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Consider using YAML files to guide table construction.
title: The 'mtcars' Demo Datasetdescription: > Aspects of automobile design and performance.properties: > Suppressed values are replaced with the value ['c']. Blank cells in the 'Notes' column indicate the absence of a note.contact: > The mtcars Team, telephone: 012 3456 789tables:
- name: Table 1title: Car Road Tests 1source: Motor Trend (1974)file: table1.csv
- name: Table 2title: Car Road Tests 2source: Motor Trend (1974)file: table2.csvnotes:
- number: 1description: US gallons
- number: 2description: > Retained to enable comparisons with previous analyses.
Processing steps:
The cover page can be generated from the head elements, title, description, properties, contact.
The contents can be generated from the information in the tables list (using the name and title components) and the existence (or otherwise) of the notes list.
The notes list can be coerced into a table.
The file property of a tables list gives the file that the tables come from, if preferable you can have function to read and check these conform, potentially only allow specific formats (e.g. only CSV/RDS).
cover:
sheet_title: Widget production in England, season 2023/2024 # mandatory main sheet title in cell A1"About this publication":
- This publication is about the quantity of widgets. # arbitrary section in form 'section header: text content'
- This is a second row of information."Period covered":
- The time period covered by this publication is quarter 3, 2023. # arbitrary sectionContact:
- You can contact the team via email.
- "[[email protected]](mailto:[email protected])"# arbitrary section, use Markdown to indicate a linkcontents:
sheet_title: Contentslinks: true # whether to add a column with links to each tabnotes:
sheet_title: Notes # mandatory expecteddata: widget_notes # mandatory expectedtable_1:
sheet_title: "Table 1: Widget quantity"# mandatory expecteddata: data/widget_quantity.csv # mandatory expectedsource: The UK Widget Survey. # optional expectedblanks: Blank cells indicate that data is missing. # optional arbitrarycoverage: The data are for the North and South of England # optional arbitrarytable_2:
sheet_title: "Tables 2a and 2b: Widget quantity by geography"source: The UK Widget Survey.table_2a:
table_title: "Table 2a: Widget quantity produced in the North of England"data: data/widget_quantity_north.csvtable_2b:
table_title: "Table 2a: Widget quantity produced in the South of England"data: widget_quantity_south
I don't think there's anything surprising in this. Note that the data values will be interpreted as files if they have an extension; otherwise as environment objects. Note that YAML input will make arbitrary pre-table metadata' easier to insert (#74) and make it easier to specify multiple tables per sheet (#3).
Consider using YAML files to guide table construction.
Processing steps:
title
,description
,properties
,contact
.name
andtitle
components) and the existence (or otherwise) of the notes list.file
property of a tables list gives the file that the tables come from, if preferable you can have function to read and check these conform, potentially only allow specific formats (e.g. only CSV/RDS).yaml::read_yaml()
will read a YAML file and return an R list.The text was updated successfully, but these errors were encountered: