Group and Sum Data Separated by Blank Rows in Google Sheets

Are you looking to effortlessly group and sum data separated by blank rows in Google Sheets? Look no further! In this article, we’ll explore a simple yet effective method to enhance your data analysis efficiency.

A Simple Solution to a Common Problem

Normally, we use a category column to identify groups in a dataset and summarize the data using functions like SUMIF, SUMIFS, or QUERY in Google Sheets. However, what if you need to group and sum data separated by one or more blank rows?

This is where our solution comes in. We’ll show you how to automatically assign unique identifiers to each set of data separated by blank rows in Google Sheets, without the need for scripting. With this method, you can effectively group and sum your data.

Sample Data and the Problem to Be Solved

Let’s consider a sample dataset with staff strength, department, and notes recorded in columns A, B, and C, respectively. The objective is to calculate the total staff strength for each group of rows separated by blank rows.

It’s important to note that to identify blank rows, the entire row must be blank, not just a single cell. Now, let’s dive into the solution for grouping and summing datasets with blank row separation in Google Sheets.

The Formula for Grouping Data Separated by Blank Rows in Google Sheets

To achieve our goal, we’ll use an array formula. Apply the following formula to cell D2, the top row of the next available column:

=ARRAYFORMULA(LET(data, A2:C, empty, IF(LEN(TRIM(TRANSPOSE(QUERY(TRANSPOSE(data),,9^9))))>0,1,), rc, COUNTIFS(empty, "<>"&empty, SEQUENCE(ROWS(data)), "<="&SEQUENCE(ROWS(data))), test, SCAN(1, rc, LAMBDA(a, v, IF(v=0, a, v))), IF(LEN(empty), test, )))

This formula assigns unique numbers to each group, ensuring efficient grouping and summing of data separated by blank rows.

Formula Explanation

Now, let’s break down the components of the formula to gain valuable insights into its functionality.

1. Returning 1 or Null Based on Row Emptiness

This formula checks for the emptiness of rows and assigns 1 or null accordingly.

2. Running Count of Non-Blank Cells in Blank Rows

This formula calculates the running count of non-blank cells in blank rows.

3. Replacing 0 with the Value Greater than 0 from the Cell Above

This step uses a lambda function to replace 0 with the value from the cell above, effectively grouping the data separated by blank rows.

4. Grouping Data Separated by Blank Rows

This final step fine-tunes the result by removing values in blank rows, creating a category column for grouping and summing data in Google Sheets.

Practical Applications and Results

With the category column established, you can easily perform various operations on your grouped and summed data. Let’s explore a couple of examples to illustrate the possibilities.

To get the total staff strength in each group, you can use the following QUERY formula:

=QUERY(A2:D, "select sum(A) where D is not null group by D label sum(A)''")

To get the total only in the third group, you can modify the QUERY formula with OFFSET and LIMIT clauses. Alternatively, you can use the SUMIF formula:

=SUMIF(D2:D, INDEX(UNIQUE(TOCOL(D2:D, 1)), 3), A2:A)

How to Replace Category Numbers with Category Texts

If you prefer category texts like “Category A,” “Category B,” etc., you can easily achieve this with a simple workaround.

1. Create categories in column D.
2. In cell G2, use the formula =UNIQUE(TOCOL(D2:D, 1)) to return unique categories.
3. Enter the desired category texts in cells H2:H5.
4. In cell E2, use the formula =ArrayFormula(XLOOKUP(D2:D, G2:G, H2:H, )) to replace the category numbers with category texts.

This will provide a clearer representation of your grouped and summed data separated by blank rows in Google Sheets.

Conclusion

In this article, we’ve explored a simple and effective method to group and sum data separated by blank rows in Google Sheets. By following the provided formula and examples, you can enhance your data analysis capabilities and streamline your workflow.

Remember, the key to successful data analysis lies in utilizing the right tools and techniques. If you have any doubts or questions, feel free to reach out. Happy data analyzing!

Check out Crawlan.com for more tips and tricks on Google Sheets and other data-related topics.