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Is there a way to create a data frame with rows for combinations of variables in other data frames?

How to join (merge) data frames (inner, outer, left, right)Drop data frame columns by nameCreate an empty data.frameMerge data frames of unequal number of rowsCreate vector of data frame subsets based on group by of columnsChanging Column Names in a List of Data Frames in RHow to substitute some values of one dataframe with other data frame in R?How to keep merging data frames using a function in R?Python Pandas - Find difference between two data framesPandas create a data frame based on two other 'sub' frames

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0

I have several data frames containing one column each. I want to create a data frame which has rows for each possible combination of the values in the other data frames.

I tried a workaround with nested for loops for each data frame but since i have about 20 data frames it became tedious quite fast.

# the data frames I already have
df1 <- data.frame(c("A","B","C")) 
colnames(df1) <- c("x")
df2 <- data.frame(c("ALPHA","BRAVO","CHARLIE")) 
colnames(df2) <- c("y")

# the data frame I want to create
df3 <- data.frame(c("A", "A", "A", "B", "B", "B", "C", "C", "C"),
 c("ALPHA","BRAVO","CHARLIE", "ALPHA","BRAVO","CHARLIE", "ALPHA","BRAVO","CHARLIE"))
colnames(df3) <- c("x", "y")

r dataframe

share|improve this question

asked Mar 25 at 12:35

erikfjonssonerikfjonsson

4877 bronze badges

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  For completeness: data.table::CJ
  
  – r2evans
  Mar 25 at 12:48
  

  
  
  
  

add a comment | 

0

I have several data frames containing one column each. I want to create a data frame which has rows for each possible combination of the values in the other data frames.

I tried a workaround with nested for loops for each data frame but since i have about 20 data frames it became tedious quite fast.

# the data frames I already have
df1 <- data.frame(c("A","B","C")) 
colnames(df1) <- c("x")
df2 <- data.frame(c("ALPHA","BRAVO","CHARLIE")) 
colnames(df2) <- c("y")

# the data frame I want to create
df3 <- data.frame(c("A", "A", "A", "B", "B", "B", "C", "C", "C"),
 c("ALPHA","BRAVO","CHARLIE", "ALPHA","BRAVO","CHARLIE", "ALPHA","BRAVO","CHARLIE"))
colnames(df3) <- c("x", "y")

r dataframe

share|improve this question

asked Mar 25 at 12:35

erikfjonssonerikfjonsson

4877 bronze badges

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  For completeness: data.table::CJ
  
  – r2evans
  Mar 25 at 12:48
  

  
  
  
  

add a comment | 

I have several data frames containing one column each. I want to create a data frame which has rows for each possible combination of the values in the other data frames.

I tried a workaround with nested for loops for each data frame but since i have about 20 data frames it became tedious quite fast.

# the data frames I already have
df1 <- data.frame(c("A","B","C")) 
colnames(df1) <- c("x")
df2 <- data.frame(c("ALPHA","BRAVO","CHARLIE")) 
colnames(df2) <- c("y")

# the data frame I want to create
df3 <- data.frame(c("A", "A", "A", "B", "B", "B", "C", "C", "C"),
 c("ALPHA","BRAVO","CHARLIE", "ALPHA","BRAVO","CHARLIE", "ALPHA","BRAVO","CHARLIE"))
colnames(df3) <- c("x", "y")

r dataframe

share|improve this question

asked Mar 25 at 12:35

erikfjonssonerikfjonsson

4877 bronze badges

# the data frames I already have
df1 <- data.frame(c("A","B","C")) 
colnames(df1) <- c("x")
df2 <- data.frame(c("ALPHA","BRAVO","CHARLIE")) 
colnames(df2) <- c("y")

# the data frame I want to create
df3 <- data.frame(c("A", "A", "A", "B", "B", "B", "C", "C", "C"),
 c("ALPHA","BRAVO","CHARLIE", "ALPHA","BRAVO","CHARLIE", "ALPHA","BRAVO","CHARLIE"))
colnames(df3) <- c("x", "y")

share|improve this question

asked Mar 25 at 12:35

erikfjonssonerikfjonsson

4877 bronze badges

share|improve this question

asked Mar 25 at 12:35

erikfjonssonerikfjonsson

4877 bronze badges

asked Mar 25 at 12:35

erikfjonssonerikfjonsson

4877 bronze badges

asked Mar 25 at 12:35

erikfjonssonerikfjonsson

4877 bronze badges

2 Answers
2

active

oldest

votes

3

One option is to use tidyr::crossing

tidyr::crossing(df1, df2)

# df1$x df2$y 
# <fct> <fct> 
#1 A ALPHA 
#2 A BRAVO 
#3 A CHARLIE
#4 B ALPHA 
#5 B BRAVO 
#6 B CHARLIE
#7 C ALPHA 
#8 C BRAVO 
#9 C CHARLIE

You can just add all the dataframes in it and it would give you output for all combinations of it.

---

In base R, you could also use merge in Reduce by putting all the dataframes in one list.

