Values bar chart are too close to observe the difference

[Anonymous]

Hello,

Here's the screenshot.

I tried to use slicer to filter out the specific category, and to observe whether each piece in this category is larger than upper bound(shows in red color) or smaller than lower bound(shows in green color. However, the range of the values is between 210.44 and 210.64 so that it's hard for me to observe the difference among 35 pieces via chart. In addition, due to the variety of the value of other categories, it can't be work to customized the start value and end value of y label. So is there any other way to achieve my target?   Thanks

New Update:
@Anonymous 

Actually, the values of X-axis represent piece id, which belongs to categorical variable, so I don't think its good to use line chart to show the trend(?

Here's the screenshot for the part of dataset

The goal is try to obersve the difference among different pieces for each category (e.g. 1-1, 2-2, etc.)

[Anonymous]

Hi @Anonymous 

I intercepted part of the data and used Line chart to reflect it. Is this effect what you want ? You can compare different values of the same ID, or compare the trends of the same value of different IDs.

Best Regards

Community Support Team _ Ailsa Tao

If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

[Anonymous]

As I know, since there's no relationship between the categorical variable(ID) in x-axis, it's a bit weird to use line chart to observe the difference. 

I tried to separately donormalization and standardization for the data, and it did achieve my goal. But, just wonder to know is there any better way to solve it?

Much appreciated

[Anonymous]

Hi @Anonymous 

Because the numbers are too close, the difference is difficult to show .Maybe you can try Line chart ? The line chart can clearly show the trend of data changes .

As for the diversification of the categories, could you provide a sample to describe your needs in detail ?

Best Regards

Community Support Team _ Ailsa Tao

If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.