使用聚合命名新列的问题

Question

For some reason, aggregate is giving me the wrong column names, even though the data are still coming out correct. Can anyone tell me why (am I doing something wrong)?

For example, with a dataframe df :

df <- structure(list(Site = c(1L, 1L, 1L, 2L, 2L, 2L), Sample = c(1L, 
2L, 3L, 1L, 2L, 3L), Diameter = 1:6), .Names = c("Site", "Sample", 
"Diameter"), class = "data.frame", row.names = c(NA, -6L))

which looks like

    Site Sample Diameter
1    1      1        1
2    1      2        2
3    1      3        3
4    2      1        4
5    2      2        5
6    2      3        6

I run the following code

# Add column to calculate area from diameter
df['Area'] = ((df['Diameter']/2)^2)*pi

# Subset sites
Site1 <- subset(df, Site == "1")

# Calculate total area for each site
Site1_area <- aggregate(Site1$Area, by=list(Sample=Site1$Sample), sum, na.rm=TRUE)

Site1_area

This gives the new dataframe Site1_area as

    Sample  Diameter
1      1 0.7853982
2      2 3.1415927
3      3 7.0685835

where the calculated areas have been preserved, but the column name is now incorrectly given as Diameter instead of Area . I know I can rename this using

colnames(Site1_area) <- c("Sample", "Area")

but it seems odd to me that the column isn't being named correctly to begin with. Can anyone tell me why? Am I doing something incorrectly?

Many thanks!

Answer 1

You made an error that wasn't caught when you did this:

df['Area'] = ((df['Diameter']/2)^2)*pi

Should have been:

df[['Area']] = ((df[['Diameter']]/2)^2)*pi

After you did this you had:

> df
  Site Sample Diameter   Diameter
1    1      1        1  0.7853982
2    1      2        2  3.1415927
3    1      3        3  7.0685835
4    2      1        4 12.5663706
5    2      2        5 19.6349541
6    2      3        6 28.2743339

So you never really had a column named "Area". If you want the labeling to be simple then try the aggregate.formula method:

Site1_area2 <- aggregate(Area~Sample, data=Site1, sum, na.rm=TRUE)
> Site1_area2
  Sample      Area
1      1 0.7853982
2      2 3.1415927
3      3 7.0685835