Time-series
Where your data varies over time (e.g. by month)

Basic time-series

This is an example of a basic time-series format:
  • Each row represents a single variable
  • The first column must have the names of each variable
  • The first row must have dates for each value

Time-series with categories

This is an example of the time-series format with categories included. You can include several categories. See more on categories here.
  • Each row represents a single variable, for a single category item.
    • For example, row 5 in the example above represents the Website Revenue variable, when the Product category is Model X. Together, rows 4 through 6 make up the entire Website Revenue variable.
  • The columns can be split into 3 sections: Variable Names, Categories, and Values
    • The first column must have the Variable Names
      • In the example above, column A has all the Variable Names
    • The next columns hold the Categories - the first row must have the name of the category, and the rows below may have the name of an item in that category
      • In the example above, columns B and C are the Categories columns
    • The last columns hold the Values - the first row must have dates, and the values themselves should be numbers (not text)
      • In the example above, columns D, E, F, G, ... are the Values columns
If a variable has more than one category dimension, you would just create a row for each possible iteration. For example, if Website Revenue was tracked by both Product and Geography, you would have 12 rows for Website Revenue (3 Products x 4 Geographies).

Time-series with linked categories

This is an example of the time-series format with categories and mappings (i.e. links between categories & category items) included. You can include several categories and several mappings in your Google Sheet. For more on Linking Categories go here.
If you set up the mappings in your Data Source, Causal will automatically know how to slice and dice your variables.
  • Each row represents a single variable, for a single category item.
    • For example, row 5 in the example above represents the Salary variable, when the Role category is Marketing Role. Together, rows 2 onwards make up the entire Salary variable.
  • The columns can be split into four sections: Variable Names, Categories, Category Mappings, and Values
    • The first column must have the Variable Names
      • In the example above, column A has all the Variable Names
    • The next columns hold the Categories - the first row must have the name of the category, and the rows below may have the name of an item in that category
      • In the example above, column B is the Categories column
    • The next columns hold the Category Mappings
      • The first row must have the name of the category being mapped from and the name of the category being mapped to, in the following format: [from category] > [to category]
        • The arrow (">") is important - it's how Causal distinguishes between a normal category column, and a category mapping column!
      • The rows below may have the name of an item in the category being mapped to
      • In the example above, column C is the Category Mappings column. It is mapping from Role to City
    • The last columns hold the Values - the first row must have dates, and the values themselves should be numbers (not text)
      • In the example above, columns D, E, ... are the Values columns