使用条件处理列表中的数据帧以子集行，使用 R 处理另一个数据帧
dealing with dataframes in a list to subset rows using a condition and another dataframe using R
我有一个包含多个数据帧的列表，即 'mylist' 和一个数据帧，即 'mydf'。有了这两个，我需要解决两个问题来解决使用 R
实际列表包含许多数据框，实际数据框包含 10000 行。这里只显示示例数据
第一个问题：
我有一个包含多个数据框的列表。下面的列表是一个例子
mylist1 <- list(a = data.frame(ID = c("a_1", "b_1", "c_1", "d_1", "e_1", "f_1"), colb = c(3.67, 4.94, 8.11, 2.85, 9.53, 7.5), colc = c(3.45, 6.19, 4.96, 6.73, 9.26, 8.62)),
b = data.frame(cola = c("a_1", "b_1", "c_1", "d_1", "e_1", "f_1"), colb = c(5.24, 3.62, 0.29, 6.65, 7.86, 8.7), colc = c(7.03, 7.51, 0.842, 3.56, 8.68, 5.844)))
我想根据列 'colc' 中的值使用此处所说的条件对列表的每个数据框中的行进行子集化，如果列 'colc' 中的值 >= 6，我想对列表的每个数据框中的行进行子集
mylist1 的预期输出 1 如下...
mylistoutput <- list(a = data.frame(ID = c("b_1", "d_1", "e_1", "f_1"), colb = c(4.94, 2.85, 9.53, 7.5), colc = c(6.19, 6.73, 9.26, 8.62)),
b = data.frame(cola = c("a_1", "b_1", "e_1"), colb = c(5.24, 3.62, 7.86), colc = c(7.03, 7.51, 8.68)))
我尝试使用 filter/subset 的条件对行进行子集化，如下所示
mylistoutput <- lapply(mylist, function(x) filter(x$colc >= 6))
但是失败了......
第二个问题：
来自'mylistoutput'，我想做两件事
首先，对于 'mylistoutput' 的第一个数据帧，我想将 'mylistoutput' 中“ID”列中的 ID 与 'mydf'[ 数据帧中的 ID 进行匹配=16=]
dataframe 'mydf'样本如下
mydf <- data.frame(ID = c("a_1","a_1","a_1","a_1","a_1", "b_1","b_1","b_1","b_1", "c_1","c_1","c_1", "d_1","d_1","d_1", "e_1","e_1","e_1","e_1","e_1", "f_1","f_1","f_1","g_1","g_1","g_1","g_1","g_1"), colb = c(3.67,1,2.3,2.5,5, 1.1,2.2,3.7,4.94, 8.11,1.23,2, 2.85,1,2, 5,4,9.53,4,5, 8,7,7.5, 1,2,3,4,5), colc = c(3.45,1,2,3,4, 6.19,1,2,3, 4.96,1,2, 6.73,1,2, 9.26,1,2,3,4, 8.62,1,2, 1,2,3,4,5))
现在，我想提取 'mylistoutput' 和 'mydf'
中第一个数据帧之间的所有匹配 ID
'mydf' 的预期输出如下
mydfoutput1 <- data.frame(ID = c("b_1","b_1","b_1","b_1", "d_1","d_1","d_1", "e_1","e_1","e_1","e_1","e_1", "f_1","f_1","f_1"), colb = c(1.1,2.2,3.7,4.94, 2.85,1,2, 5,4,9.53,4,5, 8,7,7.5), colc = c(6.19,1,2,3, 6.73,1,2, 9.26,1,2,3,4, 8.62,1,2))
其次，我想 select 列表 'mylistoutput' 中各种数据帧之间的匹配 ID。例如，“b_1”和“e_1”是列表 'mylistoutput' 的两个数据帧中的公共 ID。然后，我想从数据帧 'mydf'
中提取相同的 ID，即“b_1”和“e_1”
预期输出如下
mydfoutput2 <- data.frame(ID = c("b_1","b_1","b_1","b_1", "e_1","e_1","e_1","e_1","e_1"), colb = c(1.1,2.2,3.7,4.94, 5,4,9.53,4,5), colc = c(6.19,1,2,3, 9.26,1,2,3,4, ))
寻找解决上述问题的代码
我们可以使用 lapply 和 subset
out <- lapply(mylist1, subset, subset = colc >=6)
对于第二种情况，我们可以做
subset(mydf, ID %in% out[[1]]$ID)
对于第三种情况，使用Reduce与intersect
subset(mydf, ID %in% Reduce(intersect, lapply(out, `[[`, 1)))
filter 来自 dplyr，它需要 data.frame 作为输入而不是向量
lapply(mylist, function(x) filter(x, colc >= 6))
我有一个包含多个数据帧的列表，即 'mylist' 和一个数据帧，即 'mydf'。有了这两个，我需要解决两个问题来解决使用 R
实际列表包含许多数据框，实际数据框包含 10000 行。这里只显示示例数据
第一个问题： 我有一个包含多个数据框的列表。下面的列表是一个例子
mylist1 <- list(a = data.frame(ID = c("a_1", "b_1", "c_1", "d_1", "e_1", "f_1"), colb = c(3.67, 4.94, 8.11, 2.85, 9.53, 7.5), colc = c(3.45, 6.19, 4.96, 6.73, 9.26, 8.62)),
b = data.frame(cola = c("a_1", "b_1", "c_1", "d_1", "e_1", "f_1"), colb = c(5.24, 3.62, 0.29, 6.65, 7.86, 8.7), colc = c(7.03, 7.51, 0.842, 3.56, 8.68, 5.844)))
我想根据列 'colc' 中的值使用此处所说的条件对列表的每个数据框中的行进行子集化，如果列 'colc' 中的值 >= 6，我想对列表的每个数据框中的行进行子集
mylist1 的预期输出 1 如下...
