tidyverse equivalent to reshape [duplicate]

This question already has an answer here:

Reshaping multiple sets of measurement columns (wide format) into single columns (long format)

6 answers

How would I achieve the following with tidyverse syntax?

set.seed(1)

d <- data.frame(prd     = rep(paste0("P", 1:5), 2),

                cluster = rep(paste0("Cluster", 1:2), each = 5),

                class   = c("l", "l", "m", "h", "h", "l", "m", "m", "h", "h"),

                score   = c(1:5, 11:15))

d <- d[sample(NROW(d)), ] ## in order to not assume any pre-order

reshape(d, idvar = "prd", timevar = "cluster", direction = "wide")

#   prd class.Cluster1 score.Cluster1 class.Cluster2 score.Cluster2

# 3  P3              m              3              m             13

# 4  P4              h              4              h             14

# 5  P5              h              5              h             15

# 7  P2              l              2              m             12

# 6  P1              l              1              l             11

The closest I came was:

library(tidyverse)

d %>% spread(score, cluster)

#   prd class Cluster1 Cluster2

# 1  P1     l        1       11

# 2  P2     l        2       NA

# 3  P2     m       NA       12

# 4  P3     m        3       13

# 5  P4     h        4       14

# 6  P5     h        5       15

So I would like to spread both columns class and score simultaneously. How would I do that in tidyverse?

asked Nov 21 '18 at 15:53

thothal

3,8701232

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Nov 21 '18 at 15:59

This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.

Just curious... why not stick with reshape() if it works well for you?

– snoram
Nov 21 '18 at 15:55

Well, I would say consistency. I do all of my data transformation with one tidyverse so I would like to stick to it also for this case.

– thothal
Nov 21 '18 at 16:51

add a comment |

This question already has an answer here:

Reshaping multiple sets of measurement columns (wide format) into single columns (long format)

6 answers

How would I achieve the following with tidyverse syntax?

set.seed(1)

d <- data.frame(prd     = rep(paste0("P", 1:5), 2),

                cluster = rep(paste0("Cluster", 1:2), each = 5),

                class   = c("l", "l", "m", "h", "h", "l", "m", "m", "h", "h"),

                score   = c(1:5, 11:15))

d <- d[sample(NROW(d)), ] ## in order to not assume any pre-order

reshape(d, idvar = "prd", timevar = "cluster", direction = "wide")

#   prd class.Cluster1 score.Cluster1 class.Cluster2 score.Cluster2

# 3  P3              m              3              m             13

# 4  P4              h              4              h             14

# 5  P5              h              5              h             15

# 7  P2              l              2              m             12

# 6  P1              l              1              l             11

The closest I came was:

library(tidyverse)

d %>% spread(score, cluster)

#   prd class Cluster1 Cluster2

# 1  P1     l        1       11

# 2  P2     l        2       NA

# 3  P2     m       NA       12

# 4  P3     m        3       13

# 5  P4     h        4       14

# 6  P5     h        5       15

So I would like to spread both columns class and score simultaneously. How would I do that in tidyverse?

asked Nov 21 '18 at 15:53

thothal

3,8701232

marked as duplicate by Henrik r
Users with the r badge can single-handedly close r questions as duplicates and reopen them as needed.

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Nov 21 '18 at 15:59

This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.

Just curious... why not stick with reshape() if it works well for you?

– snoram
Nov 21 '18 at 15:55

Well, I would say consistency. I do all of my data transformation with one tidyverse so I would like to stick to it also for this case.

– thothal
Nov 21 '18 at 16:51

add a comment |

This question already has an answer here:

Reshaping multiple sets of measurement columns (wide format) into single columns (long format)

6 answers

How would I achieve the following with tidyverse syntax?

set.seed(1)

d <- data.frame(prd     = rep(paste0("P", 1:5), 2),

                cluster = rep(paste0("Cluster", 1:2), each = 5),

                class   = c("l", "l", "m", "h", "h", "l", "m", "m", "h", "h"),

                score   = c(1:5, 11:15))

d <- d[sample(NROW(d)), ] ## in order to not assume any pre-order

reshape(d, idvar = "prd", timevar = "cluster", direction = "wide")

#   prd class.Cluster1 score.Cluster1 class.Cluster2 score.Cluster2

# 3  P3              m              3              m             13

# 4  P4              h              4              h             14

# 5  P5              h              5              h             15

# 7  P2              l              2              m             12

# 6  P1              l              1              l             11

The closest I came was:

library(tidyverse)

d %>% spread(score, cluster)

#   prd class Cluster1 Cluster2

# 1  P1     l        1       11

# 2  P2     l        2       NA

# 3  P2     m       NA       12

# 4  P3     m        3       13

# 5  P4     h        4       14

# 6  P5     h        5       15

So I would like to spread both columns class and score simultaneously. How would I do that in tidyverse?

asked Nov 21 '18 at 15:53

thothal

3,8701232

This question already has an answer here:

Reshaping multiple sets of measurement columns (wide format) into single columns (long format)

6 answers

How would I achieve the following with tidyverse syntax?

set.seed(1)

d <- data.frame(prd     = rep(paste0("P", 1:5), 2),

                cluster = rep(paste0("Cluster", 1:2), each = 5),

                class   = c("l", "l", "m", "h", "h", "l", "m", "m", "h", "h"),

                score   = c(1:5, 11:15))

d <- d[sample(NROW(d)), ] ## in order to not assume any pre-order

reshape(d, idvar = "prd", timevar = "cluster", direction = "wide")

#   prd class.Cluster1 score.Cluster1 class.Cluster2 score.Cluster2

# 3  P3              m              3              m             13

# 4  P4              h              4              h             14

# 5  P5              h              5              h             15

# 7  P2              l              2              m             12

# 6  P1              l              1              l             11

The closest I came was:

library(tidyverse)

d %>% spread(score, cluster)

#   prd class Cluster1 Cluster2

# 1  P1     l        1       11

# 2  P2     l        2       NA

# 3  P2     m       NA       12

# 4  P3     m        3       13

# 5  P4     h        4       14

# 6  P5     h        5       15

So I would like to spread both columns class and score simultaneously. How would I do that in tidyverse?

