Normalize several series of different orders of magnitude

[rikazuo]

Good afternoon, as my first question on here, I'd like to know if any of you could help me on this.

I'm stuck on PBI on trying to bring several series to a closer order of magnitude to best fit a chart.

In this Excel file I can do it by using simple average manipulation.

Thank you!

[rikazuo]

Well, nothing better than a good night of sleep.

I created a groupby with the average of each stock to use it on a RELATED fetching its values for each ticker!

Thank you very much for your time!!

[TomMartens]

Hey @rikazuo ,

first things first - welcome to this community.

Regarding your question, I have to admit that I have my problems understanding your requirement.

Looking at the screenshot I assume the wanted result is the right chart, but it's still unclear what the x-axis is displaying.

It's also not clear what algorithm you are using to normalize the values from the left part of the screenshot: https://en.wikipedia.org/wiki/Normalization_(statistics)
Please provide information of the normalization.

It's always a good idea to prepare sample data either entering the data in Power BI Desktop (https://docs.microsoft.com/en-us/power-bi/connect-data/desktop-enter-data-directly-into-desktop) or use an Excel file to for the data generation.

Uploade the pbix and the xlsx to onedrive or dropbox and share the link.

Regards,

Tom

[rikazuo]

First of all, thank you very much for your time.

I have replaced the screen shoot for a better one in hope of explaining better.

I am most greatful for your site suggestion, I will get to it in the morning (Tokyo time here).

[TomMartens]

Hey  @rikazuo ,

you are welcome!

Please take the time and prepare sample data.

Regards,

Tom

[amitchandak]

@rikazuo ,The information you have provided is not making the problem clear to me. Can you please explain with an example.
Can you share sample data and sample output in table format? Or a sample pbix after removing sensitive data.
Appreciate your Kudos.

[rikazuo]

Thank you for your time!

My deepest appologies on not being clear on the first time.

I hope this new picture explains it better.