Advanced chart customization

You can utilize Carrot to customize your charts in addition to the dropdown menu.

When displaying data in charts, ChartHop uses the following Carrot time parameters:

Change type queries are pulled for the entire interval, all others are counted at the end of the interval. If your dashboard date range ends before the end of the month, it will display the summed value for the last day specified in the date range. ChartHop will alert you when this is the case by displaying a partially filled circle on the last month.



The date range on the dashboard is looking for data from October 22, 2023 - April 22, 2024. 



Because headcount is not a change type query, and instead displays data as of the end of the month, there is no partial circle on “October ‘23”. In the chart below, we are looking at New Hires. Notice the partial circle on both “October ‘23” and “April ‘24”. 



You can customize this chart by clicking the “Advanced Query Mode” toggle



Then, at the bottom of the edit chart modal, you can choose whether you want to customize the series, or customize each item. 



Both options will use Carrot methods that are chained together. Take a look at the Carrot filter box at the bottom of the edit chart modal:



If we break this expression down, we have the following: 

groupBy allows you to view data by different variables. Below is a chart that looks at headcount by ethnicity, from October 22, 2024 to April 22, 2024. 



Group by values are dynamic- as your departments and other values change in ChartHop, any chart that looks at that attribute will automatically update with new values. 



For this chart, you can see we added the “groupBy” value. The chart is now displaying all jobs in the ChartHop database that meet the assigned filter, sorted by ethnicity. 

You can group by up to 2 values in a non-time series chart. You would write that in the Carrot Expression like: 

db.job.find(jobFilter).groupBy{expression1, expression2}.sum{} 

For example, if you wanted to see headcount by gender and department:

db.job.find(jobFilter).groupBy{department, gender}.sum{headcount} 

You can now group by persons as well. For example, if you wanted to see metrics by recruiter, you could write:

db.job.find(jobFilter).groupBy{recruiter}.count()

This will group by the recruiter field, therefore updating as recruiters move through your organization. 

We have simplified the syntax for our most commonly used queries. These work in other parts of the platform, like actions, profile tabs, and resources as well.

findHires(fromDate, untilDate) displays hires between the specified interval.

findHires('2024-01-01', '2024-02-01')returns all the hires that happened in the month of January of 2024. 

You can chain methods with these functions as well:

Other ways to apply the turnover rate function: 

How we calculate turnover rate: 

turnoverRate('2023-01-01', '2023-06-01', jobFilter)

You can pull form responses into a dashboard easily as well. 

findAnswers(questionId, fromDate, untilDate)

findAnswers('downwardReviewRating', '2024-01-01','2024-02-01') returns the form answers to the question linked to the “downwardReviewRating” field that were submitted during the month of January, 2024. 

You can chain these with methods: 

findAnswers('downwardReviewRating','2024-01-01','2024-02-01').mean{value} returns the average downwardReviewRating score. 

You can also utilize groupBy if needed: 

findAnswers('downwardReviewRating','2024-01-01','2024-02-01').groupBy{submitPerson.department.mean{value} returns the average downwardReviewRating score, grouped by the department of the person who submitted the form. 

You can retrieve data from a specific assessment using findAnswers as well:

findAnswers(questionId, assessmentId, fromDate, untilDate)

Packages: Headcount Planning | Compensation Reviews | HRIS