Group By Aggregations | Summarize Data with Precision, No Code Required

Groupings and aggregations are the foundation of any analytical workflow—yet most tools demand SQL fluency, complex CASE logic, or external modeling layers to get them right.

With Edilitics, grouping becomes a no-code, schema-aware experience. The Group By operation lets users aggregate metrics, count categories, and summarize behavior across any dimension—with full control over which aggregations to apply, and how they’re named.


Why Group By Matters

Without clean aggregation logic, organizations risk:

  • Inaccurate reporting due to mismatched groupings

  • Over- or under-counted metrics because of defaults or missing logic

  • Manual cleanup for grouped outputs before downstream use

  • Rigid dashboards that can’t pivot on demand

Edilitics simplifies this through:

  • ✅ Dynamic grouping by any non-nested column

  • ✅ Type-aware default aggregations for every column

  • ✅ Real-time previews and aggregation edits

  • ✅ Custom naming for all result columns


How to Group By Columns in Edilitics

  1. Choose your Group By field

    Select any categorical, datetime, or numeric column to group by. Columns with nested types (e.g., structs, lists) are auto-excluded.

  2. Review default aggregations

    • Numerical Columns → Default: Sum

    • Categorical & Datetime Columns → Default: Count

  3. Adjust aggregation logic

    For each non-grouped column, choose from type-specific aggregation options. Only valid methods appear based on column type.

  4. Edit output column names

    Edilitics auto-generates names like sum_SalesAmount or count_CustomerID. You can override these as long as they follow naming rules:

    • Alphanumeric + underscores only

    • Cannot start with numbers or underscores

  5. Drop or exclude fields (optional)

    Remove any non-grouped fields from the output.

  6. Add alternate aggregations (optional)

    Add the same field multiple times with different aggregations (e.g., mean_Amount, max_Amount, stddev_Amount).

  7. Submit and preview result

    Apply the transformation to generate a grouped, aggregated table.


Available Aggregation Methods

Data TypeAvailable Aggregations
Categorical / DatetimeCount, Count Distinct, Mode
NumericalSum, Count, Count Distinct, Min, Max, Mean, Median, Mode, Variance, Standard Deviation

Each operation is auto-mapped to its column type. You can mix and match aggregations across fields to build full-fidelity summaries.


Real-World Use Cases

IndustryGroup ByAggregationsUse Case
RetailProductCategorysum_SalesAmount, mean_SalesAmount, count_TransactionsUnderstand average and total sales by product line
HealthcareDepartmentcount_VisitID, count_distinct_PatientIDTrack visit frequency and patient diversity by department
FinanceAccountTypesum_TransactionAmount, max_TransactionAmount, mean_BalanceAnalyze spend behavior across different account types
ManufacturingFactorysum_ProductionUnits, min_ProductionUnits, max_ProductionUnitsCompare total and peak output by facility
EducationClassmean_Score, stddev_Score, count_StudentIDEvaluate academic performance and distribution within each class

Manual Equivalent – SQL & Pandas Examples

SQL Example – Redshift


SELECT
ProductCategory,
SUM(SalesAmount) AS sum_SalesAmount,
COUNT(*) AS count_Transactions,
AVG(SalesAmount) AS mean_SalesAmount
FROM sales_data
GROUP BY ProductCategory;

Pandas Example


grouped = df.groupby('ProductCategory').agg({
'SalesAmount': ['sum', 'mean'],
'TransactionID': 'count'
})
grouped.columns = ['sum_SalesAmount', 'mean_SalesAmount', 'count_Transactions']

In Edilitics, all of this is handled via dropdowns—aggregation logic, column naming, and schema validation built-in.


Governed, Flexible, and Deeply Customizable

The Group By operation in Edilitics is:

  • Schema-aware – No unsupported column types

  • Auto-defaulted – Logical defaults for all columns

  • Customizable – Full aggregation control + naming flexibility

  • Previewable – See before you commit


Whether you’re building KPI dashboards, comparing categories, or analyzing performance distributions, Edilitics makes it easy to group, summarize, and analyze—without code, without confusion, and without compromising governance.


Next: Chain Your Insights

After grouping, you’re ready to drive deeper insights by chaining with:

Enterprise Support & Technical Assistance

For technical inquiries, implementation support, or enterprise-level assistance, our dedicated technical support team is available to ensure optimal deployment and utilization of Edilitics solutions. Please contact our enterprise support desk at support@edilitics.com. Our team of specialists will respond promptly to address your requirements.

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