R Extract Rows Where Column Greater Than 40

Extracting columns having greater than certain values in R dataframe

We could use colSums to subset columns using base R

df[colSums(df > 0.6) > 0]

# Jux Gyno
#1 0.67 0.89
#2 0.11 0.65
#3 0.60 0.67
#4 0.09 0.01

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Or with dplyr, select_if

library(dplyr)
df %>% select_if(~any(. > 0.6))

R: Select only Rows where value greater than a certain value and Mapped to another column where value is Yes or No

Turns out it was pretty easy.

x = df[df$Answer == "Yes"]
x = df[df$Age >= 40]
x$Age

Extract all rows with any value greater than x

You can use filter_all:

library(tidyverse)

df <- mtcars %>% 
  select_if(is.numeric) %>% 
  cor() %>% 
  round(digits = 2) %>% 
  as.data.frame() %>%
  filter_all(all_vars(abs(.) > 0.4))

Result:

    mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
1  1.00 -0.85 -0.85 -0.78  0.68 -0.87  0.42  0.66  0.60  0.48 -0.55
2 -0.85  1.00  0.90  0.83 -0.70  0.78 -0.59 -0.81 -0.52 -0.49  0.53

To select columns where all values are greater than 0.4, use select_if:

df <- mtcars %>% 
  select_if(is.numeric) %>% 
  cor() %>% 
  round(digits = 2) %>% 
  as.data.frame() %>%
  select_if(funs(all(abs(.) > 0.4)))

Result:

       mpg   cyl
mpg   1.00 -0.85
cyl  -0.85  1.00
disp -0.85  0.90
hp   -0.78  0.83
drat  0.68 -0.70
wt   -0.87  0.78
qsec  0.42 -0.59
vs    0.66 -0.81
am    0.60 -0.52
gear  0.48 -0.49
carb -0.55  0.53

Note:

If you want rows or columns with any value greater than 0.4, just switch out all_vars or all with any_vars or any respectively:

filter_all(any_vars(abs(.) > 0.4))

select_if(funs(any(abs(.) > 0.4)))

Getting rows whose value are greater than the group mean

You can just group and then filter:

mydf %>%
  group_by(A) %>%
  filter(B > mean(B, na.rm = TRUE)) %>%
  ungroup()

How to compare variables to a number in a column (dataframe) in R

You shouldn't need to use a loop. You can subset a data frame directly using a logical test on the specified column. verbs[verbs$LengthOfTheme > 1.609438,]

Select rows of a matrix that meet a condition

This is easier to do if you convert your matrix to a data frame using as.data.frame(). In that case the previous answers (using subset or m$three) will work, otherwise they will not.

To perform the operation on a matrix, you can define a column by name:

m[m[, "three"] == 11,]

Or by number:

m[m[,3] == 11,]

Note that if only one row matches, the result is an integer vector, not a matrix.

Extract rows for the first occurrence of a variable in a data frame

t.first <- species[match(unique(species$Taxa), species$Taxa),]

should give you what you're looking for. match returns indices of the first match in the compared vectors, which give you the rows you need.

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