R: Return the first “n” rows and group the remaining rows into “Other” row and summarise the column

I'm Brazilian, sorry about my english!

I would like to know if there is an function implemented in some R package to filter first "n" rows and group the remaining into an "Other" row and summarise the column.

Here is below an example of what I want:

library(tidyverse)

library(plotly)

library(scales)  

data("lakers")



x = bind_rows(  

lakers %>% count(player) %>% arrange(-n) %>% head(10),  

lakers %>% count(player) %>% arrange(-n) %>% slice(11:n()) %>%  

summarise(player = "Others", n = sum(n))) %>%  

  filter(!player == "") %>%  

  mutate(

    player = factor(player, levels = rev(.$player)))



ggplot(x, aes(x=player, y=n))+  

  geom_col(fill = "DodgerBlue1", col = "DodgerBlue3")+  

  coord_flip()+  

  geom_text(aes(y=n, label = comma(n)),hjust = -.2)+  

  scale_y_continuous(limits = c(0, max( x$n*1.1 )))+  

  theme_minimal()

I need to create an ggplot like that. So I have a big query using dplyr and I don't want to repeat the query every time.

I would like some function like:

head.other(x, rows = 20, fun = sum, name = "Others")

edited Nov 13 '18 at 12:59

asked Nov 13 '18 at 12:49

Rodrigo Cardoso

add a comment |

I'm Brazilian, sorry about my english!

I would like to know if there is an function implemented in some R package to filter first "n" rows and group the remaining into an "Other" row and summarise the column.

Here is below an example of what I want:

library(tidyverse)

library(plotly)

library(scales)  

data("lakers")



x = bind_rows(  

lakers %>% count(player) %>% arrange(-n) %>% head(10),  

lakers %>% count(player) %>% arrange(-n) %>% slice(11:n()) %>%  

summarise(player = "Others", n = sum(n))) %>%  

  filter(!player == "") %>%  

  mutate(

    player = factor(player, levels = rev(.$player)))



ggplot(x, aes(x=player, y=n))+  

  geom_col(fill = "DodgerBlue1", col = "DodgerBlue3")+  

  coord_flip()+  

  geom_text(aes(y=n, label = comma(n)),hjust = -.2)+  

  scale_y_continuous(limits = c(0, max( x$n*1.1 )))+  

  theme_minimal()

I need to create an ggplot like that. So I have a big query using dplyr and I don't want to repeat the query every time.

I would like some function like:

head.other(x, rows = 20, fun = sum, name = "Others")

edited Nov 13 '18 at 12:59

asked Nov 13 '18 at 12:49

Rodrigo Cardoso

add a comment |

I'm Brazilian, sorry about my english!

I would like to know if there is an function implemented in some R package to filter first "n" rows and group the remaining into an "Other" row and summarise the column.

Here is below an example of what I want:

library(tidyverse)

library(plotly)

library(scales)  

data("lakers")



x = bind_rows(  

lakers %>% count(player) %>% arrange(-n) %>% head(10),  

lakers %>% count(player) %>% arrange(-n) %>% slice(11:n()) %>%  

summarise(player = "Others", n = sum(n))) %>%  

  filter(!player == "") %>%  

  mutate(

    player = factor(player, levels = rev(.$player)))



ggplot(x, aes(x=player, y=n))+  

  geom_col(fill = "DodgerBlue1", col = "DodgerBlue3")+  

  coord_flip()+  

  geom_text(aes(y=n, label = comma(n)),hjust = -.2)+  

  scale_y_continuous(limits = c(0, max( x$n*1.1 )))+  

  theme_minimal()

I need to create an ggplot like that. So I have a big query using dplyr and I don't want to repeat the query every time.

I would like some function like:

head.other(x, rows = 20, fun = sum, name = "Others")

edited Nov 13 '18 at 12:59

asked Nov 13 '18 at 12:49

Rodrigo Cardoso

I'm Brazilian, sorry about my english!

I would like to know if there is an function implemented in some R package to filter first "n" rows and group the remaining into an "Other" row and summarise the column.

Here is below an example of what I want:

library(tidyverse)

library(plotly)

library(scales)  

data("lakers")



x = bind_rows(  

lakers %>% count(player) %>% arrange(-n) %>% head(10),  

lakers %>% count(player) %>% arrange(-n) %>% slice(11:n()) %>%  

summarise(player = "Others", n = sum(n))) %>%  

  filter(!player == "") %>%  

  mutate(

    player = factor(player, levels = rev(.$player)))



ggplot(x, aes(x=player, y=n))+  

  geom_col(fill = "DodgerBlue1", col = "DodgerBlue3")+  

  coord_flip()+  

  geom_text(aes(y=n, label = comma(n)),hjust = -.2)+  

  scale_y_continuous(limits = c(0, max( x$n*1.1 )))+  

  theme_minimal()

I need to create an ggplot like that. So I have a big query using dplyr and I don't want to repeat the query every time.

