将 R 中的行与 Pivot 或 Spread 结合起来？
Combining Rows in R with Pivot or Spread?
这里我操作的是选举数据，目前的数据格式如下。包括视觉和编码示例（虽然视觉有点浓缩）。此外，值已从其原始值进行了编辑。
# Representative Example
library(tidyverse)
test.df <- tibble(yr=rep(1956),mn=rep(11),
sub=rep("Alabama"),
unit_type=rep("County"),
unit_name=c("Autauga","Baldwin","Barbour"),
TotalVotes=c(1000,2000,3000),
RepVotes=c(500,1000,1500),
RepCandidate=rep("Eisenhower"),
DemVotes=c(500,1000,1500),
DemCandidate=rep("Stevenson"),
ThirdVotes=c(0,0,0),
ThirdCandidate=rep("Uncommitted"),
RepVotesTotalPerc=rep(50.00),
DemVotesTotalPerc=rep(50.00),
ThirdVotesTotalPerc=rep(0.00)
)
----------------------------------------------------------------------------------------------------
yr | mn | sub | unit_type | unit_name | TotalVotes | RepVotes | RepCan | DemVotes | DemCan
----------------------------------------------------------------------------------------------------
1956 11 Alabama County Autauga 1000 500 EisenHower 500 Stevenson
----------------------------------------------------------------------------------------------------
1956 11 Alabama County Baldwin 2000 1000 EisenHower 1000 Stevenson
----------------------------------------------------------------------------------------------------
1956 11 Alabama County Barbour 3000 2000 EisenHower 2000 Stevenson
----------------------------------------------------------------------------------------------------
我正在尝试获得如下所示的 table：
----------------------------------------------------------------------------------------------------
yr | mn | sub | unit_type | unit_name | pty_n | can | TotalVotes | CanVotes
----------------------------------------------------------------------------------------------------
1956 11 Alabama County Autauga Republican Eisenhower 1000 500
----------------------------------------------------------------------------------------------------
1956 11 Alabama County Autauga Democrat Stevenson 1000 500
----------------------------------------------------------------------------------------------------
1956 11 Alabama County Autauga Independent Uncommitted 1000 0
----------------------------------------------------------------------------------------------------
# and etc. for other counties in example (Baldwin, Barbour, etc)
如您所见，我非常希望每个县有三个观察值，候选人都在一栏中，而他们各自的选票则在另一栏中（CanVotes，等等）。
我曾尝试使用 pivot_longer() 或 spread() 之类的东西，但我很难在代码中将它们可视化。如果能重新调整我的数据以获得候选列，同时移动其余数据，我们将不胜感激！
这是一个解决方案，首先使用 pivot_longer 将投票转换为长格式。然后我使用 mutate 和 case_when 将以前的列名称替换为实际的候选名称并删除单个候选列：
long_table <- pivot_longer(test.df,
cols = c(RepVotes, DemVotes, ThirdVotes),
names_to = "pty_n",
values_to = "CanVotes") %>%
mutate(can = case_when(
pty_n == "RepVotes" ~ RepCandidate,
pty_n == "DemVotes" ~ DemCandidate,
pty_n == "ThirdVotes" ~ ThirdCandidate
),
pty_n = case_when(
pty_n == "RepVotes" ~ "Republican",
pty_n == "DemVotes" ~ "Democrat",
pty_n == "ThirdVotes" ~ "Independent"
)) %>%
select(-c(RepCandidate, DemCandidate, ThirdCandidate))
# A tibble: 9 x 12
yr mn sub unit_type unit_name TotalVotes RepVotesTotalPerc DemVotesTotalPerc ThirdVotesTotalPe~ pty_n CanVotes can
<dbl> <dbl> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <chr> <dbl> <chr>
1 1956 11 Alabama County Autauga 1000 50 50 0 Republican 500 Eisenhower
2 1956 11 Alabama County Autauga 1000 50 50 0 Democrat 500 Stevenson
3 1956 11 Alabama County Autauga 1000 50 50 0 Independe~ 0 Uncommitt~
4 1956 11 Alabama County Baldwin 2000 50 50 0 Republican 1000 Eisenhower
