Spread a data frame of cells into spreadsheet shape

Reshapes a data frame of cells (presumably the output of range_read_cells()) into another data frame, i.e., puts it back into the shape of the source spreadsheet. This function exists primarily for internal use and for testing. The flagship function range_read(), a.k.a. read_sheet(), is what most users are looking for. It is basically range_read_cells() + spread_sheet().

Usage

spread_sheet(
  df,
  col_names = TRUE,
  col_types = NULL,
  na = "",
  trim_ws = TRUE,
  guess_max = min(1000, max(df$row)),
  .name_repair = "unique"
)

Arguments

df

A data frame with one row per (nonempty) cell, integer variables row and column (probably referring to location within the spreadsheet), and a list-column cell of SHEET_CELL objects.

col_names

TRUE to use the first row as column names, FALSE to get default names, or a character vector to provide column names directly. If user provides col_types, col_names can have one entry per column or one entry per unskipped column.

col_types

Column types. Either NULL to guess all from the spreadsheet or a string of readr-style shortcodes, with one character or code per column. If exactly one col_type is specified, it is recycled. See Column Specification for more.

na

Character vector of strings to interpret as missing values. By default, blank cells are treated as missing data.

trim_ws

Logical. Should leading and trailing whitespace be trimmed from cell contents?

guess_max

Maximum number of data rows to use for guessing column types.

.name_repair

Handling of column names. By default, googlesheets4 ensures column names are not empty and are unique. There is full support for .name_repair as documented in tibble::tibble().

Value

A tibble in the shape of the original spreadsheet, but enforcing user's wishes regarding column names, column types, NA strings, and whitespace trimming.

Examples

df <- gs4_example("mini-gap") %>%
  range_read_cells()
#> ✔ Reading from mini-gap.
#> ✔ Range Africa.
spread_sheet(df)
#> # A tibble: 5 × 6
#>   country      continent  year lifeExp     pop gdpPercap
#>   <chr>        <chr>     <dbl>   <dbl>   <dbl>     <dbl>
#> 1 Algeria      Africa     1952    43.1 9279525     2449.
#> 2 Angola       Africa     1952    30.0 4232095     3521.
#> 3 Benin        Africa     1952    38.2 1738315     1063.
#> 4 Botswana     Africa     1952    47.6  442308      851.
#> 5 Burkina Faso Africa     1952    32.0 4469979      543.

# ^^ gets same result as ...
read_sheet(gs4_example("mini-gap"))
#> ✔ Reading from mini-gap.
#> ✔ Range Africa.
#> # A tibble: 5 × 6
#>   country      continent  year lifeExp     pop gdpPercap
#>   <chr>        <chr>     <dbl>   <dbl>   <dbl>     <dbl>
#> 1 Algeria      Africa     1952    43.1 9279525     2449.
#> 2 Angola       Africa     1952    30.0 4232095     3521.
#> 3 Benin        Africa     1952    38.2 1738315     1063.
#> 4 Botswana     Africa     1952    47.6  442308      851.
#> 5 Burkina Faso Africa     1952    32.0 4469979      543.