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r data table wide to long

Tiange Ye answered on July 11, 2022 Popularity 4/10 Helpfulness 5/10

answer r data table wide to long

related r data table long to wide

r data table wide to long

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DT.m1 = melt(DT, id.vars = c("family_id", "age_mother"),
                measure.vars = c("dob_child1", "dob_child2", "dob_child3"))
DT.m1
#     family_id age_mother   variable      value
#  1:         1         30 dob_child1 1998-11-26
#  2:         2         27 dob_child1 1996-06-22
#  3:         3         26 dob_child1 2002-07-11
#  4:         4         32 dob_child1 2004-10-10
#  5:         5         29 dob_child1 2000-12-05
#  6:         1         30 dob_child2 2000-01-29
#  7:         2         27 dob_child2       <NA>
#  8:         3         26 dob_child2 2004-04-05
#  9:         4         32 dob_child2 2009-08-27
# 10:         5         29 dob_child2 2005-02-28
# 11:         1         30 dob_child3       <NA>
# 12:         2         27 dob_child3       <NA>
# 13:         3         26 dob_child3 2007-09-02
# 14:         4         32 dob_child3 2012-07-21
# 15:         5         29 dob_child3       <NA>
str(DT.m1)
# Classes 'data.table' and 'data.frame':    15 obs. of  4 variables:
#  $ family_id : int  1 2 3 4 5 1 2 3 4 5 ...
#  $ age_mother: int  30 27 26 32 29 30 27 26 32 29 ...
#  $ variable  : Factor w/ 3 levels "dob_child1","dob_child2",..: 1 1 1 1 1 2 2 2 2 2 ...
#  $ value     : IDate, format: "1998-11-26" "1996-06-22" "2002-07-11" ...
#  - attr(*, ".internal.selfref")=<externalptr>

Popularity 4/10 Helpfulness 5/10 Language whatever

Source: cran.r-project.org

Tags: r whatever

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Contributed on Jul 11 2022

Tiange Ye

0 Answers Avg Quality 2/10

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r data table long to wide

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## new 'cast' functionality - multiple value.vars
DT.c2 = dcast(DT.m2, family_id + age_mother ~ variable, value.var = c("dob", "gender"))
DT.c2
#    family_id age_mother      dob_1      dob_2      dob_3 gender_1 gender_2 gender_3
# 1:         1         30 1998-11-26 2000-01-29       <NA>        1        2       NA
# 2:         2         27 1996-06-22       <NA>       <NA>        2       NA       NA
# 3:         3         26 2002-07-11 2004-04-05 2007-09-02        2        2        1
# 4:         4         32 2004-10-10 2009-08-27 2012-07-21        1        1        1
# 5:         5         29 2000-12-05 2005-02-28       <NA>        2        1       NA

Popularity 4/10 Helpfulness 2/10 Language whatever

Source: cran.r-project.org

Tags: whatever r

Link to this answer
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Contributed on Jul 11 2022

Tiange Ye

0 Answers Avg Quality 2/10

r data table wide to long

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