提取dataframe中每个列的列名，其中值不超过dplyr函数中定义的列范围
我正在尝试编写一个函数，该函数采用dataframe、一个确定是否满足特定条件以将该框架子集的列、一个具有数值的列、一个分组子句和一个子集名称作为参数 我希望函数检查定义范围内的哪些列的值不是NA，然后提取这些列的列名，并将它们附加到函数为dplyr根据grouping子句生成的每个汇总行生成的dplyr表中。我在一个更大、更复杂的数据帧的数百个子集上做这项工作，所以这就是为什么我需要一个可以反复使用的函数 示例数据集如下所示，我已使用扩展的数据集对其进行了更新 向那些试图帮助他人的人道歉：提取dataframe中每个列的列名，其中值不超过dplyr函数中定义的列范围,r,dataframe,dplyr,R,Dataframe,Dplyr,我正在尝试编写一个函数，该函数采用dataframe、一个确定是否满足特定条件以将该框架子集的列、一个具有数值的列、一个分组子句和一个子集名称作为参数 我希望函数检查定义范围内的哪些列的值不是NA，然后提取这些列的列名，并将它们附加到函数为dplyr根据grouping子句生成的每个汇总行生成的dplyr表中。我在一个更大、更复杂的数据帧的数百个子集上做这项工作，所以这就是为什么我需要一个可以反复使用的函数 示例数据集如下所示，我已使用扩展的数据集对其进行了更新 向那些试图帮助他人的人道歉： s
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TRUE, TRUE, TRUE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE,
TRUE, TRUE, FALSE, FALSE, TRUE, FALSE, FALSE), funder13funded = c(TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE,
TRUE, FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE,
TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE,
TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE,
FALSE), funder2funded = c(FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE), funder3funded = c(FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE), funder4funded = c(TRUE, TRUE,
TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
TRUE, TRUE, FALSE, FALSE, FALSE), funder5funded = c(TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE), sectorFunded = c("TRUE",
"TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE",
"TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE",
"TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE",
"TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE",
"TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE",
"TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE",
"TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE",
"TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE",
"TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE",
"TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE",
"TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE",
"TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE",
"TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE", "TRUE",
"TRUE", "TRUE"), totHolder = c(7000, 7000, 7000, 7000, 1500,
1500, 1500, 1500, 4000, 3000, 3000, 3000, 500, 500, 500, 500,
4500, 500, 500, 500, 4500, 500, 1500, 1500, 1500, 3000, 3000,
4000, 4000, 4500, 4500, 4500, 4500, 1500, 500, 500, 1500, 1500,
4000, 4000, 4000, 4000, 0, 0, 0, 1500, 0, 0, 0, 0, 3000, 3000,
3000, 0, 0, 0, 0, 0, 1500, 1500, 4500, 4500, 3000, 3000, 3500,
3500, 3500, 3500, 500, 500, 500, 500, 500, 500, 500, 500, 500,
500, 500, 500, 500, 500, 500, 500, 500, 7000, 7000, 4000, 4000,
3500, 3500, 3000, 3000, 3000, 3000, 3000, 4000, 4000, 500, 500,
500, 500, 6500, 3500, 500, 0, 3000)), row.names = c(NA, -107L
), class = c("tbl_df", "tbl", "data.frame"))
