I’m pleased to announce that readxl 1.0.0 is available on CRAN. readxl makes it easy to bring tabular data out of Excel and into R, for modern
.xlsx files and the legacy
.xls format. readxl does not have any tricky external dependencies, such as Java or Perl, and is easy to install and use on Mac, Windows, and Linux.
You can install it with:
As well as fixing many bugs, this release:
- Allows you to target specific cells for reading, in a variety of ways
- Adds two new column types:
"list", for data of disparate type
- Is more resilient to the wondrous diversity in spreadsheets, e.g., those written by 3rd party tools
You can see a full list of changes in the release notes. This is the first release maintained by Jenny Bryan.
Specifying the data rectangle
In an ideal world, data would live in a neat rectangle in the upper left corner of a spreadsheet. But spreadsheets often serve multiple purposes for users with different priorities. It is common to encounter several rows of notes above or below the data, for example. The new
range argument provides a flexible interface for describing the data rectangle, including Excel-style ranges and row- or column-only ranges.
library(readxl) read_excel( readxl_example("deaths.xlsx"), <span style="color:#3366ff;">range = "arts!A5:F15"</span> ) #> # A tibble: 10 × 6 #> Name Profession Age `Has kids` `Date of birth` #> #> 1 David Bowie musician 69 TRUE 1947-01-08 #> 2 Carrie Fisher actor 60 TRUE 1956-10-21 #> 3 Chuck Berry musician 90 TRUE 1926-10-18 #> 4 Bill Paxton actor 61 TRUE 1955-05-17 #> # ... with 6 more rows, and 1 more variables: `Date of death` read_excel( readxl_example("deaths.xlsx"), sheet = "other", <span style="color:#3366ff;">range = cell_rows(5:15)</span> ) #> # A tibble: 10 × 6 #> Name Profession Age `Has kids` `Date of birth` #> #> 1 Vera Rubin scientist 88 TRUE 1928-07-23 #> 2 Mohamed Ali athlete 74 TRUE 1942-01-17 #> 3 Morley Safer journalist 84 TRUE 1931-11-08 #> 4 Fidel Castro politician 90 TRUE 1926-08-13 #> # ... with 6 more rows, and 1 more variables: `Date of death`
There is also a new argument
n_max that limits the number of data rows read from the sheet. It is an example of readxl’s evolution towards a readr-like interface. The Sheet Geometry vignette goes over all the options.
The new ability to target cells for reading means that readxl’s automatic column typing will “just work”” for most sheets, most of the time. Above, the
Has kids column is automatically detected as
logical, which is a new column type for readxl.
You can still specify column type explicitly via
col_types, which gets a couple new features. If you provide exactly one type, it is recycled to the necessary length. The new type
"guess" can be mixed with explicit types to specify some types, while leaving others to be guessed.
read_excel( readxl_example("deaths.xlsx"), range = "arts!A5:C15", <span style="color:#3366ff;">col_types = c("guess", "skip", "numeric")</span> ) #> # A tibble: 10 × 2 #> Name Age #> #> 1 David Bowie 69 #> 2 Carrie Fisher 60 #> 3 Chuck Berry 90 #> 4 Bill Paxton 61 #> # ... with 6 more rows
The new argument
guess_max limits the rows used for type guessing. Leading and trailing whitespace is trimmed when the new
trim_ws argument is
TRUE, which is the default. Finally, thanks to Jonathan Marshall, multiple
na values are accepted. The Cell and Column Types vignette has more detail.
Thanks to Greg Freedman Ellis we now have a
"list" column type. This is useful if you want to bring truly disparate data into R without the coercion required by atomic vector types.
(df <- read_excel( readxl_example("clippy.xlsx"), <span style="color:#3366ff;">col_types = c("text", "list")</span> )) #> # A tibble: 4 × 2 #> name value #> <chr> <list> #> 1 Name <chr > #> 2 Species <chr > #> 3 Approx date of death <dttm > #> 4 Weight in grams <dbl > tibble::deframe(df) #> $Name #>  "Clippy" #> #> $Species #>  "paperclip" #> #> $`Approx date of death` #>  "2007-01-01 UTC" #> #> $`Weight in grams` #>  0.9
- General rationalization of sheet geometry, including detection and treatment of empty rows and columns.
- Improved behavior and messaging around coercion and mismatched cell and column types.
- Improved handling of datetimes with respect to 3rd party software, rounding, and the Lotus 1-2-3 leap year bug.
read_xlsx()are now exposed, so that files without an
.xlsxextension can be read. Thanks Jirka Lewandowski!
- readxl Workflows showcases patterns that reduce tedium and increase reproducibility when raw data arrives in a spreadsheet.