如何基于R中的某些条件和总和对多行进行分组？

Question

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Hi All, Example :- The above is the data I have. I want to group age 1-2 and count the values. In this data value is 4 for age group 1-2. Similarly I want to group age 3-4 and count the values. Here the value for age group 3-4 is 6.

How can I group age and aggregate the values correspond to it?

I know this way: code-

data.frame(df %>% group_by(df$Age) %>% tally())

But the values are aggregating on individual Age. I want the values aggregating on multiple age to be a group as mentioned above example.

Any help on this will be greatly helpful. Thanks a lot to All.

Answer 1

Here's one way using dplyr and ?cut from base R -

df <- data.frame(age = c(1,1,2,2,3,3,3,4,4,4),
                 Name = letters[1:10],
                 stringsAsFactors = F)

df %>% 
  count(grp = cut(age, breaks = c(0,2,4)))

# A tibble: 2 x 2
  grp       n
  <fct> <int>
1 (0,2]     4
2 (2,4]     6

Answer 2

Here are two solutions, with base R and with package dplyr .
I will use the data posted by Shree .

First , base R.
I create a grouping variable grp and then aggregate on it.

grp <- with(df, c((age %in% 1:2) + 2*(age %in% 3:4)))
aggregate(age ~ grp, df, length)
#  grp age
#1   1   4
#2   2   6

Second a dplyr way.
Function case_when is used to create a grouping variable. This allows for meaningful names to be given to the groups in an easy way.

library(dplyr)

df %>%
  mutate(grp = case_when(
    age %in% 1:2 ~ "2:3",
    age %in% 3:4 ~ "3:4",
    TRUE ~ NA_character_
  )) %>%
  group_by(grp) %>%
  tally()
## A tibble: 2 x 2
#  grp       n
#  <chr> <int>
#1 1:2       4
#2 3:4       6