How to Extract All the Rows If a Level in One Column Contains All the Levels of Another Column in R

How to extract all the rows if a level in one column contains all the levels of another column in R?

Multiple ways to do this :

In dplyr

df %>% 
   group_by(ID) %>% 
   filter(all(c("Neolone Preservatives", "Optiphen") %in% PRODUCT))

#     ID     INDUSTRY               PRODUCT
#   <int>        <chr>                 <chr>
#1 625109 PersonalCare Neolone Preservatives
#2 227047       Pharma              Optiphen
#3 625109 PersonalCare              Optiphen
#4 227047         Food Neolone Preservatives

In base R :

df[ave(df$PRODUCT, df$ID, FUN = function(x) 
                 all(c("Neolone_Preservatives", "Optiphen") %in% x)) == "TRUE", ]

Extract column data on the basis of another column levels in r

Conducting a t.test in R. It is best practice to convert your factor variable (the 0/1) to a factor before running the t.test. The function assumes each row is a separate person, and they belong to the group specified in Col1.

Col1 <- sample(c(0,1), 50, replace = TRUE)
Col2 <- round(rnorm(50),2)
dat <- data.frame(Col1, Col2)

dat$Col1 <- factor(dat$Col1) 
t.test(Col2 ~ Col1, data = dat)

R - How to extract a subset of a data frame containing many observations of two factors, each with multiple levels based on conditions?

Here is a dplyr solution:

library(dplyr)
group_by(df, Alphabet) %>% filter(!(L == 3 & any(L %in% c(1, 2))))

Replace whole values in a column with another column using condition

I think you want to merge the two datasets using the level. Then for each date you would have variable and depth, and you can do what you want with that (including overwriting the level with the depth, as you suggest).

library(tidyverse)
reference_data <- read_table("depth   levels
0.06    1
0.19    2
0.33    3
0.48    4
0.63    5
0.8     6")

data_file <- read_table("Date    Levels  variable
3-Jan   1       15.25
3-Feb   5       13.09
3-Mar   25      14.21
3-Apr   26      13.65
3-May   27      12.79
3-Jun   27      15.65")

data_file %>% 
  left_join(reference_data, by = c("Levels" = "levels"))
#> # A tibble: 6 x 4
#>   Date  Levels variable depth
#>   <chr>  <dbl>    <dbl> <dbl>
#> 1 3-Jan      1     15.2  0.06
#> 2 3-Feb      5     13.1  0.63
#> 3 3-Mar     25     14.2 NA   
#> 4 3-Apr     26     13.6 NA   
#> 5 3-May     27     12.8 NA   
#> 6 3-Jun     27     15.6 NA

^{Created on 2021-07-14 by the reprex package (v2.0.0)}

Extract rows from R data frame based on factors (strings)

Try using the subset function.

This site provides a good reference:
HowtoInR

my_data = subset(my_data, gender == "male")

filter for rows that meet multiple conditions in a column

After grouping by 'ID', filter by checking all the elements of the vector (c("up", "down")) are %in% the column 'DIR'

library(dplyr)
x %>%
   group_by(ID) %>%
   filter(all(c("up", "down") %in% DIR) )
# A tibble: 2 x 2
# Groups:   ID [1]
#     ID DIR  
#  <dbl> <fct>
#1     2 up   
#2     2 down 

---

Or using base R

i1 <- with(x, as.logical(ave(as.character(DIR), ID, FUN = 
          function(x) all(c("up", "down") %in% x))))
x[i1, ]
#   ID  DIR
#2  2   up
#3  2 down

---

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