5 1956 11 Alabama County Baldwin 2000 50 50 0 Democrat 1000 Stevenson
6 1956 11 Alabama County Baldwin 2000 50 50 0 Independe~ 0 Uncommitt~
7 1956 11 Alabama County Barbour 3000 50 50 0 Republican 1500 Eisenhower
8 1956 11 Alabama County Barbour 3000 50 50 0 Democrat 1500 Stevenson
9 1956 11 Alabama County Barbour 3000 50 50 0 Independe~ 0 Uncommitt~
我尝试构建自定义 spec，但名称似乎必须从列名派生，不能直接以其他列为条件。
这里是data.table做事
library( data.table )
#convert data to the data.table-format
setDT( test.df )
#get the different paries to update the variable balter in
parties <- gsub( "Candidate", "", grep( "^.*Candidate$", names( test.df ), value = TRUE ) )
#melt to each candidate and his/her votes
DT.melt <- melt(test.df,
id.vars = c("yr", "mn", "sub", "unit_type", "unit_name"),
measure.vars = patterns( can = "^.*Candidate$",
canVotes = "^(Rep|Dem|Third)Votes$" ),
variable.name = "pty_n"
)
#get the totals from the original date (by unit_name) through joining
DT.melt[ test.df, TotalVotes := i.TotalVotes, on = .(unit_name)]
#and pass the correct party name to the pty_n column
DT.melt[, pty_n := parties[ pty_n ] ][]
# yr mn sub unit_type unit_name pty_n can canVotes TotalVotes
# 1: 1956 11 Alabama County Autauga Rep Eisenhower 500 1000
# 2: 1956 11 Alabama County Baldwin Rep Eisenhower 1000 2000
# 3: 1956 11 Alabama County Barbour Rep Eisenhower 1500 3000
# 4: 1956 11 Alabama County Autauga Dem Stevenson 500 1000
# 5: 1956 11 Alabama County Baldwin Dem Stevenson 1000 2000
# 6: 1956 11 Alabama County Barbour Dem Stevenson 1500 3000
# 7: 1956 11 Alabama County Autauga Third Uncommitted 0 1000
# 8: 1956 11 Alabama County Baldwin Third Uncommitted 0 2000
# 9: 1956 11 Alabama County Barbour Third Uncommitted 0 3000
这里我操作的是选举数据，目前的数据格式如下。包括视觉和编码示例（虽然视觉有点浓缩）。此外，值已从其原始值进行了编辑。
# Representative Example
library(tidyverse)
test.df <- tibble(yr=rep(1956),mn=rep(11),
sub=rep("Alabama"),
unit_type=rep("County"),
unit_name=c("Autauga","Baldwin","Barbour"),
TotalVotes=c(1000,2000,3000),
RepVotes=c(500,1000,1500),
RepCandidate=rep("Eisenhower"),
DemVotes=c(500,1000,1500),
DemCandidate=rep("Stevenson"),
ThirdVotes=c(0,0,0),
ThirdCandidate=rep("Uncommitted"),
RepVotesTotalPerc=rep(50.00),
DemVotesTotalPerc=rep(50.00),
ThirdVotesTotalPerc=rep(0.00)
)
----------------------------------------------------------------------------------------------------
yr | mn | sub | unit_type | unit_name | TotalVotes | RepVotes | RepCan | DemVotes | DemCan
----------------------------------------------------------------------------------------------------
1956 11 Alabama County Autauga 1000 500 EisenHower 500 Stevenson
----------------------------------------------------------------------------------------------------
1956 11 Alabama County Baldwin 2000 1000 EisenHower 1000 Stevenson
----------------------------------------------------------------------------------------------------
1956 11 Alabama County Barbour 3000 2000 EisenHower 2000 Stevenson
----------------------------------------------------------------------------------------------------
我正在尝试获得如下所示的 table：
----------------------------------------------------------------------------------------------------
yr | mn | sub | unit_type | unit_name | pty_n | can | TotalVotes | CanVotes
----------------------------------------------------------------------------------------------------
1956 11 Alabama County Autauga Republican Eisenhower 1000 500