mylistoutput <- list(a = data.frame(ID = c("b_1", "d_1", "e_1", "f_1"), colb = c(4.94, 2.85, 9.53, 7.5), colc = c(6.19, 6.73, 9.26, 8.62)),
b = data.frame(cola = c("a_1", "b_1", "e_1"), colb = c(5.24, 3.62, 7.86), colc = c(7.03, 7.51, 8.68)))
我尝试使用 filter/subset 的条件对行进行子集化，如下所示
mylistoutput <- lapply(mylist, function(x) filter(x$colc >= 6))
但是失败了......
第二个问题： 来自'mylistoutput'，我想做两件事
首先，对于 'mylistoutput' 的第一个数据帧，我想将 'mylistoutput' 中“ID”列中的 ID 与 'mydf'[ 数据帧中的 ID 进行匹配=16=]
dataframe 'mydf'样本如下
mydf <- data.frame(ID = c("a_1","a_1","a_1","a_1","a_1", "b_1","b_1","b_1","b_1", "c_1","c_1","c_1", "d_1","d_1","d_1", "e_1","e_1","e_1","e_1","e_1", "f_1","f_1","f_1","g_1","g_1","g_1","g_1","g_1"), colb = c(3.67,1,2.3,2.5,5, 1.1,2.2,3.7,4.94, 8.11,1.23,2, 2.85,1,2, 5,4,9.53,4,5, 8,7,7.5, 1,2,3,4,5), colc = c(3.45,1,2,3,4, 6.19,1,2,3, 4.96,1,2, 6.73,1,2, 9.26,1,2,3,4, 8.62,1,2, 1,2,3,4,5))
现在，我想提取 'mylistoutput' 和 'mydf'
中第一个数据帧之间的所有匹配 ID'mydf' 的预期输出如下
mydfoutput1 <- data.frame(ID = c("b_1","b_1","b_1","b_1", "d_1","d_1","d_1", "e_1","e_1","e_1","e_1","e_1", "f_1","f_1","f_1"), colb = c(1.1,2.2,3.7,4.94, 2.85,1,2, 5,4,9.53,4,5, 8,7,7.5), colc = c(6.19,1,2,3, 6.73,1,2, 9.26,1,2,3,4, 8.62,1,2))
其次，我想 select 列表 'mylistoutput' 中各种数据帧之间的匹配 ID。例如，“b_1”和“e_1”是列表 'mylistoutput' 的两个数据帧中的公共 ID。然后，我想从数据帧 'mydf'
中提取相同的 ID，即“b_1”和“e_1”预期输出如下
mydfoutput2 <- data.frame(ID = c("b_1","b_1","b_1","b_1", "e_1","e_1","e_1","e_1","e_1"), colb = c(1.1,2.2,3.7,4.94, 5,4,9.53,4,5), colc = c(6.19,1,2,3, 9.26,1,2,3,4, ))
寻找解决上述问题的代码
我们可以使用 lapply 和 subset
out <- lapply(mylist1, subset, subset = colc >=6)
对于第二种情况，我们可以做
subset(mydf, ID %in% out[[1]]$ID)
对于第三种情况，使用Reduce与intersect
subset(mydf, ID %in% Reduce(intersect, lapply(out, `[[`, 1)))
filter 来自 dplyr，它需要 data.frame 作为输入而不是向量
lapply(mylist, function(x) filter(x, colc >= 6))