CountIf

CountIf counts the total number of rows in a table that match a condition. CountIf counts every row, not just unique rows.

Syntax: CountIf(condition).

Example: in the table below, CountIf([Plan] = "Basic") would return 3.

Aggregations like CountIf should be added to the query builder’s Summarize menu > Custom Expression (scroll down in the menu if needed).

Parameters

CountIf accepts a function or conditional statement that returns a boolean value (true or false).

Multiple conditions

We’ll use the following sample data to show you CountIf with required, optional, and mixed conditions.

Required conditions

To count the total number of rows in a table that match multiple required conditions, combine the conditions using the AND operator:

CountIf(([Plan] = "Basic" AND [Active Subscription] = true))

This expression will return 2 on the sample data above (the total number of Basic plans that have an active subscription).

Optional conditions

To count the total rows in a table that match multiple optional conditions, combine the conditions using the OR operator:

CountIf(([Plan] = "Basic" OR [Active Subscription] = true))

Returns 4 on the sample data: there are three Basic plans, plus one Premium plan has an active subscription.

Some required and some optional conditions

To combine required and optional conditions, group the conditions using parentheses:

CountIf(([Plan] = "Basic" OR [Plan] = "Business") AND [Active Subscription] = "false")

Returns 2 on the sample data: there are only two Basic or Business plans that lack an active subscription.

Tip: make it a habit to put parentheses around your AND and OR groups to avoid making required conditions optional (or vice versa).

Conditional counts by group

In general, to get a conditional count for a category or group, such as the number of inactive subscriptions per plan, you’ll:

1. Write a CountIf expression with your conditions.
2. Add a Group by column in the query builder.

Using the sample data:

Count the total number of inactive subscriptions per plan:

CountIf([Active Subscription] = false)

Alternatively, if your Active Subscription column contains null (empty) values that represent inactive plans, you could use:

CountIf([Payment], [Plan] != true)

The “not equal” operator != should be written as !=.

To view your conditional counts by plan, set the Group by column to “Plan”.

Tip: when sharing your work with other people, it’s helpful to use the OR filter, even though the != filter is shorter. The inclusive OR filter makes it easier to understand which categories (e.g., plans) are included in your conditional count.

Accepted data types

CountIf accepts a function or conditional statement that returns a boolean value (true or false).

Related functions

Different ways to do the same thing, because it’s fun to try new things.

Metabase

• case
• CumulativeCount

Other tools

• SQL
• Spreadsheets
• Python

case

You can combine Count with case:

Count(case([Plan] = "Basic", [ID]))

to do the same thing as CountIf:

CountIf([Plan] = "Basic")

The case version lets you count a different column when the condition isn’t met. For example, if you’ve got data from different sources:

To count the total number of Basic plans across both sources, you could create a case expression to:

• Count the rows in “ID: Source A” where “Plan: Source A = “Basic”
• Count the rows in “ID: Source B” where “Plan: Source B = “basic”

Count(case([Plan: Source A] = "Basic", [ID: Source A], 
            case([Plan: Source B] = "basic", [ID: Source B])))

CumulativeCount

CountIf doesn’t do running counts. You’ll need to combine CumulativeCount with case.

If our sample data is a time series:

And we want to get the running count of active plans like this:

Create an aggregation from Summarize > Custom expression:

CumulativeCount(case([Active Subscription] = true, [ID]))

You’ll also need to set the Group by column to “Created Date: Month”.

SQL

When you run a question using the query builder, Metabase will convert your query builder settings (filters, summaries, etc.) into a SQL query, and run that query against your database to get your results.

If our sample data is stored in a PostgreSQL database, the SQL query:

SELECT COUNT(CASE WHEN plan = "Basic" THEN id END) AS total_basic_plans
FROM accounts

is equivalent to the Metabase expression:

CountIf([Plan] = "Basic")

If you want to get conditional counts broken out by group, the SQL query:

SELECT 
    plan,
    COUNT(CASE WHEN active_subscription = false THEN id END) AS total_inactive_subscriptions
FROM accounts
GROUP BY 
    plan

The SELECT part of the SQl query matches the Metabase expression:

CountIf([Active Subscription] = false)

The GROUP BY part of the SQL query matches a Metabase Group by set to the “Plan” column.

Spreadsheets

If our sample data is in a spreadsheet where “ID” is in column A, the spreadsheet formula:

=CountIf(B:B, "Basic")

produces the same result as the Metabase expression:

CountIf([Plan] = "Basic")

Python

If our sample data is in a pandas dataframe column called df, the Python code:

len(df[df['Plan'] == "Basic"])

uses the same logic as the Metabase expression:

CountIf([Plan] = "Basic")

To get a conditional count with a grouping column:

## Add your conditions

    df_filtered = df[df['Active subscription'] == false]

## Group by a column, and count the rows within each group

    len(df_filtered.groupby('Plan'))

The Python code above will produce the same result as the Metabase CountIf expression (with the Group by column set to “Plan”).

CountIf([Active Subscription] = false)

Further reading

• Custom expressions documentation
• Custom expressions tutorial