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⇤ ← Revision 1 as of 2026-05-05 15:46:42
Size: 2733
Comment: Initial commit
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Size: 2769
Comment: Styling
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| Deletions are marked like this. | Additions are marked like this. |
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| df1 <- data.frame(foo = c(1,2,4), bar = c("a","b","c")) |
> df1 <- data.frame(foo = c(1,2,4), bar = c("a","b","c")) |
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| df2 <- as.data.frame(matrix(1:9, nrow=3)) | > df2 <- as.data.frame(matrix(1:9, nrow=3)) |
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| df1 <- rbind(df1, c(8, "d")) | > df1 <- rbind(df1, c(8, "d")) |
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| df2 <- cbind(df2, V4 = c(10, 10, 10)) | > df2 <- cbind(df2, V4 = c(10, 10, 10)) |
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| df2$V4 <- c(10, 10, 10) | > df2$V4 <- c(10, 10, 10) |
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| ### 1. Single bracket, single index ### df2[3] |
> # 1. Single bracket, single index > df2[3] |
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| ### 2. Double brackets, numeric index ### df2[[3]] |
> # 2. Double brackets, numeric index > df2[[3]] |
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| ### 3. Double brackets, variable name ### df2[["V3"]] |
> # 3. Double brackets, variable name > df2[["V3"]] |
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| ### 4. Single bracket, two indices ### df2[, 3] |
> # 4. Single bracket, two indices > df2[, 3] |
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| ### 5. Single bracket, two indices, disallow dropping dimensions ### df2[, 3, drop = FALSE] |
> # 5. Single bracket, two indices, disallow dropping dimensions > df2[, 3, drop = FALSE] |
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| ### 6. Dollar sign syntax ### df2$V3 |
> # 6. Dollar sign syntax > df2$V3 |
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| df2[1, 1] | > df2[1, 1] |
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| df2[1, ] | > df2[1, ] |
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| df2[, 1] | > df2[, 1] |
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| df2[1:2, ] | > df2[1:2, ] |
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| df2[c(1,3), ] | > df2[c(1,3), ] |
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| df1 <- subset(df, foo <= 10 | bar == 1) | > df1 <- subset(df, foo <= 10 | bar == 1) |
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| df2 <- subset(df, select = foo) df2 <- subset(df, select = -foo) df2 <- subset(df, select = foo:bar) df2 <- subset(df, select = c(foo, bar)) |
> df2 <- subset(df, select = foo) > df2 <- subset(df, select = -foo) > df2 <- subset(df, select = foo:bar) > df2 <- subset(df, select = c(foo, bar)) |
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| df3 <- df[df$foo <= 10 | df$bar == 1, ] | > df3 <- df[df$foo <= 10 | df$bar == 1, ] |
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| df4 <- df[, -2] df4 <- df[, -c(2)] |
> df4 <- df[, -2] > df4 <- df[, -c(2)] |
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| df$baz <- NULL | > df$baz <- NULL |
Data Frames
Data frames (data.frame) are matrices with non-homogeneous columns.
Contents
Usage
A data frame is instantiated like:
> df1 <- data.frame(foo = c(1,2,4),
bar = c("a","b","c"))
> df2 <- as.data.frame(matrix(1:9, nrow=3))Note that df2 here has column names like V1 and so on.
To append a row, try:
> df1 <- rbind(df1, c(8, "d"))
To append a column, the following are essentially equivalent:
> df2 <- cbind(df2, V4 = c(10, 10, 10)) > df2$V4 <- c(10, 10, 10)
To access the dimensions of a data frame, try the dim, ncol, and nrow functions.
Indexing
There are several methods for indexing a data frame. All of the following select a single column, but some of the methods return a vector while others return a new data frame containing just a single column.
> # 1. Single bracket, single index > df2[3] ## V3 ## 1 7 ## 2 8 ## 3 9 > # 2. Double brackets, numeric index > df2[[3]] ## [1] 7 8 9 > # 3. Double brackets, variable name > df2[["V3"]] ## [1] 7 8 9 > # 4. Single bracket, two indices > df2[, 3] ## [1] 7 8 9 > # 5. Single bracket, two indices, disallow dropping dimensions > df2[, 3, drop = FALSE] ## V3 ## 1 7 ## 2 8 ## 3 9 > # 6. Dollar sign syntax > df2$V3 ## [1] 7 8 9
More generally, indexing is done with single brackets and two indices (row and column). An index can be either an integer or a vector of integers. Leaving an index blank is equivalent to selecting all.
> df2[1, 1] ## [1] 1 > df2[1, ] ## [1] 1 4 7 > df2[, 1] ## [1] 1 2 3 > df2[1:2, ] ## [1] 1 4 > df2[c(1,3), ] ## [1] 1 7
Subsetting
The best method for removing rows and columns is the subset function. To filter rows based on a condition, try:
> df1 <- subset(df, foo <= 10 | bar == 1)
Use the select option to filter columns.
> df2 <- subset(df, select = foo) > df2 <- subset(df, select = -foo) > df2 <- subset(df, select = foo:bar) > df2 <- subset(df, select = c(foo, bar))
This also demonstrates that subset can be used without a condition, meaning that no rows are filtered.
Logical vector indexing is an alternative. For example, to select rows based on a condition, try:
> df3 <- df[df$foo <= 10 | df$bar == 1, ]
A further extension of this is negative indexing. For example, to remove the second variable, try:
> df4 <- df[, -2] > df4 <- df[, -c(2)]
A final alternative method for removing a single column is to assign NUL.
> df$baz <- NULL