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根據公共列比較兩個數據幀

[英]Compare two data frames based on common columns

我有兩個csv文件:

文件1:

SN  CY  Year    Month   Day Hour    Lat Lon
196101  1   1961    1   14  12  8.3 134.7
196101  1   1961    1   14  18  8.8 133.4
196101  1   1961    1   15  0   9.1 132.5
196101  1   1961    1   15  6   9.3 132.2
196101  1   1961    1   15  12  9.5 132
196101  1   1961    1   15  18  9.9 131.8

文件2:

Year    Month Day RR Hour Lat  Lon
1961    1   14  0   0   14.0917 121.055
1961    1   14  0   6   14.0917 121.055
1961    1   14  0   12  14.0917 121.055
1961    1   14  0   18  14.0917 121.055
1961    1   15  0   0   14.0917 121.055
1961    1   15  0   6   14.0917 121.055

如果文件2中的行具有相同的年,月,日和小時,則我想在文件2中添加另一列,並在文件2中的行存在時輸入“真”,否則為“假”。 然后另存為csv文件。

所需的輸出:

Year    Month Day RR Hour Lat  Lon      com
1961    1   14  0   0   14.0917 121.055 FALSE
1961    1   14  0   6   14.0917 121.055 FALSE
1961    1   14  0   12  14.0917 121.055 TRUE
1961    1   14  0   18  14.0917 121.055 TRUE
1961    1   15  0   0   14.0917 121.055 TRUE
1961    1   15  0   6   14.0917 121.055 TRUE

這是我的腳本:

jtwc <- read.csv("file1.csv",header=T,sep=",")
stn <- read.csv("file2.csv",header=T,sep=",")

if ((jtwc$Year == "stn$YY") & (jtwc$Month == "stn$MM") & (jtwc$Day == "stn$DD") &(jtwc$Hour == "stn$HH")){
stn$com <- "TRUE"
} else {
stn$com <- "FALSE"
}
write.csv(stn,file="test.csv",row.names=T)

這給出了一個錯誤:

In if ((jtwc$Year == "stn$YY") & (jtwc$Month == "stn$MM") & (jtwc$Day ==  :the condition has length > 1 and only the first element will be used

您還可以使用dplyr / tidyverse:

library(tidyverse)
d2 %>% 
  left_join(select(d1, Year, Month, Day, Hour, Com=Lon)) %>% 
  mutate(Com=ifelse(is.na(Com), FALSE, TRUE))

Joining, by = c("Year", "Month", "Day", "Hour")
  Year Month Day RR Hour     Lat     Lon   Com
1 1961     1  14  0    0 14.0917 121.055 FALSE
2 1961     1  14  0    6 14.0917 121.055 FALSE
3 1961     1  14  0   12 14.0917 121.055  TRUE
4 1961     1  14  0   18 14.0917 121.055  TRUE
5 1961     1  15  0    0 14.0917 121.055  TRUE
6 1961     1  15  0    6 14.0917 121.055  TRUE  

使用data.table快速而骯臟的解決方案:

  1. 使用fread讀取文件。
  2. file1提取想要的列(因為您僅對file2感興趣)
  3. 使用merge合並文件
  4. 如果file1中沒有匹配項,則添加FALSE

碼:

library(data.table)
result <- merge(fread("file2.csv"),
                fread("file1.csv")[, .(Year, Month, Day, Hour, com = TRUE)], 
                all.x = TRUE)[is.na(com), com := FALSE]

result
   Year Month Day Hour RR     Lat     Lon   com
1: 1961     1  14    0  0 14.0917 121.055 FALSE
2: 1961     1  14    6  0 14.0917 121.055 FALSE
3: 1961     1  14   12  0 14.0917 121.055  TRUE
4: 1961     1  14   18  0 14.0917 121.055  TRUE
5: 1961     1  15    0  0 14.0917 121.055  TRUE
6: 1961     1  15    6  0 14.0917 121.055  TRUE

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