Forum Discussion
Box and Whisker Chart setting: 1.5IQR and Inclusive/Exclusive
Hi
I'm trying to plot my data and identify outliers. Here's my data. I have three industries as categories, and one metric. I want to identify outliers in each industry. I created a Sampling Index column for 'sampling'. I am confused with the settings in the Box and Whisker chart in Power BI. In Chart Options in the tool box, I chose either <1.5 IQR or =1.5IQR as my whisker type, either Exclusive or Inclusive as in the Quartile option, and have the outlier option turned on in all settings. I don't understand the math behind each setting, can someone explain and suggest when to use what? I also attached the graphs that I plot in 4 scenarios.
In my data, negative data would not make sense as the metric does not allow negative numbers. Therefore, I wonder how to look for outliers that are in the lower bound. It looks like the =1.5IQR setting gives me a range that includes negative values, which is not ideal in my case. I wonder if I should use the customize my chart instead. But how?
Please advise when do use =1.5IQR or <1.5IQR, and when to select Inclusive or Exclusive quartile. Thank you!
| Industry Name | Metric Name | Sampling Index | Metric Data |
| AAA | Metric1 | 1 | 41.4 |
| AAA | Metric1 | 2 | 40.6 |
| AAA | Metric1 | 3 | 32.4 |
| AAA | Metric1 | 4 | 19 |
| AAA | Metric1 | 5 | 11.8 |
| AAA | Metric1 | 6 | 9.8 |
| AAA | Metric1 | 7 | 10.2 |
| AAA | Metric1 | 8 | 5.473701539 |
| AAA | Metric1 | 9 | 100 |
| AAA | Metric1 | 10 | 18.8 |
| AAA | Metric1 | 11 | 22.77 |
| AAA | Metric1 | 12 | 35 |
| AAA | Metric1 | 13 | 9.89 |
| AAA | Metric1 | 14 | 6.61 |
| AAA | Metric1 | 15 | 9.29 |
| AAA | Metric1 | 16 | 11.07 |
| BBB | Metric1 | 17 | 14.32 |
| BBB | Metric1 | 18 | 1.36 |
| BBB | Metric1 | 19 | 1.32 |
| BBB | Metric1 | 20 | 0.0127 |
| BBB | Metric1 | 21 | 27.81 |
| BBB | Metric1 | 22 | 24.3 |
| BBB | Metric1 | 23 | 24.47 |
| BBB | Metric1 | 24 | 14.24747748 |
| BBB | Metric1 | 25 | 13.69800397 |
| BBB | Metric1 | 26 | 16.62681592 |
| BBB | Metric1 | 27 | 6.294481627 |
| BBB | Metric1 | 28 | 5.628550029 |
| BBB | Metric1 | 29 | 24.11336717 |
| BBB | Metric1 | 30 | 24.36012831 |
| BBB | Metric1 | 31 | 0.1099 |
| BBB | Metric1 | 32 | 0.13 |
| BBB | Metric1 | 33 | 0.06 |
| BBB | Metric1 | 34 | 0.06 |
| BBB | Metric1 | 35 | 0.05 |
| BBB | Metric1 | 36 | 0.05 |
| BBB | Metric1 | 37 | 0 |
| BBB | Metric1 | 38 | 79 |
| BBB | Metric1 | 39 | 78 |
| BBB | Metric1 | 40 | 78 |
| BBB | Metric1 | 41 | 73 |
| BBB | Metric1 | 42 | 73 |
| BBB | Metric1 | 43 | 3.62 |
| BBB | Metric1 | 44 | 63 |
| BBB | Metric1 | 45 | 58 |
| BBB | Metric1 | 46 | 14 |
| BBB | Metric1 | 47 | 8.5 |
| BBB | Metric1 | 48 | 9.3 |
| BBB | Metric1 | 49 | 8 |
| BBB | Metric1 | 50 | 8 |
| BBB | Metric1 | 51 | 8.8 |
| BBB | Metric1 | 52 | 7.7 |
| BBB | Metric1 | 53 | 5.98 |
| BBB | Metric1 | 54 | 38 |
| BBB | Metric1 | 55 | 33 |
| BBB | Metric1 | 56 | 20 |
| BBB | Metric1 | 57 | 50.66 |
| BBB | Metric1 | 58 | 51.45 |
| BBB | Metric1 | 59 | 50.05 |
| BBB | Metric1 | 60 | 51.6 |