GRclauseSDregion <- c("year", "employerClass", "multiFunder", "serviceDivision", "healthRegion")
假设我们正在使用2020-04-01更新的GRsectorRegion，以下是所需输出 “问题是，我需要它吐出的Provvincial资金汇总值，作为所有省级资金的总和；由group子句设置的子集内的资金。因此，当我在聚合的上层运行时，就像是由出资人对整个部门运行一样，它开始给我错误的数字。此外，当我从等式中取出总数时，我无法对整个部门进行计算。” 基于您的评论和通过您的pastebin链接共享的输出，我对此进行了另一次尝试。如果这仍然不能回答您的问题，我可以请您特别分享“正确”的示例吗“回答了更广泛的分组子句数组，因为这样可以更容易地看到方法失败的位置/时间。例如，我不清楚您对“集资者对整个行业的贡献”的预期结果是什么 在显示以下更新的方法之前，有一些注意事项：
- OP中共享的数据和通过pastebin共享的输出之间似乎存在某种程度的断开。明确地：
- 似乎用于生成通过pastebin共享的输出的输入数据与OP中共享的数据有所不同
- pastebin数据包含列
，而不是根据您的操作在multiFunded
下multiFunded - pastebin数据在列下包含一个
numf，但OP中的
函数没有collapsePassFunderArray（） - 根据OP中的
函数，您的pastebin输出不包含collapsePassFunderArray（）
列medianFounder - 您的pastebin输出中
和funderPercProv
列的值让我感到困惑：我假设funderPercTot
应该表示funderfunderPercProv
的总资金占分组条款中省级资金总额的百分比。然而，尽管存在一些情况，例如，在您的示例分组条款中，x
提供的资金总额超过省级资金总额，但您的pastebin数据中的others
值从未超过1。这对我来说似乎不对，但也许我错过了什么。类似地，您的pastebin数据中的FunderPerProv
值似乎不符合funderfunderPercTot
在分组条款中占总资金百分比的定义。例如，如果您查看OP中以下过滤器适用的数据：x
，那么您可以清楚地看到，在分组条款filter（year==2015&employeerclass==class1&multifounder==F&healthRegion==Region3'）
。但是，您的pastebin输出报告该值为0.14285714(“year”、“EmployeerClass”、“Multifounder”、“healthRegion”）
funderPercProvfunderPercTot#加载所需的库
图书馆（tidyverse）
#注意：根据OP定义原始输入数据，并存储为对象可重新编程
#首先将数据转换为长格式
可谴责的_long%
选择（-totHolder）%>%
再长一点(
cols=火柴(
“^funder\\d{1，}$|其他$| ^总计$| ^省级资金$|非省级资金”
),
姓名_to=‘出资人’
)
#定义感兴趣的功能
collapsePassFunderArray%
分组依据（.dots=GRsectorRegion）%>%
过滤器（总和（值[funder==FunderVal]，na.rm=T）>0）%>%
总结(
funderName=名称，
totFund=总和（值[出资人='总额']，na.rm=T），
minFunder=min（numUnders，na.rm=T），
maxFunder=max（numUnders，na.rm=T），
avgFunder=平均值（numUnders，na.rm=真值），
medianFunder=中间值（numUnders，na.rm=TRUE），
provPerc=sum（值[funder=='provincialFunding']，na.rm=T）/
总和（值[funder='total'，na.rm=T），
非ProvPerc=总和（值[出资人='非省级基金']，na.rm=T）/
总和（值[funder='total'，na.rm=T），
FUNDERPERPROV=sum（值[funder==FunderVal]，na.rm=T）/
总和（值[funder=='provincialFunding']，na.rm=T），
funderPercTot=sum（值[funder==FunderVal]，na.rm=T）/
总和（值[funder='total'，na.rm=T），
NUMAGENCES=n_distinct（联系人ID），
出资人=出资人[！is.na（值）&！出资人%单位%
GRsectorProfile <- c("year", "employerClass", "multiFunder")
GRclass1SD <- c("year", "employerClass", "multiFunder", "serviceDivision")
GRsectorRegion <- c("year", "employerClass", "multiFunder", "healthRegion")
GRclass1SDregion <- c("year", "employerClass", "multiFunder", "serviceDivision", "healthRegion")
GRsectorAgencySize <- c("year", "employerClass", "multiFunder", "agencySize")
GRclass1AgencySize <- c("year","employerClass", "multiFunder", "agencySize")
GRclass1SDagencySize <- c("year", "employerClass", "multiFunder", "serviceDivision", "agencySize")
GRclass1SDregionAgencySize <- c("year", "employerClass", "multiFunder", "serviceDivision", "healthRegion", "agencySize")
GRnonCLASS1AregionAgencySize <- c("year", "employerClass", "multiFunder", "healthRegion", "agencySize")
