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A markdown guide

- Vizzuality

Welcome!

###### This is a highlight text. includes only top-level, national-level scores or ratings for countries. It does not currently contain any of the indicator-, category-, or question-level data that comprise the overall national ratings or scores from each data producer. To access this more disaggregated data, as well as further background information and analysis on each data set, please visit the respective data producer organization’s website (relevant links are included in the downloadable .csv files). The following is a full description of the metadata and data fields used by Alliance data producers to share their data in a consistent and comparable manner on the Governance Data Alliance website and via associated data downloads (.csv files) and API access.

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This is an example of comparison table

  Option Description Address
data path to data files to supply the data that will be passed into templates. Lorem ipsum id suscipit metus varius. Aenean eget blandit elit,
engine engine to be used for processing templates. Handlebars is the default. Lorem ipsum Ut enim ad minim veniam, quis nostrud exercitation
ext extension to be used for dest files. Lorem ipsum unt in culpa qui officia deserunt mollit anim id est laborum

and some lists

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  • Suspendisse feugiat fermentum eros id sagittis. Suspendisse potenti. Donec dapibus eu sem quis.
  • Convallis. Aenean neque velit, scelerisque et commodo sit amet, sodales eget urna.
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  2. Suspendisse feugiat fermentum eros id sagittis. Suspendisse potenti. Donec dapibus eu sem quis
  3. convallis. Aenean neque velit, scelerisque et commodo sit amet, sodales eget urna.

Writing styles

This is an amazing bold text

And this, and incredible italic text!

I’m a link

Those are our awesome titles

Super big title

Medium title

Small title

and of course, images!

Here, alt text to explain what is this image about

Here is how you can define Terms

desired_direction: “Up” if the scoring scale is one where higher scores are positive, “down” if the scale is one where lower scores are positive

has_historical_info: “Yes” if data is available for prior years, “no” if not

income_group: Country’s income classification, according to the World Bank, based on the country’s gross national income (GNI) per capita. There are six income groupings: low, lower-middle, upper-middle, high non-OECD, and high OECD.

iso: ISO 3166-1 alpha-3 code, three-letter country codes to represent countries, dependent territories, and special areas of geographical interest

lending_category: Type of lending the country receives from the World Bank (IDA, Blend, IBRD)

max_score: The maximum score a country can have for the particular dataset

methodology_link: URL to obtain further information about the product.

min_score: The minimum score a country can have for the particular dataset

name: Country name

notes: Any notes or clarifications about the data.(e.g. What specific commodities are covered by the Resource Governance Index in each country)

organization: Name of the organization that produces the data set

product_description: A short description of what the product assesses, in plain English terms

product_logo: Full URL to a jpg or png version of the product logo.

product_name: The alphanumeric name of the dataset in question (e.g. Global Integrity Report)

region: Country’s regional classification, according to the World Bank. There are East Asia and Pacific, Europe and Central Asia, Latin America and the Caribbean, Middle East and North Africa, North America, South Asia, and Sub-Saharan Africa.

score: Country’s rating in the particular assessment for a given year

score_range: Ranges by which scores are broken down, from best to worst

score_text: Provides richer context for “score” values that also might contain additional, companion information.

short_name: A machine readable version of the product name with no spaces or caps (e.g. global_integrity_report).

units: Unit in which the score is measured (example: no unit, percentage, United States Dollars, Millions of United States Dollars, etc…)

units_abbr: Abbreviation for the unit in which the score is measured (example: %, USD, M USD, etc…)

year: This refers to the year assessed, the year the data was gathered, the year it was published, and/or the year it was updated; see the notes field and each producer’s website for details.

And here you have a reference in case you miss something:

##https://guides.github.com/features/mastering-markdown/