| CCC | Metric1 | 61 | 21.64 |
| CCC | Metric1 | 62 | 14.55 |
| CCC | Metric1 | 63 | 0 |
| CCC | Metric1 | 64 | 0 |
| CCC | Metric1 | 65 | 0 |
| CCC | Metric1 | 66 | 0 |
| CCC | Metric1 | 67 | 0 |
| CCC | Metric1 | 68 | 4.96 |
| CCC | Metric1 | 69 | 3.02 |
| CCC | Metric1 | 70 | 3.5 |
| AAA | Metric1 | 71 | 41.02 |
| AAA | Metric1 | 72 | 22.36 |
| AAA | Metric1 | 73 | 25.83 |
| AAA | Metric1 | 74 | 25.55 |
| AAA | Metric1 | 75 | 18.15 |
| CCC | Metric1 | 76 | 0.192086903 |
| CCC | Metric1 | 77 | 0.244432374 |
| CCC | Metric1 | 78 | 0.265173836 |
| BBB | Metric1 | 79 | 4.23 |
| BBB | Metric1 | 80 | 6.29 |
| BBB | Metric1 | 81 | 5.97 |
| BBB | Metric1 | 82 | 1.25 |
| BBB | Metric1 | 83 | 0.71 |
| CCC | Metric1 | 84 | 25.3 |
| CCC | Metric1 | 85 | 4.3 |
| CCC | Metric1 | 86 | 0 |
| CCC | Metric1 | 87 | 0 |
| CCC | Metric1 | 88 | 0 |
| CCC | Metric1 | 89 | 1.11 |
| CCC | Metric1 | 90 | 1.12 |
Hi Anonymous ,
You can refer to this article: Power BI Box and Whisker chart.
Quartile calculation:
1. Inclusive - When calculation the 1st and 3rd quartile, the median is included in the calculation. Equivalent of the Excel calculation QUARTILE.INC()
2. Exclusive - When calculation the 1st and 3rd quartile, the median is excluded in the calculation. Equivalent of the Excel calculation QUARTILE.EXC()Whisker Type:
1. Min/Max - The whiskers represent the minimum and maximum values of the dataset.
2. < 1.5 IQR - The top and bottom whiskers are set to the highest/lowest value of the dataset that are included in the 1.5IQR range.
3. = 1.5IQR - The top and bottom whiskers are set to 1.5IQR of the dataset.
4. Custom - The whiskers can be set to a custom percentile value based on the dataset. The lower value is bound to the lower percentile possible and 25%. And the same is for the higher value, but then from 75% and up to the highest percentile value possible.Best Regards,
IceyIf this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
1 Reply
- Icey
Community Support
Hi Anonymous ,
You can refer to this article: Power BI Box and Whisker chart.
Quartile calculation:
1. Inclusive - When calculation the 1st and 3rd quartile, the median is included in the calculation. Equivalent of the Excel calculation QUARTILE.INC()
2. Exclusive - When calculation the 1st and 3rd quartile, the median is excluded in the calculation. Equivalent of the Excel calculation QUARTILE.EXC()Whisker Type:
1. Min/Max - The whiskers represent the minimum and maximum values of the dataset.
2. < 1.5 IQR - The top and bottom whiskers are set to the highest/lowest value of the dataset that are included in the 1.5IQR range.
3. = 1.5IQR - The top and bottom whiskers are set to 1.5IQR of the dataset.
4. Custom - The whiskers can be set to a custom percentile value based on the dataset. The lower value is bound to the lower percentile possible and 25%. And the same is for the higher value, but then from 75% and up to the highest percentile value possible.Best Regards,
IceyIf this post helps, then please consider Accept it as the solution to help the other members find it more quickly.