608      5.70518     6.49572     6.12622     6.23690     6.39569     6.70869
2315640       5.85307     6.07303     6.41875      6.07282     6.28283     6.13699     6.16377     6.48616     6.34162

How to subset windows in a dataframe using start- and end-values from another dataframe in R?

Maybe try this approach with purrr::map2

# dataframe of data to subset
df1 <- tibble(my_values = rnorm(100, mean = 45, sd = 30) %>% abs())

# dataframe of windows (i.e. row number IDs) to extract from data
df2 <-tibble::tribble(
  ~window_start, ~window_end,
  3L,         10L,
  21L,         25L,
  52L,         63L,
  78L,         90L
)

subset_thats_in <- function(mini, maxi){
  df1 %>% 
    filter(between(my_values, mini, maxi))
}

purrr::map2(df2$window_start, 
            df2$window_end, 
            subset_thats_in)

[[1]]
# A tibble: 4 × 1
  my_values
      <dbl>
1      6.47
2      8.69
3      7.73
4      7.35

[[2]]
# A tibble: 12 × 1
   my_values
       <dbl>
 1      24.2
 2      22.9
 3      22.4
 4      24.4
 5      22.6
 6      21.7
 7      23.2
 8      21.3
 9      23.3
10      21.1
11      23.5
12      22.6

[[3]]
# A tibble: 10 × 1
   my_values
       <dbl>
 1      54.0
 2      61.4
 3      62.5
 4      60.8
 5      60.5
 6      55.5
 7      61.4
 8      59.0
 9      57.9
10      53.3

[[4]]
# A tibble: 6 × 1
  my_values
      <dbl>
1      87.8
2      79.1
3      80.5
4      82.7
5      85.2
6      80.6

Subsetting a dataframe based on values in another dataframe

d <- read.table(text="hh_id   trans_type  transaction_value
hh1 food    4
hh1 water   5
hh1 transport   4
hh2 water   3
hh3 transport   1
hh3 food    10
hh4 food    5
hh4 transport   15
hh4 water   10", header=T)

dw <- as.character(with(d, hh_id[trans_type=="water"])) 
ds <- d[which(d$hh_id%in%dw),]
ds
#   hh_id trans_type transaction_value
# 1   hh1       food                 4
# 2   hh1      water                 5
# 3   hh1  transport                 4
# 4   hh2      water                 3
# 7   hh4       food                 5
# 8   hh4  transport                15
# 9   hh4      water                10

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