Read a Markdown Table into a Tibble
Arguments
- file
Either a path to a file, a connection, or literal data (either a single string or a raw vector). Files starting with
http://,https://,ftp://, orftps://will be automatically downloaded.- warn
Boolean. Should warnings be raised about possible issues with the passed
file? Defaults toTRUE.- ...
Arguments passed on to
readr::read_delim.
Details
read_md_table reads a markdown table into a tibble from a string,
file, or URL. It uses readr::read_delim to efficiently read in data.
read_md_table expects file to be a markdown table. If file is a
markdown file that contains more than just a table or tables, the table(s)
should be extracted with extract_md_tables before reading
them in.
If warn is TRUE, read_md_table will warn if there are potential
issues with the provided markdown table. Depending on the issue,
read_md_table may still correctly read the table. For instance, if the
row separating the header from the other rows is malformed or any rows
have missing leading or trailing pipes, warnings will be raised but the
data will be read correctly. readr::read_delim will provide its own
warnings if there are potential issues.
Examples
# Read from a file
read_md_table(read_md_table_example("mtcars.md"))
#> Rows: 32 Columns: 12
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: "|"
#> chr (1): model
#> dbl (11): mpg, cyl, disp, hp, drat, wt, qsec, vs, am, gear, carb
#>
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
#> # A tibble: 32 × 12
#> model mpg cyl disp hp drat wt qsec vs am gear carb
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 Mazda RX4 21 6 160 110 3.9 2.62 16.5 0 1 4 4
#> 2 Mazda RX4 … 21 6 160 110 3.9 2.88 17.0 0 1 4 4
#> 3 Datsun 710 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
#> 4 Hornet 4 D… 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1
#> 5 Hornet Spo… 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2
#> 6 Valiant 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1
#> 7 Duster 360 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4
#> 8 Merc 240D 24.4 4 147. 62 3.69 3.19 20 1 0 4 2
#> 9 Merc 230 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2
#> 10 Merc 280 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4
#> # ℹ 22 more rows
# Read from a string
read_md_table("| H1 | H2 | \n|-----|-----|\n| R1C1 | R1C2 |\n| R2C1 | R2C2 |")
#> Rows: 2 Columns: 2
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: "|"
#> chr (2): H1, H2
#>
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
#> # A tibble: 2 × 2
#> H1 H2
#> <chr> <chr>
#> 1 R1C1 R1C2
#> 2 R2C1 R2C2
# \donttest{
# Read from a URL
read_md_table(
"https://raw.githubusercontent.com/jrdnbradford/readMDTable/main/inst/extdata/iris.md"
)
#> Rows: 150 Columns: 5
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: "|"
#> chr (1): variety
#> dbl (4): sepal.length, sepal.width, petal.length, petal.width
#>
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
#> # A tibble: 150 × 5
#> sepal.length sepal.width petal.length petal.width variety
#> <dbl> <dbl> <dbl> <dbl> <chr>
#> 1 5.1 3.5 1.4 0.2 Setosa
#> 2 4.9 3 1.4 0.2 Setosa
#> 3 4.7 3.2 1.3 0.2 Setosa
#> 4 4.6 3.1 1.5 0.2 Setosa
#> 5 5 3.6 1.4 0.2 Setosa
#> 6 5.4 3.9 1.7 0.4 Setosa
#> 7 4.6 3.4 1.4 0.3 Setosa
#> 8 5 3.4 1.5 0.2 Setosa
#> 9 4.4 2.9 1.4 0.2 Setosa
#> 10 4.9 3.1 1.5 0.1 Setosa
#> # ℹ 140 more rows
# }
# Get warnings for malformed tables
read_md_table(
"| Name | Age | City | Date |
|-------|-----|-------------|------------|
| Alice | 30 | New York | 2021/01/08 |
| Bob | 25 | Los Angeles | 2023/07/22 |
Carol | 27 | Chicago | 2022/11/01 "
)
#> Warning: ✖ Row 5 of the table does not have the same number of cells as the header row:
#> Carol | 27 | Chicago | 2022/11/01
#> ℹ Expected: 5 pipes, but found: 3 pipes.
#> Rows: 3 Columns: 4
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: "|"
#> chr (2): Name, City
#> dbl (1): Age
#> date (1): Date
#>
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
#> # A tibble: 3 × 4
#> Name Age City Date
#> <chr> <dbl> <chr> <date>
#> 1 Alice 30 New York 2021-01-08
#> 2 Bob 25 Los Angeles 2023-07-22
#> 3 Carol 27 Chicago 2022-11-01