tidy_table() will be deprecated. Use as_cells() instead.
For certain non-rectangular data formats, it can be useful to parse the data into a melted format where each row represents a single token.
Data frames represent data in a tabular structure. tidy_table takes the
row and column position of each 'cell', and returns that information in a new
data frame, alongside the content and type of each cell.
This makes it easier to deal with complex or non-tabular data (e.g. pivot
tables) that have been imported into R as data frames. Once they have been
'melted' by tidy_table(), you can use functions like behead() and
spatter() to reshape them into conventional, tidy, unpivoted structures.
For HTML tables, the content of each cell is returned as a standalone HTML string that can be further parsed with tools such as the rvest package. This is particularly useful when an HTML cell itself contains an HTML table, or contains both text and a URL. If the HTML itself is poorly formatted, try passing it through the htmltidy package first.
This is an S3 generic.
tidy_table(x, row_names = FALSE, col_names = FALSE)
| x | A data.frame or an HTML document |
|---|---|
| row_names | Whether to treat the row names as cells, Default: FALSE |
| col_names | Whether to treat the column names as cells, Default: FALSE |
A data.frame with the following columns:
row and col (integer) giving the original position of the 'cells'
any relevant columns for cell values in their original types: chr,
cpl, dbl, fct, int, lgl, list, and ord
data_type to specify for each cell which of the above columns (chr
etc.) the value is in.
The columns fct and ord are, like list, list-columns (each element is
independent) to avoid factor levels clashing. For HTML tables, the column
html gives the HTML string of the original cell.
Row and column names, when present and required by row_names = TRUE or
col_names = TRUE, are treated as though they were cells in the table, and
they appear in the chr column.
#> a b #> 1 10 foo #> 2 20 bartidy_table(x)#>#> # A tibble: 4 x 5 #> row col data_type chr dbl #> <int> <int> <chr> <chr> <dbl> #> 1 1 1 dbl NA 10 #> 2 2 1 dbl NA 20 #> 3 1 2 chr foo NA #> 4 2 2 chr bar NAtidy_table(x, row_names = TRUE)#>#> # A tibble: 6 x 5 #> row col data_type chr dbl #> <int> <int> <chr> <chr> <dbl> #> 1 1 1 chr 1 NA #> 2 2 1 chr 2 NA #> 3 1 2 dbl NA 10 #> 4 2 2 dbl NA 20 #> 5 1 3 chr foo NA #> 6 2 3 chr bar NAtidy_table(x, col_names = TRUE)#>#> # A tibble: 6 x 5 #> row col data_type chr dbl #> <int> <int> <chr> <chr> <dbl> #> 1 1 1 chr a NA #> 2 2 1 dbl NA 10 #> 3 3 1 dbl NA 20 #> 4 1 2 chr b NA #> 5 2 2 chr foo NA #> 6 3 2 chr bar NA# 'list' columns are undisturbed y <- data.frame(a = c("a", "b"), stringsAsFactors = FALSE) y$b <- list(1:2, 3:4) y#> a b #> 1 a 1, 2 #> 2 b 3, 4tidy_table(y)#>#> # A tibble: 4 x 5 #> row col data_type chr list #> <int> <int> <chr> <chr> <list> #> 1 1 1 chr a <NULL> #> 2 2 1 chr b <NULL> #> 3 1 2 list NA <int [2]> #> 4 2 2 list NA <int [2]># Factors are preserved by being wrapped in lists so that their levels don't # conflict. Blanks are NULLs. z <- data.frame(x = factor(c("a", "b")), y = factor(c("c", "d"), ordered = TRUE)) tidy_table(z)#>#> # A tibble: 4 x 5 #> row col data_type fct ord #> <int> <int> <chr> <list> <list> #> 1 1 1 fct <fct [1]> <NULL> #> 2 2 1 fct <fct [1]> <NULL> #> 3 1 2 ord <NULL> <ord [1]> #> 4 2 2 ord <NULL> <ord [1]>tidy_table(z)$fct#>#> [[1]] #> [1] a #> Levels: a b #> #> [[2]] #> [1] b #> Levels: a b #> #> [[3]] #> NULL #> #> [[4]] #> NULL #>tidy_table(z)$ord#>#> [[1]] #> NULL #> #> [[2]] #> NULL #> #> [[3]] #> [1] c #> Levels: c < d #> #> [[4]] #> [1] d #> Levels: c < d #># HTML tables can be extracted from the output of xml2::read_html(). These # are returned as a list of tables, similar to rvest::html_table(). The # value of each cell is its standalone HTML string, which can contain # anything -- even another table. colspan <- system.file("extdata", "colspan.html", package = "unpivotr") rowspan <- system.file("extdata", "rowspan.html", package = "unpivotr") nested <- system.file("extdata", "nested.html", package = "unpivotr") if (FALSE) { browseURL(colspan) browseURL(rowspan) browseURL(nestedspan) } tidy_table(xml2::read_html(colspan))#>#> [[1]] #> # A tibble: 4 x 4 #> row col data_type html #> <int> <int> <chr> <chr> #> 1 1 1 html "<th colspan=\"2\">Header (1, 1:2)</th>" #> 2 2 1 html "<td>cell (2, 1)</td>" #> 3 1 2 html NA #> 4 2 2 html "<td>cell (2, 2)</td>" #>#>#> [[1]] #> # A tibble: 4 x 4 #> row col data_type html #> <int> <int> <chr> <chr> #> 1 1 1 html "<th rowspan=\"2\">Header (1:2, 1)</th>" #> 2 2 1 html NA #> 3 1 2 html "<th>Header (1, 2)</th>" #> 4 2 2 html "<td>cell (2, 2)</td>" #>#>#> [[1]] #> # A tibble: 4 x 4 #> row col data_type html #> <int> <int> <chr> <chr> #> 1 1 1 html "<th>Header (1, 1)</th>" #> 2 2 1 html "<td>cell (2, 1)</td>" #> 3 1 2 html "<th>Header (1, 2)</th>" #> 4 2 2 html "<td>\n <table>\n<tr>\n<th>Header (2, 2)(1, 1)… #>