----------------------------------------------------------------------------------------------------
1956 11 Alabama County Autauga Democrat Stevenson 1000 500
----------------------------------------------------------------------------------------------------
1956 11 Alabama County Autauga Independent Uncommitted 1000 0
----------------------------------------------------------------------------------------------------
# and etc. for other counties in example (Baldwin, Barbour, etc)
如您所见，我非常希望每个县有三个观察值，候选人都在一栏中，而他们各自的选票则在另一栏中（CanVotes，等等）。
我曾尝试使用 pivot_longer() 或 spread() 之类的东西，但我很难在代码中将它们可视化。如果能重新调整我的数据以获得候选列，同时移动其余数据，我们将不胜感激！
这是一个解决方案，首先使用 pivot_longer 将投票转换为长格式。然后我使用 mutate 和 case_when 将以前的列名称替换为实际的候选名称并删除单个候选列：
long_table <- pivot_longer(test.df,
cols = c(RepVotes, DemVotes, ThirdVotes),
names_to = "pty_n",
values_to = "CanVotes") %>%
mutate(can = case_when(
pty_n == "RepVotes" ~ RepCandidate,
pty_n == "DemVotes" ~ DemCandidate,
pty_n == "ThirdVotes" ~ ThirdCandidate
),
pty_n = case_when(
pty_n == "RepVotes" ~ "Republican",
pty_n == "DemVotes" ~ "Democrat",
pty_n == "ThirdVotes" ~ "Independent"
)) %>%
select(-c(RepCandidate, DemCandidate, ThirdCandidate))
# A tibble: 9 x 12
yr mn sub unit_type unit_name TotalVotes RepVotesTotalPerc DemVotesTotalPerc ThirdVotesTotalPe~ pty_n CanVotes can
<dbl> <dbl> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <chr> <dbl> <chr>
1 1956 11 Alabama County Autauga 1000 50 50 0 Republican 500 Eisenhower
2 1956 11 Alabama County Autauga 1000 50 50 0 Democrat 500 Stevenson
3 1956 11 Alabama County Autauga 1000 50 50 0 Independe~ 0 Uncommitt~
4 1956 11 Alabama County Baldwin 2000 50 50 0 Republican 1000 Eisenhower
5 1956 11 Alabama County Baldwin 2000 50 50 0 Democrat 1000 Stevenson
6 1956 11 Alabama County Baldwin 2000 50 50 0 Independe~ 0 Uncommitt~
7 1956 11 Alabama County Barbour 3000 50 50 0 Republican 1500 Eisenhower
8 1956 11 Alabama County Barbour 3000 50 50 0 Democrat 1500 Stevenson
9 1956 11 Alabama County Barbour 3000 50 50 0 Independe~ 0 Uncommitt~
我尝试构建自定义 spec，但名称似乎必须从列名派生，不能直接以其他列为条件。
这里是data.table做事
library( data.table )
#convert data to the data.table-format
setDT( test.df )
#get the different paries to update the variable balter in
parties <- gsub( "Candidate", "", grep( "^.*Candidate$", names( test.df ), value = TRUE ) )
#melt to each candidate and his/her votes
DT.melt <- melt(test.df,
id.vars = c("yr", "mn", "sub", "unit_type", "unit_name"),
measure.vars = patterns( can = "^.*Candidate$",
canVotes = "^(Rep|Dem|Third)Votes$" ),
variable.name = "pty_n"
)
#get the totals from the original date (by unit_name) through joining
DT.melt[ test.df, TotalVotes := i.TotalVotes, on = .(unit_name)]
#and pass the correct party name to the pty_n column
DT.melt[, pty_n := parties[ pty_n ] ][]
# yr mn sub unit_type unit_name pty_n can canVotes TotalVotes
# 1: 1956 11 Alabama County Autauga Rep Eisenhower 500 1000
# 2: 1956 11 Alabama County Baldwin Rep Eisenhower 1000 2000
# 3: 1956 11 Alabama County Barbour Rep Eisenhower 1500 3000
# 4: 1956 11 Alabama County Autauga Dem Stevenson 500 1000
# 5: 1956 11 Alabama County Baldwin Dem Stevenson 1000 2000
# 6: 1956 11 Alabama County Barbour Dem Stevenson 1500 3000
# 7: 1956 11 Alabama County Autauga Third Uncommitted 0 1000
# 8: 1956 11 Alabama County Baldwin Third Uncommitted 0 2000
# 9: 1956 11 Alabama County Barbour Third Uncommitted 0 3000