This question already has an answer here:

Reshaping multiple sets of measurement columns (wide format) into single columns (long format)

6 answers

r tidyverse

asked Nov 21 '18 at 15:53

thothal

3,8701232

asked Nov 21 '18 at 15:53

thothal

3,8701232

asked Nov 21 '18 at 15:53

thothal

3,8701232

asked Nov 21 '18 at 15:53

thothal

3,8701232

asked Nov 21 '18 at 15:53

thothal

3,8701232

marked as duplicate by Henrik r
Users with the r badge can single-handedly close r questions as duplicates and reopen them as needed.

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Nov 21 '18 at 15:59

This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.

marked as duplicate by Henrik r
Users with the r badge can single-handedly close r questions as duplicates and reopen them as needed.

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Nov 21 '18 at 15:59

This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.

Just curious... why not stick with reshape() if it works well for you?

– snoram
Nov 21 '18 at 15:55

Well, I would say consistency. I do all of my data transformation with one tidyverse so I would like to stick to it also for this case.

– thothal
Nov 21 '18 at 16:51

add a comment |

Just curious... why not stick with reshape() if it works well for you?

– snoram
Nov 21 '18 at 15:55

Well, I would say consistency. I do all of my data transformation with one tidyverse so I would like to stick to it also for this case.

– thothal
Nov 21 '18 at 16:51

Just curious... why not stick with reshape() if it works well for you?

– snoram
Nov 21 '18 at 15:55

Well, I would say consistency. I do all of my data transformation with one tidyverse so I would like to stick to it also for this case.

– thothal
Nov 21 '18 at 16:51

add a comment |

1 Answer
1

active

oldest

votes

With tidyr:

library(tidyverse)



d %>%

  gather(var, value, class:score) %>%

  unite(var, var, cluster, sep = ".") %>%

  spread(var, value)

Output:

  prd class.Cluster1 class.Cluster2 score.Cluster1

1  P1              l              l              1

2  P2              l              m              2

3  P3              m              m              3

4  P4              h              h              4

5  P5              h              h              5

  score.Cluster2

1             11

2             12

3             13

4             14

5             15

answered Nov 21 '18 at 15:58

avid_useR

12.4k41831

add a comment |

1 Answer
1

active

oldest

votes

1 Answer
1

active

oldest

votes

With tidyr:

library(tidyverse)



d %>%

  gather(var, value, class:score) %>%

  unite(var, var, cluster, sep = ".") %>%

  spread(var, value)

Output:

  prd class.Cluster1 class.Cluster2 score.Cluster1

1  P1              l              l              1

2  P2              l              m              2

3  P3              m              m              3

4  P4              h              h              4

5  P5              h              h              5

  score.Cluster2

1             11

2             12

3             13

4             14

5             15

answered Nov 21 '18 at 15:58

avid_useR

12.4k41831

add a comment |

With tidyr:

library(tidyverse)



d %>%

  gather(var, value, class:score) %>%

  unite(var, var, cluster, sep = ".") %>%

  spread(var, value)

Output:

  prd class.Cluster1 class.Cluster2 score.Cluster1

1  P1              l              l              1

2  P2              l              m              2

3  P3              m              m              3

4  P4              h              h              4

5  P5              h              h              5

  score.Cluster2

1             11

2             12

3             13

4             14

5             15

answered Nov 21 '18 at 15:58

avid_useR

12.4k41831

add a comment |

With tidyr:

library(tidyverse)



d %>%

  gather(var, value, class:score) %>%

  unite(var, var, cluster, sep = ".") %>%

  spread(var, value)

Output:

  prd class.Cluster1 class.Cluster2 score.Cluster1

1  P1              l              l              1

2  P2              l              m              2

3  P3              m              m              3

4  P4              h              h              4

5  P5              h              h              5

  score.Cluster2

1             11

2             12

3             13

4             14

5             15

answered Nov 21 '18 at 15:58

avid_useR

12.4k41831

With tidyr:

library(tidyverse)



d %>%

  gather(var, value, class:score) %>%

  unite(var, var, cluster, sep = ".") %>%

  spread(var, value)

Output:

  prd class.Cluster1 class.Cluster2 score.Cluster1

1  P1              l              l              1

2  P2              l              m              2

3  P3              m              m              3

4  P4              h              h              4

5  P5              h              h              5

  score.Cluster2

1             11

2             12

3             13

4             14

5             15

answered Nov 21 '18 at 15:58

avid_useR

12.4k41831

answered Nov 21 '18 at 15:58

avid_useR

12.4k41831

answered Nov 21 '18 at 15:58

avid_useR

12.4k41831

answered Nov 21 '18 at 15:58

avid_useR

12.4k41831

add a comment |

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