The `read.xlsx()` and `read.xlsx2()` functions are both used to read Excel files in R. The `read.xlsx()` function is the older function and is not as efficient as the `read.xlsx2()` function. However, the `read.xlsx()` function is more widely supported and is available on older versions of R.
The `read.xlsx()` function has the following arguments:
- `file`: The path to the Excel file to read.
- `sheet`: The name or index of the sheet to read. If `sheet` is not specified, the first sheet will be read.
- `startRow`: The row number to start reading from.
- `endRow`: The row number to stop reading at. If `endRow` is not specified, all rows will be read.
- `colClasses`: A vector of class names to assign to the columns. If `colClasses` is not specified, the class of each column will be guessed.
- `na.strings`: A vector of strings to interpret as NA values.
- `skipEmptyRows`: If `TRUE`, empty rows will be skipped.
- `...`: Other arguments passed to the `read.xlsx()` function.
The `read.xlsx2()` function has the same arguments as the `read.xlsx()` function, with the following additions:
- `header`: A logical value indicating whether the first row of the Excel file contains column names.
- `stringsAsFactors`: A logical value indicating whether character strings should be converted to factors.
The following code shows how to read an Excel file into a data frame using the `read.xlsx()` function:
library(xlsx)
df <- read.xlsx("my_data.xlsx")
print(df)
This code will read the Excel file `my_data.xlsx` into a data frame called `df`. The `print()` function will then print the data frame to the console.
You can also use the `read.xlsx()` function to read a specific sheet from an Excel file. For example, the following code will read the first sheet from the Excel file `my_data.xlsx` into a data frame called `df`:
df <- read.xlsx("my_data.xlsx", sheet = 1)
print(df)
You can also use the `read.xlsx()` function to specify a range of cells to read. For example, the following code will read the cells A1:C10 from the Excel file `my_data.xlsx` into a data frame called `df`:
df <- read.xlsx("my_data.xlsx", range = "A1:C10")
print(df)
- The write.xlsx() function can be used to write an R object to an Excel file. The syntax is similar to the read.xlsx() function.
- The read.xlsx2() function is much faster than the read.xlsx() function, but it may be slightly unstable when reading subsets of rows.
- The XLConnect package has more options for writing and manipulating Excel files. It can be used to create charts, pivot tables, and other objects in Excel.
- The XLConnect vignette is a good place to start for that package. It provides examples of how to use the package to read, write, and manipulate Excel files.
- In general, it is advised to store your data in either a database or in comma separated files (.csv) or tab separated files (.tab/.txt) as they are easier to distribute.
