Forum Discussion
Two data granularities overlayed
Hi JasperVanGils ,
This doesn't make sense, in the Line and clustered column chart, the number of turning points and bars of the folded line are displayed based on the granularity on the x-axis, so their granularity needs to be consistent. You could set the quarter as a line, which would produce a baseline to measure each month against the average of the quarter, which would be statistically significant. Bars, on the other hand, show values by date or totaled by quarter, so that you can differentiate how much granularity there is at different times.Best regards,
Albert HeIf this post helps, then please consider Accept it as the solution to help the other members find it more quickly
Hi JasperVanGils ,
According to your description, regarding visualization, you can use Line and clustered column chart. since it needs to be yes they have the same date granularity, you can create a corresponding quarterly profit column on calendar table. Here are the detailed steps
Sample data
Pricing table
| Date | Closing Prices |
| 1/2/2024 | 521 |
| 2/4/2024 | 456 |
| 3/5/2024 | 123 |
| 4/6/2024 | 478 |
| 5/7/2024 | 598 |
| 6/7/2024 | 632 |
| 7/8/2024 | 458 |
| 8/9/2024 | 124 |
| 9/10/2024 | 523 |
| 10/11/2024 | 458 |
Income statement table
| Quarter Date | Average Price |
| 3/1/2024 | 500 |
| 6/1/2024 | 400 |
| 9/1/2024 | 450 |
| 10/1/2024 | 600 |
Relationship
Create columns
Average_Price_Quarter =
VAR _Quarter = QUARTER('Calendar Table'[Date])
RETURN
CALCULATE(
MAX('Income statement table'[Average Price]),
FILTER(
'Income statement table',
QUARTER('Income statement table'[Quarter Date]) = _Quarter
)
)Qtr = 'Calendar Table'[Date].[QuarterNo]
Final output
Best regards,
Albert He
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly