[英]R: Create a new column in a dataframe, using column name, condition and value from another dataframe
將基本數據幀視為:
data <- data.frame(amount_bin = c("10K-25K", "25K-35K", "35K-45K", "45K-50K", "50K+", "10K-25K", "25K-35K", "35K-45K", "45K-50K", "50K+", "10K-25K", "25K-35K", "35K-45K", "45K-50K", "50K+"),
risk_score = c("0-700", "700-750", "750-800", "800-850", "850-900", "0-700", "700-750", "750-800", "800-850", "850-900", "0-700", "700-750", "750-800", "800-850", "850-900"))
並在另一個數據幀中將信息分組為:
group_info <- data.frame(variable = c("amount_bin_group", "amount_bin_group", "amount_bin_group", "amount_bin_group", "amount_bin_group",
"risk_score_group", "risk_score_group", "risk_score_group", "risk_score_group", "risk_score_group"),
bin = c("10K-25K", "25K-35K", "35K-45K", "45K-50K", "50K+",
"0-700", "700-750", "750-800", "800-850", "850-900"),
group = c("1", "1", "2", "2", "3",
"a", "a", "a", "b", "b"))
我想在稱為“ amount_bin_group”和“ risk_score_group”的基本數據幀(數據)中創建2列,當來自group_info和數據的bin列相同時,它們將從列group_info $ group中獲取值。 為簡單起見,我們假設基本列始終是group_info $ variable名稱減去“ group”字符串。 這意味着,當我們要創建列amount_bin_group時,基本列在基本數據幀中將始終為amount_bin。
預期結果數據幀為:
final_data <- data.frame(amount_bin = c("10K-25K", "25K-35K", "35K-45K", "45K-50K", "50K+", "10K-25K", "25K-35K", "35K-45K", "45K-50K", "50K+", "10K-25K", "25K-35K", "35K-45K", "45K-50K", "50K+"),
risk_score = c("0-700", "700-750", "750-800", "800-850", "850-900", "0-700", "700-750", "750-800", "800-850", "850-900", "0-700", "700-750", "750-800", "800-850", "850-900"),
amount_bin_group = c("1", "1", "2", "2", "3", "1", "1", "2", "2", "3", "1", "1", "2", "2", "3"),
risk_score_group = c("a", "a", "a", "b", "b", "a", "a", "a", "b", "b", "a", "a", "a", "b", "b"))
我剛剛想到的解決方案是迭代合並數據幀,即:
final_data <- merge(data, group_info[, c("bin", "group")], by.x = "amount_bin", by.y = "bin")
final_data$amount_bin_group <- final_data$group
final_data$group <- NULL
但是,我相信可以有一個更有效的解決方案。 請注意,有多個此類列,而不僅僅是兩個。 因此,也許循環會有所幫助。
您的group_info太整潔了。 我真不敢說我在說。 通過將其分為兩個數據框,或將每個半框分成自己的列,您可以自己進行簡單的左連接以獲取答案。
final_data_calc <- data %>%
left_join(
group_info %>%
filter(variable == 'amount_bin_group') %>%
rename(amount_bin_group = group,amount_bin = bin) %>%
select(-variable)
) %>%
left_join(
group_info %>%
filter(variable == 'risk_score_group') %>%
rename(risk_score_group = group,risk_score = bin) %>%
select(-variable)
)
# amount_bin risk_score amount_bin_group risk_score_group
#1 10K-25K 0-700 1 a
#2 25K-35K 700-750 1 a
#3 35K-45K 750-800 2 a
#4 45K-50K 800-850 2 b
#5 50K+ 850-900 3 b
#6 10K-25K 0-700 1 a
#7 25K-35K 700-750 1 a
#8 35K-45K 750-800 2 a
#9 45K-50K 800-850 2 b
#10 50K+ 850-900 3 b
#11 10K-25K 0-700 1 a
#12 25K-35K 700-750 1 a
#13 35K-45K 750-800 2 a
#14 45K-50K 800-850 2 b
#15 50K+ 850-900 3 b
您可以只使用for
循環來繼續合並不同的集合:
for (i in unique(group_info$variable)) {
data <- merge(
data, group_info[group_info$variable==i,c("bin","group")],
by.x=sub("_group","",i), by.y="bin"
)
names(data)[names(data)=="group"] <- i
}
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