POWER BI - Ribbon Chart, Waterfall, Scatter Chart, Bubble Chart, Dot Plot Chart
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This document contains summaries of different chart types in Power BI including ribbon charts, waterfall charts, line charts, scatter charts, bubble charts, and dot plots. It provides examples of each chart type using sample sales data and discusses how they can be used to visualize rankings over time, running totals, comparisons between multiple variables, and categorical grouping. Format options like colors, labels, and customizations are also demonstrated.
POWER BI - Ribbon Chart, Waterfall, Scatter Chart, Bubble Chart, Dot Plot Chart
- 1. 11/26/2020 Ribbon Chart 1/1 Sales Volume by Year and Region Name Year 1995 2000 2005 2010 2015 33K 31K 61K 24K 61K 42K 41K 49K 25K 43K 26K 52K 30K 40K 48K 61K 38K 26K 17K 14K 30K 10K 27K 21K 19K 11K12K 23K 20K 24K 19K 29K 26K 14K 11K 19K 15K 14K 28K 12K 27K 19K 24K 21K 13K18K 25K 13K 27K 27K 15K 19K 16K 17K 13K 11K 25K 10K 25K 16K21K 11K11K 18K17K 21K 24K 24K 12K 10K 13K 16K 30K 27K 51K 22K 51K 37K 38K 24K 42K 39K 50K 24K 49K 43K 27K 35K 35K 24K 30K 26K 55K 21K 35K 44K 52K 42K 37K 52K 37K 42K 52K 22K 28K 26K 34K 47K Region Name Greater Manchester Merseyside South Yorkshire Tyne and Wear West Midlands West Yorkshire Ribbon Chart You can create ribbon charts to visualize data, and quickly discover which data category has the highest rank (largest value). Ribbon charts are effective at showing rank change, with the highest range (value) always displayed on top for each time period. We can see that we've got West Yorkshire starting off third and then it comes up to second. Then goes down to third again. Similarly we can see very clearly that South Yorkshire tarts at fifth and then becomes fourth in 2001, before slipping back down. Ribbon Chart allows us to see the volume with the total. So it's equivalent to the stacked, but it doesn't display them in a fixed order like the stacked charts do. Instead, it puts at the top the one which is the biggest and at the bottom the one which is the smallest. Format + Ribbons section or Format + Data Labels So Ribbons are useful when you want to know the ranking of individual categories, together with their size. So it serves a different purpose to the line charts and the stacked area charts, but it does make for an interesting topic of conversation.
- 2. 11/26/2020 Waterfall Chart - Cumulative 1/1 SalesVolume by Year 0.0M 0.5M 1.0M 1.5M 2.0M 2.5M 3.0M 3.5M Date Year SalesVolume 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Total Increase Decrease Total Waterfall Chart: Cumulative WATERFALL CHARTS: - show a running total as Power BI adds and subtracts values, - useful for understanding how an initial value is affected by a series of positive and negative changes, - are quite useful when you're want to have an allocated cumulative count or if you want to drill down into the significant figures. For instance, you might be calculating a company's profits and seeing what the most profitable items were and which made the most loss. So you can be auditing the major changes. Example: How many homes did we sell by the end of 2004? Using a Waterfall Chart, each year's sales volumes gets added to the previous year. As we can see, 243,065 is the Sales Volume in 2004.
- 3. 11/26/2020 Waterfall Chart - Breakdown 1/1 SalesVolume by Year and RegionName 0K 50K 100K 150K 200K Year SalesVolume 1995 Other WestMidlands GreaterManches… 1996 Other GreaterManches… WestYorkshire 1997 Merseyside Other GreaterManches… 1998 Other GreaterManches… WestYorkshire 1999 Other SouthYorkshire GreaterManches… 2000 Other WestYorkshire GreaterManches… 2001 Other GreaterManches… WestYorkshire 2002 Merseyside Other WestMidlands 2003 Other Merseyside SouthYorkshire 2004 WestYorkshire GreaterManches… Other 2005 Other GreaterManches… WestYorkshire 2006 Other WestMidlands WestYorkshire 2007 WestYorkshire GreaterManches… Other 2008 WestMidlands GreaterManches… Other 2009 WestMidlands Other Increase Decrease Total Other Waterfall Chart: Breakdown If we add Region Name into the Breakdown, each of the Regions gets added into all of the years. We can see that when we get to 2004 and 2005, we have got some negative sales volume compared to the previous year. And then 2009 drops off completely. Format + Sentiment colors: Increase - Green: means that these are your big advances. Decrease - Red: means these are your biggest decliners. To see the most 2 significant (the biggest bottom and the biggest top): Format + Breakdown + 2. Note: it is showing 3 breakdowns, as the others are going to be wrapped up into Other. Also, as soon as I put in a breakdown, it is not longer cumulative (the end figure is the totality for that year). For example, we can see that in 2003, Merseyside has got up 2000 units and West Midlands has gone down by 2000 units.
