Question

我有很多测量因素，例如：

measurement1Height;
[1] 176 177 180 181 177
Levels: 176 177 180 181

measurement2Height;
[1] 176 177 180 181 177
Levels: 176 177 180 181

measurement3Height;
[1] 176 177 180 181 176
Levels: 176 180 181

measurement1Weight;
[1] 73 79 85 85 80
Levels: 73 79 80 85

measurement2Weight;
[1] 75 80 84 85 80
Levels: 75 80 84 85

measurement3Weight;
[1] 74 79 85 84 76
Levels: 74 76 79 84 85

measurement1Height <- factor(c(176, 177, 180, 181, 177));
measurement2Height <- factor(c(176, 177, 180, 181, 177));
measurement3Height <- factor(c(176, 177, 180, 181, 176));
measurement1Weight <- factor(c(73, 79, 85, 85, 80));
measurement2Weight <- factor(c(75, 80, 84, 85, 80));
measurement3Weight <- factor(c(74, 79, 85, 84, 76));

我需要获取输出表，其中所有数据均按度量分组：

        Measurement1    Measurement2    Measurement3    
        Height  Weight  Height  Weight  Height  Weight
Person1 176     73      176     75      176     74
Person2 177     79      177     80      177     79
Person3 180     85      180     84      180     85
Person4 181     85      181     85      181     84
Person5 177     80      177     80      176     76

有没有办法快速做到？

Answer 1

这是使用dplyr的快速而肮脏的解决方案。

library(dplyr)

# your data
measurement1Height <- factor(c(176, 177, 180, 181, 177))
measurement2Height <- factor(c(176, 177, 180, 181, 177))
measurement3Height <- factor(c(176, 177, 180, 181, 176))
measurement1Weight <- factor(c(73, 79, 85, 85, 80))
measurement2Weight <- factor(c(75, 80, 84, 85, 80))
measurement3Weight <- factor(c(74, 79, 85, 84, 76))

# operations
data_names <- as.list(sort(paste0(paste0("measurement", 1:3), rep(c("Height", "Weight"), each=3))))
data <- lapply(data_names, get)
names(data) <- data_names
data <- data %>%
  bind_rows() %>%
  mutate(Person = paste("Person", 1:nrow(bind_rows(data)))) %>%
  select(Person, everything())

# here's your new data
data

毕竟，我建议使用整数和数值而不是因数（取决于您的目标）。

如何获得带有分组数据的表？

1 个答案: