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12. Data Hierarchies and Groups

12.5 Data Groups (List Groups)

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Start with a problem

Shraddha's category head wants Fresh versus Packaged, but the data has only Dairy, Snacks and Fruits.

Explain simply

A list group puts several values of a column into one bucket, without code. It creates a new field, Category (groups).

Show the data

Category Total Sales (₹) Share
Dairy 1,050 50.0%
Snacks 650 31.0%
Fruits 400 19.0%
Total 2,100 100%

About this data: This table uses columns: Category, Total Sales (₹), Share. This table uses columns: Category (groups), Total Sales (₹). This table uses columns: City, Sales (₹). This table uses columns: Region, Sales (₹). Values shown are the lesson examples already on this page (not a new dataset).

Fictional sample data. Practice file: visuals_orders_apr_may_2026.csv (source: src/practice/).

Demonstrate

  1. Data pane › right-click Orders[Category] › New group.

  2. Ctrl-click Dairy and Fruits › Group › rename the group Fresh.

    Your result should look like this:

    Groups and members
    Fresh: Dairy, Fruits

  3. Select Snacks › Group › rename Packaged. Leave Include Other group ticked for future categories.

    Your result should look like this:

    Groups and members
    Fresh: Dairy, Fruits · Packaged: Snacks

  4. OK › a new field Category (groups) appears.

  5. Bar chart: Category (groups) + Total Sales.

Show the result

Your result should look like this (fictional sample):

Category (groups) Total Sales (₹)
Fresh 1,450
Packaged 650
Total 2,100

Explain what happened

Power BI created a calculated grouping column that maps each category to its bucket. Fresh = ₹1,050 + ₹400 = ₹1,450.

Explore further

  • For many values or rules that change often, a mapping table is easier to maintain than a group.

Detailed reference for this lesson:

Groups in Power BI with example — in 30 seconds

What: A group puts several values of a column into one bucket.

Why: The state head wants a Region view (West, Vidarbha), but the data only has City.

Tiny example: Pune + Mumbai = West. Nagpur = Vidarbha.

First look at the data (before, then after):

Groups in Power BI with example: before and after tables, fictional Blinkit Maharashtra data

Same before / after tables as text

Before — Sales by City

City Sales (₹)
Pune 1,000
Mumbai 1,100
Nagpur 600

Formula / click path

Data pane › right-click City › New group
West = Pune, Mumbai · Vidarbha = Nagpur

After — Sales by City (groups)

Region Sales (₹)
West 2,100
Vidarbha 600

Do it step by step:

  1. In the Data pane, right-click City › New group.
  2. Ctrl + click Pune and Mumbai. Click Group. Rename it West.
  3. Select Nagpur. Group it as Vidarbha.
  4. Click OK. Put City (groups) in a bar chart.

A group combines several values of a column into a new category without writing DAX. Our trainer wants to show orders by Maharashtra region:

Region (group) Cities (members)
West Pune, Mumbai
Vidarbha Nagpur
North Maharashtra Nashik
Marathwada Sambhaji Nagar
South Maharashtra Kolhapur

(These labels are the grouping chosen for our practice reports.)

Steps in Power BI

  1. In the Data pane, right-click DarkStore › City › New group.
  2. The Groups dialog opens: Name Region, Field City, Group type List.
  3. In Ungrouped values, Ctrl + click Pune and Mumbai › click Group. A group appears on the right under Groups and members. Double-click its name and type West.
  4. Repeat: Nagpur → Vidarbha; Nashik → North Maharashtra; Sambhaji Nagar → Marathwada; Kolhapur → South Maharashtra.
  5. Tick Include Other group if you want every value that is not in a group (for example a future city) to fall into Other.
  6. OK. A new field Region with a group icon (paperclip-style) appears in DarkStore. Use it like a normal column in visuals, slicers and filters.
  7. Shortcut from a visual: in a bar chart of Orders by City, Ctrl + click the Pune and Mumbai bars › right-click › Group data. Power BI creates the group, and you can then rename it.

Edit or remove a group: right-click the Region field › Edit groups (add/remove members, rename, Ungroup). Delete the field to remove the grouping entirely.

Try this example yourself with Maharashtra's regions – West, Vidarbha, North Maharashtra, Marathwada and South Maharashtra.

Ravindra Bagale's Tip

Remember one thing: forgetting Include Other group is the mistake I see most. New cities then show as their own names instead of a region, which confuses totals. Also clean spelling variants before grouping (Pune/pune). If the logic is long or changes often, use a mapping table in Power Query instead of a group. Keep this in mind!

Fix common mistakes

Wrong result Reason Correction
A new category Bakery shows as Other Group membership is fixed Edit the group
Fruits missing from Fresh after a rename to Fruit Membership matches exact values Add the renamed value to the group
Users cannot see which value is in which group Rules hidden in a dialog Document them, or use a mapping table

Practise independently

Practice task

Group Pune and Nashik as Big cities and Kolhapur as Other. What are the totals?

Hints
  • City totals: Pune ₹850, Nashik ₹800, Kolhapur ₹450.
Solution

Big cities ₹1,650; Other ₹450.

Think like a professional

Groups are perfect for quick, stable buckets. When the business keeps changing the rules, move them to a mapping table they can edit.

Loading DAX practice tasks...

  1. Region of each plant (Easy): Calculated column on Plants: Region = "Asia" when Country is "India", else "Europe".
  2. Shift code (Easy): Calculated column on Batches: Shift Code = "D" for the Day shift, else "N".
  3. Plant country on each batch (Easy): Calculated column on Batches: Country = the Country of the plant.
  4. Part family (Medium): Calculated column on Batches: Family = "Brakes" for Brake Disc, "Transmission" for Clutch Plate and Gear Shaft, else "Engine".
  5. Home or away (Medium): Calculated column on Plants: Group = "Home" for India, "DACH" for Germany, else "Other".
  6. Transmission units (Medium): Measure: Transmission Units = [Units Made] for Part in Clutch Plate and Gear Shaft.
  7. European units per part (Medium): Shown per Part. Measure: Europe Units = [Units Made] for Country in Germany and France.
  8. German share per part (Hard): Shown per Part. Measure: Germany Share = units in Germany ÷ [Units Made].
  9. Everything except pistons (Hard): Shown per Plant. Measure: Non Piston Units = [Units Made] for every part except Piston.
  10. Rejects in German night shifts (Hard): Shown per Part. Measure: DE Night Rejects = SUM of UnitsRejected for Germany and the Night shift.

See all Power BI practice tasks

Ravi Sir's Cards for this lesson

Data groups: list groups. Business areas like regions are not always in the data.Revision card

मराठी cards