比较列中的值

发布于 2025-01-24 02:10:30 字数 726 浏览 0 评论 0原文

请查看以下数据框架作为可再现的示例：

df <- data.frame(Last_year = c('2013', '2020', '2017', '2015', '2016', '2021'), 
year = c('2021', '2020', '2019', '2018', '2017', '2016'))

我想比较列中的值，并在值不同的情况下丢弃行，并丢弃行。 last_year＆lt;年。

这是我想到的代码：

for(i in 1:nrow(df)){
    if((df1$Last_year[i] != df1$year[i] && df1$Last_year[i] < df1$year[i]) | 
         is.na(df1$year[i]))
         {df <- df[-i,]}
    else 
         next}

我不明白为什么，此代码不会消除所有last_year＆lt;一年..你能发现原因吗？

我希望获得的最终数据框架是：

df <- data.frame(Last_year = c('2020', '2021'), 
year = c('2020', '2016'))

与第二个和最后一个值相对应，这是满足我的愿望的一个值 - ＆gt; last_year＆gt;年

原文

please look at the following dataframe as a reproducible example:

df <- data.frame(Last_year = c('2013', '2020', '2017', '2015', '2016', '2021'), 
year = c('2021', '2020', '2019', '2018', '2017', '2016'))

I want to compare the values in the columns and discard the row if the value is different & Last_year<year.

This is the code I come up with:

for(i in 1:nrow(df)){
    if((df1$Last_year[i] != df1$year[i] && df1$Last_year[i] < df1$year[i]) | 
         is.na(df1$year[i]))
         {df <- df[-i,]}
    else 
         next}

I cannot understand why, this code does not eliminate all the last_year < year.. can you spot the reason?

The final dataframe I wish to obtain is:

df <- data.frame(Last_year = c('2020', '2021'), 
year = c('2020', '2016'))

which correspond to the second and the last values, which are the one that satisfy my wish --> Last_year > year

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葬心 2025-01-31 02:10:30

与 @Maël的贡献类似，似乎您想保持last_year超过一年的行：

df[df$Last_year > df$year, ]

如果您想避免NAS，则可以使用wher（）：

df[which(df$Last_year < df$year), ]

Similar to @Maël's contribution, it seems you want to keep rows which last_year is greater than year:

df[df$Last_year > df$year, ]

If you want to avoid NAs, you can use which():

df[which(df$Last_year < df$year), ]

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幼儿园老大 2025-01-31 02:10:30

您根本不需要循环。您只需用简单的filter语句从dplyr替换for循环，也可以使用其他循环使用基本R。

library(dplyr)
    
df %>%
  filter(Last_year >= year  & !is.na(year))

或使用子集从基本R：

subset(df, Last_year >= year  & !is.na(year))

输出

  Last_year year
1      2020 2020
2      2021 2016

数据

df <- structure(list(Last_year = c("2013", "2020", "2017", "2015", 
"2016", "2021", "2022"), year = c("2021", "2020", "2019", "2018", 
"2017", "2016", "NA")), class = "data.frame", row.names = c(NA, 
-7L))

You don't need a for loop at all. You can just replace the for loop with a simple filter statement from dplyr or use base R as provided by the others.

library(dplyr)
    
df %>%
  filter(Last_year >= year  & !is.na(year))

Or use subset from base R:

subset(df, Last_year >= year  & !is.na(year))

Output

  Last_year year
1      2020 2020
2      2021 2016

Data

df <- structure(list(Last_year = c("2013", "2020", "2017", "2015", 
"2016", "2021", "2022"), year = c("2021", "2020", "2019", "2018", 
"2017", "2016", "NA")), class = "data.frame", row.names = c(NA, 
-7L))

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