Posted By: Anonymous
Given two data frames:
df1 = data.frame(CustomerId = c(1:6), Product = c(rep("Toaster", 3), rep("Radio", 3))) df2 = data.frame(CustomerId = c(2, 4, 6), State = c(rep("Alabama", 2), rep("Ohio", 1))) df1 # CustomerId Product # 1 Toaster # 2 Toaster # 3 Toaster # 4 Radio # 5 Radio # 6 Radio df2 # CustomerId State # 2 Alabama # 4 Alabama # 6 Ohio
How can I do database style, i.e., sql style, joins? That is, how do I get:
- An inner join of
Return only the rows in which the left table have matching keys in the right table.
- An outer join of
Returns all rows from both tables, join records from the left which have matching keys in the right table.
- A left outer join (or simply left join) of
Return all rows from the left table, and any rows with matching keys from the right table.
- A right outer join of
Return all rows from the right table, and any rows with matching keys from the left table.
How can I do a SQL style select statement?
By using the
merge function and its optional parameters:
merge(df1, df2) will work for these examples because R automatically joins the frames by common variable names, but you would most likely want to specify
merge(df1, df2, by = "CustomerId") to make sure that you were matching on only the fields you desired. You can also use the
by.y parameters if the matching variables have different names in the different data frames.
merge(x = df1, y = df2, by = "CustomerId", all = TRUE)
merge(x = df1, y = df2, by = "CustomerId", all.x = TRUE)
merge(x = df1, y = df2, by = "CustomerId", all.y = TRUE)
merge(x = df1, y = df2, by = NULL)
Just as with the inner join, you would probably want to explicitly pass “CustomerId” to R as the matching variable. I think it’s almost always best to explicitly state the identifiers on which you want to merge; it’s safer if the input data.frames change unexpectedly and easier to read later on.
You can merge on multiple columns by giving
by a vector, e.g.,
by = c("CustomerId", "OrderId").
If the column names to merge on are not the same, you can specify, e.g.,
by.x = "CustomerId_in_df1", by.y = "CustomerId_in_df2" where
CustomerId_in_df1 is the name of the column in the first data frame and
CustomerId_in_df2 is the name of the column in the second data frame. (These can also be vectors if you need to merge on multiple columns.)