DatetimeAdd
datetimeAdd
takes a datetime value and adds some unit of time to it. This function is useful when you’re working with time series data that’s marked by a “start” and an “end”, such as sessions or subscriptions data.
Syntax | Example |
---|---|
datetimeAdd(column, amount, unit) |
datetimeAdd("2021-03-25", 1, "month") |
Takes a timestamp or date value and adds the specified number of time units to it. | 2021-04-25 |
Parameters
column
can be any of:
- The name of a timestamp column,
- a custom expression that returns a datetime, or
- a string in the format
"YYYY-MM-DD"
or"YYYY-MM-DDTHH:MM:SS"
(as shown in the example above).
unit
can be any of:
- “year”
- “quarter”
- “month”
- “day”
- “hour”
- “second”
- “millisecond”
amount
:
- A whole number or a decimal number.
- May be a negative number:
datetimeAdd("2021-03-25", -1, "month")
will return2021-04-25
.
Calculating an end date
Let’s say you’re a coffee connoisseur, and you want to keep track of the freshness of your beans:
Coffee | Opened On | Finish By |
---|---|---|
DAK Honey Dude | October 31, 2022 | November 14, 2022 |
NO6 Full City Espresso | November 7, 2022 | November 21, 2022 |
Ghost Roaster Giakanja | November 27, 2022 | December 11, 2022 |
Here, Finish By is a custom column with the expression:
datetimeAdd([Opened On], 14, 'day')
Comparing a date to a window of time
To check if a specific datetime falls between your start and end datetimes, use between
.
Unfortunately, Metabase doesn’t currently support functions like today
. If you want to check if today’s date falls between Opened On and Finish By in the Coffee example:
- Ask your database admin if there’s table in your database that stores dates for reporting (sometimes called a date dimension table).
- Create a new question using the date dimension table, with a filter for “Today”.
- Turn the “Today” question into a model.
- Create a left join between Coffee and the “Today” model on
[Opened On] <= [Today]
and[Finish By] >= [Today]
.
The result should give you a Today column that’s non-empty if today’s date falls inside the coffee freshness window:
Coffee | Opened On | Finish By | Today |
---|---|---|---|
DAK Honey Dude | October 31, 2022 | November 14, 2022 | November 11, 2022 |
NO6 Full City Espresso | November 7, 2022 | November 21, 2022 | November 11, 2022 |
Ghost Roaster Giakanja | November 27, 2022 | December 11, 2022 |
Accepted data types
Data type | Works with datetimeAdd |
---|---|
String | ❌ |
Number | ❌ |
Timestamp | ✅ |
Boolean | ❌ |
JSON | ❌ |
We use “timestamp” and “datetime” to talk about any temporal data type that’s supported by Metabase.
If your timestamps are stored as strings or numbers in your database, an admin can cast them to timestamps from the Data Model page.
Limitations
If you’re using MongoDB, datetimeAdd
will only work on versions 5 and up.
Related functions
This section covers functions and formulas that work the same way as the Metabase datetimeAdd
expression, with notes on how to choose the best option for your use case.
Other tools
datetimeSubtract
datetimeSubtract
and datetimeAdd
are interchangeable, since you can use a negative number for amount
. It’s generally a good idea to avoid double negatives (such as subtracting a negative number).
datetimeSubtract([Opened On], -14, "day")
does the same thing as
datetimeAdd([Opened On], 14, "day")
SQL
When you run a question using the query builder, Metabase will convert your graphical query settings (filters, summaries, etc.) into a query, and run that query against your database to get your results.
If our coffee sample data is stored in a PostgreSQL database:
SELECT opened_on + INTERVAL '14 days' AS finish_by
FROM coffee
is equivalent to the Metabase datetimeAdd
expression:
datetimeAdd([Opened On], 14, "day")
Spreadsheets
If our coffee sample data is in a spreadsheet where “Opened On” is in column A with a date format, the spreadsheet function
A:A + 14
produces the same result as
datetimeAdd([Opened On], 14, "day")
Most spreadsheet tools require use different functions for different time units (for example, you’d use a different function to add “months” to a date). datetimeAdd
makes it easy for you to convert all of those functions to a single consistent syntax.
Python
Assuming the coffee sample data is in a pandas
dataframe column called df
, you can import the datetime
module and use the timedelta
function:
df['Finish By'] = df['Opened On'] + datetime.timedelta(days=14)
is equivalent to
datetimeAdd([Opened On], 14, "day")