Question

我仍然是R的新手并尝试以特定方式汇总数据。为了说明这里，我正在使用来自nasaweather包的天气数据。例如，我想获得特定日期的平均温度，并显示该数据集中包含的3个来源和12个月。

我想我可以使用以下代码完成它，我指定我感兴趣的那一天，创建一个空数据框以填充，然后在我计算平均温度的月份运行for循环对于每个来源，用月份来约束它们，然后将它们绑定到数据框。最后，我调整列名称并打印出结果：

library(nasaweather)
library(magrittr)
library(dplyr)

query_day = 15
data_output <- data.frame(month = numeric(),
                EWR = numeric(), 
                JFK = numeric(),
                LGA = numeric())

for (i in 1:12) {
  data_subset <- weather %>%
    filter(day == query_day, month == i) %>%
    summarize(
      EWR = mean(temp[origin == "EWR"]),
      JFK = mean(temp[origin == "JFK"]),
      LGA = mean(temp[origin == "LGA"]))
  data_output <- rbind(data_output, cbind(i, data_subset))
  rm(data_subset)
}

names(data_output) <- c("month", "EWR", "JFK", "LGA")
print(data_output)

在我手中，这产生以下结果：

   month     EWR     JFK     LGA
1      1 39.3725 39.0875 38.9150
2      2 42.1625 39.3425 42.9050
3      3 37.4150 36.7775 37.3025
4      4 50.1275 48.1550 49.2050
5      5 58.8725 55.7150 59.1575
6      6 70.7825 70.2950 71.5700
7      7 86.9900 85.1225 87.2000
8      8 69.2075 69.0725 69.9425
9      9 60.6350 61.2125 61.7375
10    10 59.8850 58.3850 60.5150
11    11 45.7475 45.1700 49.0700
12    12 32.4950 38.0975 34.0325

这正是我想要的。我只是觉得我的代码似乎太复杂了，想问一下是否有更简单的方法来完成这项工作？

Answer 1

你的代码存在各种各样的问题......但主要的问题是你没有先成为group_by。一旦你把它包括在内，这就变得容易了。首先查看我对您的代码的评论，然后查看底部的最终代码：

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收益率：

library(nasaweather) ## Wrong package
# library(magrittr) ## not needed, it's called by dplyr
library(dplyr)

query_day = 15
#  data_output <- data.frame(month = numeric(), ## We won't need to specify this explicitly 
## (but you are right that you should specify this in a for loop. Go one step
## further by actually telling the data.frame how many rows to expect. 
## But not in this case cause we won't use for loop)
                        #  EWR = numeric(), 
                        #  JFK = numeric(),
                        #  LGA = numeric())

for (i in 1:12) { ## You don't need to do a for loop... you can do it with the summarize_by function.
  data_subset <- weather %>%
    filter(day == query_day, month == i) %>%
    summarize(       ## Before doing summarize, you need a group_by to say what to summarize_by
      EWR = mean(temp[origin == "EWR"]),
      JFK = mean(temp[origin == "JFK"]),
      LGA = mean(temp[origin == "LGA"]))
  data_output <- rbind(data_output, cbind(i, data_subset)) ## If you're doing the group_by, this step isn't required. 
  # rm(data_subset) ## You don't have to remove temporary datasets...
## When the for loop ends, they are automatically removed.
}

names(data_output) <- c("month", "EWR", "JFK", "LGA") 
print(data_output) 

################### Better code:
library(nycflights13) ## your the package you waant is nycflights13... not nasaweather
library(dplyr)

query_day = 15

weather %>%
  filter(day == query_day) %>%
  group_by(month) %>%
  summarize(
      EWR = mean(temp[origin == "EWR"]),
      JFK = mean(temp[origin == "JFK"]),
      LGA = mean(temp[origin == "LGA"])) -> data_output

data_output

使用查询汇总数据集中的选定条目

1 个答案: