Excel formula for Beginners – How to Average response time per month in Excel

Hits: 296


(Excel examples for Beginners)

In this end-to-end excel example, you will learn – Excel formula for Beginners – How to Average response time per month in Excel.


Excel formula for Beginners – How to Average response time per month in Excel

Generic formula



To average response times by month, you can use a formula based on the AVERAGEIFS function, together with the EOMONTH function.

In the example shown, the formula in G5 is:


How this formula works

This formula uses the named ranges “dates” (B5:B25) and “durations” (D5:D25). Durations column D are in minutes, calculated by subtracting the date opened from date closed.

The AVERAGEIFS function is designed to average ranges based on multiple criteria. In this case, we configure AVERAGEIFS to average durations by month using two criteria: (1) matching dates greater than or equal to the first day of the month, (2) matching dates less than or equal to the last day of the month.

To bracket dates by month, we use a simple trick to make things easier: In column F, instead of typing month names (“Jan”, “Feb”, Mar”, etc.) we add we add actual dates for the first of each month (1/1/2016, 2/1/2016, 3/1/2016, etc.),. Then, we use the custom date format (“mmm”) to display the month names.

This makes it a lot easier to build the criteria we need for AVERAGEIFS using values in column F.  To match dates greater than or equal to the first of the month, we use:


To match dates less than or equal to the last day of the month, we use:


We get the EOMONTH to return the last day of the same month by supplying zero for the months argument.

Personal Career & Learning Guide for Data Analyst, Data Engineer and Data Scientist

Applied Machine Learning & Data Science Projects and Coding Recipes for Beginners

A list of FREE programming examples together with eTutorials & eBooks @ SETScholars

95% Discount on “Projects & Recipes, tutorials, ebooks”

Projects and Coding Recipes, eTutorials and eBooks: The best All-in-One resources for Data Analyst, Data Scientist, Machine Learning Engineer and Software Developer

Topics included: Classification, Clustering, Regression, Forecasting, Algorithms, Data Structures, Data Analytics & Data Science, Deep Learning, Machine Learning, Programming Languages and Software Tools & Packages.
(Discount is valid for limited time only)

Disclaimer: The information and code presented within this recipe/tutorial is only for educational and coaching purposes for beginners and developers. Anyone can practice and apply the recipe/tutorial presented here, but the reader is taking full responsibility for his/her actions. The author (content curator) of this recipe (code / program) has made every effort to ensure the accuracy of the information was correct at time of publication. The author (content curator) does not assume and hereby disclaims any liability to any party for any loss, damage, or disruption caused by errors or omissions, whether such errors or omissions result from accident, negligence, or any other cause. The information presented here could also be found in public knowledge domains.

Learn by Coding: v-Tutorials on Applied Machine Learning and Data Science for Beginners

Please do not waste your valuable time by watching videos, rather use end-to-end (Python and R) recipes from Professional Data Scientists to practice coding, and land the most demandable jobs in the fields of Predictive analytics & AI (Machine Learning and Data Science).

The objective is to guide the developers & analysts to “Learn how to Code” for Applied AI using end-to-end coding solutions, and unlock the world of opportunities!