GRclass1RegionAgencySize <- c("year", "employerClass", "multiFunder", "healthRegion", "agencySize")
# collapse function (funder)
collapsePassFunderArray <- function(df, funderTrueCol, fundingCol, groupClause, name) {
funderTrueHolder <- enquo(funderTrueCol)
fundingColHolder <- enquo(fundingCol)
newDf <- df %>%
filter((!!funderTrueHolder) == TRUE) %>%
group_by(.dots = groupClause) %>%
summarise(funderName = name,
totFund = sum(total),
minFunder = min(numFunders),
maxFunder = max(numFunders),
avgFunder = mean(numFunders, na.rm = TRUE),
medianFunder = median(numFunders, na.rm = TRUE),
provPerc = sum(provincialFunding)/sum(total),
nonProvPerc = sum(nonProvincialFunding)/sum(total),
funderPercProv = sum((!!fundingColHolder))/sum(provincialFunding),
funderPercTot = sum((!!fundingColHolder))/sum(total),
numAgencies = n_distinct(contactID),
funders = simplify2array(apply(df[8:13], 1,
function(x)paste(names(df[6:11]) [which(!is.na(x))], collapse = " ")))
)
}
reproTable$funders <- simplify2array(apply(reproTable[6:11], 1,
function(x)paste(names(reproTable[8:13]) [which(!is.na(x))], collapse = " ")))
test1 <- collapsePassFunderArray(reproTable, funder1funded, funder1, GRclauseSDregion, "All")
Error: Column `funders` must be length 1 (a summary value), not 107
https://pastebin.com/1Z8vRLir
library(dplyr)
library(stringr)
library(purrr)
collapsePassFunderArray <- function(df, funderTrueCol,
fundingCol, groupClause, name) {
funderTrueHolder <- enquo(funderTrueCol)
fundingColHolder <- enquo(fundingCol)
df %>%
filter((!!funderTrueHolder) == TRUE) %>%
mutate(funder = pmap_chr(select(., matches("^(funder\\d+$)|(^others$)")),
~ {x1 <- c(...)
str_c(names(x1)[!is.na(x1)], collapse=" ")
})) %>%
group_by_at(vars(intersect(groupClause, names(.)), 'funder')) %>%
summarise(funderName = name,
totFund = sum(total),
minFunder = min(numFunders),
maxFunder = max(numFunders),
avgFunder = mean(numFunders, na.rm = TRUE),
medianFunder = median(numFunders, na.rm = TRUE),
provPerc = sum(provincialFunding)/sum(total),
nonProvPerc = sum(nonProvincialFunding)/sum(total),
funderPercProv = sum((!!fundingColHolder))/sum(provincialFunding),
funderPercTot = sum((!!fundingColHolder))/sum(total),
numAgencies = n_distinct(contactID))
}
test1 <- collapsePassFunderArray(reproTable, funder1funded, funder1, GRclauseSDregion, "All")
test1$funder
#[1] "funder1 funder3 funder5 others" "funder1 funder3 funder4 funder5" "funder1 funder3 funder4 funder5"
#[4] "funder1 funder3 funder5"
test2 <- collapsePassFunderArray(reproTable, funder2funded, funder2, GRclauseSDregion, "All")
test2$funder
#[1] "funder2 funder4" "funder2 funder4 others" "funder2 funder4 others"
testothers <- collapsePassFunderArray(reproTable, otherFunded, others, GRclauseSDregion, "All")
testothers$funder
#[1] "funder1 funder3 funder5 others" "funder2 funder4 others" "funder2 funder4 others"