I would like some function like:

head.other(x, rows = 20, fun = sum, name = "Others")

r dplyr tidyr

edited Nov 13 '18 at 12:59

asked Nov 13 '18 at 12:49

Rodrigo Cardoso

edited Nov 13 '18 at 12:59

asked Nov 13 '18 at 12:49

Rodrigo Cardoso

edited Nov 13 '18 at 12:59

asked Nov 13 '18 at 12:49

Rodrigo Cardoso

asked Nov 13 '18 at 12:49

Rodrigo Cardoso

asked Nov 13 '18 at 12:49

Rodrigo Cardoso

add a comment |

1 Answer
1

active

oldest

votes

Here is a function that I think will give you what you need:

library(tibble)

library(dplyr)



df <- data.frame(col1 = rnorm(10), col2 = rnorm(10)) # your data frame

n <- 6 # top n rows to keep



myfun <- function(df, n) {



  # seperate keep rows and those to aggregate

  preserve.df <- df[1:n, ]

  summarise.df <- df[(n+1):nrow(df), ]



  # create new df in required format

  new.df <- bind_rows(preserve.df, sapply(summarise.df, sum))



  # add a column to identify the rows and return

  rownames(new.df) <- c(paste0("r", 1:n), "Other")

  rownames_to_column(new.df)

}



myfun(df, 6)

edited Nov 13 '18 at 13:31

answered Nov 13 '18 at 13:23

Cleland

1656

add a comment |

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1 Answer
1

active

oldest

votes

1 Answer
1

active

oldest

votes

Here is a function that I think will give you what you need:

library(tibble)

library(dplyr)



df <- data.frame(col1 = rnorm(10), col2 = rnorm(10)) # your data frame

n <- 6 # top n rows to keep



myfun <- function(df, n) {



  # seperate keep rows and those to aggregate

  preserve.df <- df[1:n, ]

  summarise.df <- df[(n+1):nrow(df), ]



  # create new df in required format

  new.df <- bind_rows(preserve.df, sapply(summarise.df, sum))



  # add a column to identify the rows and return

  rownames(new.df) <- c(paste0("r", 1:n), "Other")

  rownames_to_column(new.df)

}



myfun(df, 6)

edited Nov 13 '18 at 13:31

answered Nov 13 '18 at 13:23

Cleland

1656

add a comment |

Here is a function that I think will give you what you need:

library(tibble)

library(dplyr)



df <- data.frame(col1 = rnorm(10), col2 = rnorm(10)) # your data frame

n <- 6 # top n rows to keep



myfun <- function(df, n) {



  # seperate keep rows and those to aggregate

  preserve.df <- df[1:n, ]

  summarise.df <- df[(n+1):nrow(df), ]



  # create new df in required format

  new.df <- bind_rows(preserve.df, sapply(summarise.df, sum))



  # add a column to identify the rows and return

  rownames(new.df) <- c(paste0("r", 1:n), "Other")

  rownames_to_column(new.df)

}



myfun(df, 6)

edited Nov 13 '18 at 13:31

answered Nov 13 '18 at 13:23

Cleland

1656

add a comment |

Here is a function that I think will give you what you need:

library(tibble)

library(dplyr)



df <- data.frame(col1 = rnorm(10), col2 = rnorm(10)) # your data frame

n <- 6 # top n rows to keep



myfun <- function(df, n) {



  # seperate keep rows and those to aggregate

  preserve.df <- df[1:n, ]

  summarise.df <- df[(n+1):nrow(df), ]



  # create new df in required format

  new.df <- bind_rows(preserve.df, sapply(summarise.df, sum))



  # add a column to identify the rows and return

  rownames(new.df) <- c(paste0("r", 1:n), "Other")

  rownames_to_column(new.df)

}



myfun(df, 6)

edited Nov 13 '18 at 13:31

answered Nov 13 '18 at 13:23

Cleland

1656

Here is a function that I think will give you what you need:

library(tibble)

library(dplyr)



df <- data.frame(col1 = rnorm(10), col2 = rnorm(10)) # your data frame

n <- 6 # top n rows to keep



myfun <- function(df, n) {



  # seperate keep rows and those to aggregate

  preserve.df <- df[1:n, ]

  summarise.df <- df[(n+1):nrow(df), ]



  # create new df in required format

  new.df <- bind_rows(preserve.df, sapply(summarise.df, sum))



  # add a column to identify the rows and return

  rownames(new.df) <- c(paste0("r", 1:n), "Other")

  rownames_to_column(new.df)

}



myfun(df, 6)

edited Nov 13 '18 at 13:31

answered Nov 13 '18 at 13:23

Cleland

1656

edited Nov 13 '18 at 13:31

answered Nov 13 '18 at 13:23

Cleland

1656

answered Nov 13 '18 at 13:23

Cleland

1656

answered Nov 13 '18 at 13:23

Cleland

1656

add a comment |

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