Reduce(merge, list(df1, df2))

share|improve this answer

edited Mar 25 at 12:48

answered Mar 25 at 12:42

Ronak ShahRonak Shah

62.7k1010 gold badges4646 silver badges8080 bronze badges

add a comment | 

0

We can use CJ from data.table

library(data.table)
CJ(x= df1$x, y = df2$y)
# x y
#1: A ALPHA
#2: A BRAVO
#3: A CHARLIE
#4: B ALPHA
#5: B BRAVO
#6: B CHARLIE
#7: C ALPHA
#8: C BRAVO
#9: C CHARLIE

share|improve this answer

answered Mar 25 at 15:08

akrunakrun

443k1414 gold badges245245 silver badges325325 bronze badges

add a comment | 

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3

One option is to use tidyr::crossing

tidyr::crossing(df1, df2)

# df1$x df2$y 
# <fct> <fct> 
#1 A ALPHA 
#2 A BRAVO 
#3 A CHARLIE
#4 B ALPHA 
#5 B BRAVO 
#6 B CHARLIE
#7 C ALPHA 
#8 C BRAVO 
#9 C CHARLIE

You can just add all the dataframes in it and it would give you output for all combinations of it.

---

In base R, you could also use merge in Reduce by putting all the dataframes in one list.

Reduce(merge, list(df1, df2))

share|improve this answer

edited Mar 25 at 12:48

answered Mar 25 at 12:42

Ronak ShahRonak Shah

62.7k1010 gold badges4646 silver badges8080 bronze badges

add a comment | 

3

One option is to use tidyr::crossing

tidyr::crossing(df1, df2)

# df1$x df2$y 
# <fct> <fct> 
#1 A ALPHA 
#2 A BRAVO 
#3 A CHARLIE
#4 B ALPHA 
#5 B BRAVO 
#6 B CHARLIE
#7 C ALPHA 
#8 C BRAVO 
#9 C CHARLIE

You can just add all the dataframes in it and it would give you output for all combinations of it.

---

In base R, you could also use merge in Reduce by putting all the dataframes in one list.

Reduce(merge, list(df1, df2))

share|improve this answer

edited Mar 25 at 12:48

answered Mar 25 at 12:42

Ronak ShahRonak Shah

62.7k1010 gold badges4646 silver badges8080 bronze badges

add a comment | 

One option is to use tidyr::crossing

tidyr::crossing(df1, df2)

# df1$x df2$y 
# <fct> <fct> 
#1 A ALPHA 
#2 A BRAVO 
#3 A CHARLIE
#4 B ALPHA 
#5 B BRAVO 
#6 B CHARLIE
#7 C ALPHA 
#8 C BRAVO 
#9 C CHARLIE

You can just add all the dataframes in it and it would give you output for all combinations of it.

---

In base R, you could also use merge in Reduce by putting all the dataframes in one list.

Reduce(merge, list(df1, df2))

share|improve this answer

edited Mar 25 at 12:48

answered Mar 25 at 12:42

Ronak ShahRonak Shah

62.7k1010 gold badges4646 silver badges8080 bronze badges

tidyr::crossing(df1, df2)

# df1$x df2$y 
# <fct> <fct> 
#1 A ALPHA 
#2 A BRAVO 
#3 A CHARLIE
#4 B ALPHA 
#5 B BRAVO 
#6 B CHARLIE
#7 C ALPHA 
#8 C BRAVO 
#9 C CHARLIE

Reduce(merge, list(df1, df2))

share|improve this answer

edited Mar 25 at 12:48

answered Mar 25 at 12:42

Ronak ShahRonak Shah

62.7k1010 gold badges4646 silver badges8080 bronze badges

answered Mar 25 at 12:42

Ronak ShahRonak Shah

62.7k1010 gold badges4646 silver badges8080 bronze badges

answered Mar 25 at 12:42

Ronak ShahRonak Shah

62.7k1010 gold badges4646 silver badges8080 bronze badges

0

We can use CJ from data.table

library(data.table)
CJ(x= df1$x, y = df2$y)
# x y
#1: A ALPHA
#2: A BRAVO
#3: A CHARLIE
#4: B ALPHA
#5: B BRAVO
#6: B CHARLIE
#7: C ALPHA
#8: C BRAVO
#9: C CHARLIE

share|improve this answer

answered Mar 25 at 15:08

akrunakrun

443k1414 gold badges245245 silver badges325325 bronze badges

add a comment | 

0

We can use CJ from data.table

library(data.table)
CJ(x= df1$x, y = df2$y)
# x y
#1: A ALPHA
#2: A BRAVO
#3: A CHARLIE
#4: B ALPHA
#5: B BRAVO
#6: B CHARLIE
#7: C ALPHA
#8: C BRAVO
#9: C CHARLIE

share|improve this answer

answered Mar 25 at 15:08

akrunakrun

443k1414 gold badges245245 silver badges325325 bronze badges

add a comment | 

We can use CJ from data.table

library(data.table)
CJ(x= df1$x, y = df2$y)
# x y
#1: A ALPHA
#2: A BRAVO
#3: A CHARLIE
#4: B ALPHA
#5: B BRAVO
#6: B CHARLIE
#7: C ALPHA
#8: C BRAVO
#9: C CHARLIE

share|improve this answer

answered Mar 25 at 15:08

akrunakrun

443k1414 gold badges245245 silver badges325325 bronze badges

library(data.table)
CJ(x= df1$x, y = df2$y)
# x y
#1: A ALPHA
#2: A BRAVO
#3: A CHARLIE
#4: B ALPHA
#5: B BRAVO
#6: B CHARLIE
#7: C ALPHA
#8: C BRAVO
#9: C CHARLIE

share|improve this answer

answered Mar 25 at 15:08

akrunakrun

443k1414 gold badges245245 silver badges325325 bronze badges

answered Mar 25 at 15:08

akrunakrun

443k1414 gold badges245245 silver badges325325 bronze badges

answered Mar 25 at 15:08

akrunakrun

443k1414 gold badges245245 silver badges325325 bronze badges