- 4. 11/26/2020 Line Chart 1/1 Line Chart: Average House Price change So we can see that we start off at around 4% (1997) go all the way up to +28% (2004), and then all the way down to -9.6 (2009). Note: Change the aggregation for 12m%change 12m% Change by Year -10 -5 0 5 10 15 20 25 30 Year 12m%Change 2000 2005 2010 2015 0.0 5.4 28.6 -9.6 3.8 3.0 -3.3 4.7 4.2 3.8 9.6 7.0 0.6 7.3 26.1 8.2 -3.0 -0.6
- 5. 11/26/2020 Waterfall 2 1/1 Waterfall Chart: Average House Price change So we can see that: - between 2001 and 2002: we have the biggest raisers in South Yorkshire and Tyne and Wear - between 2004 and 2005: we have got huge declines in Tyne and Wear and Merseyside. So it just allows a different view of your data and see how it's been going over time. 12m% Change by Year and RegionName -10 0 10 20 30 40 50 60 Year 12m%Change 1996 WestMidlands GreaterManchester Other 1997 Other SouthYorkshire WestYorkshire 1998 Merseyside SouthYorkshire Other 1999 WestMidlands GreaterManchester Other 2000 Merseyside TyneandWear Other 2001 SouthYorkshire TyneandWear Other 2002 SouthYorkshire TyneandWear Other 2003 Merseyside Other WestMidlands 2004 Other TyneandWear Merseyside 2005 Other WestYorkshire GreaterManchester 2006 Other SouthYorkshire Merseyside 2007 Other WestYorkshire GreaterManchester 2008 Other SouthYorkshire GreaterManchester 2009 WestMidlands WestYorkshire Other 2010 Other WestYorkshire WestMidlands Increase Decrease Total Other
- 6. 11/26/2020 Scatter Chart 1/1 Scatter Chart: Comparing two different values How does the Sales volume vary according to Price Inflation? - If houses are rising quickly, do we have more Sales Volume? So people are trying to buy the houses before the prices get too high. - If it's going down, do we have a reduction in the Sales Volume? - Are people frightened and not want to buy? So let's compare SUM Sales Volume and AVG House Price Inflation, using a Scatter chart. Note: - add Date into Details, so we don't have it overall. - drag Region Name to Legend, so we have each Region in a different colour. So we can now see the difference in sales volume for the various Regions. Sales Volume and Sum of 12m% Change by Year and RegionName -200 -100 0 100 200 300 400 500 Sales Volume Sumof12m%Change 10K 20K 30K 40K 50K 60K RegionName Greater Manchester Merseyside South Yorkshire Tyne and Wear West Midlands West Yorkshire
- 7. 11/26/2020 Scatter Chart2 1/1 Scatter Chart: Showing Dates at once So the question is: So, do we want all of the dates to be shown at once, or do we want it to be shown more as a presentation? What if I want to concentrate on one year at a time? - Drag Year down from Details to Play Axis. Clicking on the Play Button, we can see the dots for each year and how they change over time. - Add Sales Volume to Size: the bigger the Sales Volume, the bigger the Size. Clicking on the Play Button, we can see that the further right we go, the more the circles get bigger. But as soon as we get to the left-hand side, they start reducing in size. Sales Volume, Sum of 12m% Change and Sales Volume by RegionName and Year -200 -100 0 100 200 300 400 500 Sales Volume Sumof12m%Change 10K 20K 30K 40K 50K 60K 2016 RegionName 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Greater Manchester Merseyside South Yorkshire Tyne and Wear West Midlands West Yorkshire
- 8. 11/26/2020 Bubble Chart 1/1 Bubble Chart: Comparing three different values So the idea about this is generally to have three independent variables, numeric. So let's have a different, a third value, for the size. For example, let's add Average Price in the Size. Note: Change the aggregation to Average. So now, we can see that the cumulative effect of all the house price inflation. But when we get around to 2007, this is when the house prices were at their maximum, and then they slightly declined. However, they were still fairly big even though there is some negative inflation, and even though sales values are down. We still have much lower house prices in 1996 compared to the peak of the negative house price inflation around 2009. SalesVolume, Sum of 12m% change and Average Price by RegionName and Year -200 -100 0 100 200 300 400 500 SalesVolume Sumof12m%change 10K 20K 30K 40K 50K 60K 2016 RegionName 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Greater Manchester Merseyside South Yorkshire Tyne and Wear West Midlands West Yorkshire
- 9. 11/26/2020 Dot Plot Chart 1/1 Dot Plot Chart: Adding a categorical field into X-Axis To create a dot plot chart, replace the numerical X-Axis field with a categorical field (es.Area Code) and remove Date from Play Axis Sum of 12m% change and Average Price by RegionName and AreaCode 1,520 1,540 1,560 1,580 1,600 1,620 1,640 1,660 1,680 AreaCode Sumof12m%change E11000001 E11000002 E11000003 E11000007 E11000005 E11000006 RegionName Greater Manchester Merseyside South Yorkshire Tyne and Wear West Midlands West Yorkshire
- 10. 11/26/2020 Format - Scatter Chart 1/1 Scatter Chart: Format - Change the shape for Mangester: Format + Shape + Customise Series ON - Add Category labels: Format + Category labels ON - Add Color Borders: Format + Color Borders ON Note: It is not possible at the moment to change the speed of Play button. Sales Volume, Sum of 12m% Change and Sales Volume by RegionName and Year -200 -100 0 100 200 300 400 500 Sales Volume Sumof12m%Change 10K 20K 30K 40K 50K 60K 2016 Greater Manchester West Midlands West YorkshireMerseyside South Yorkshire Tyne and Wear RegionName 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Greater Manchester Merseyside South Yorkshire Tyne and Wear West Midlands West Yorkshire