Fold Multiple Columns
Infoveave Data Automation — Pivot & Transpose
Turn thirty columns of monthly data into clean rows — one label, one value, infinitely easier to chart and analyze.
Wide-format data — where each time period, metric, or response option is its own column — is common in spreadsheet exports, survey outputs, and legacy reports. But charting tools, machine learning models, and aggregation queries work best on long-format data where each observation is a row. Fold Multiple Columns reshapes your dataset from wide to long in one step, turning column names into values in a label column and their data into a values column — no manual pivot table manipulation required.
What Fold Multiple Columns does
Transform multiple columns into key-value row pairs in Infoveave workflows. Reshape wide-form survey, time-series, or metric data into long format for charting, ML, and normalization.
When to use Fold Multiple Columns
- You have monthly, quarterly, or yearly data spread across separate columns and need to stack it into a single date-value column pair for charting or aggregation
- You are working with survey data where each question is a column and you need each response as its own row for analysis
- You need to prepare wide-form data for a machine learning model that expects one observation per row
- You want to normalize a dataset where multiple columns represent the same measurement across different conditions
When to avoid it
- Your columns contain array values rather than scalar values — use Fold an Array to expand array-type columns
- You want to go from long format back to wide format — use Pivot Columns to reverse this operation
- You only need to expand one array column rather than reshape multiple separate columns — Fold an Array is simpler for that
Where it fits in your Infoveave automation
Fold Multiple Columns is one step inside a multi-step Infoveave workflow. Chain it with other activities — no code, no manual hand-offs.
Build this workflow visually in Infoveave Data Automation — drag, connect, and schedule with no infrastructure setup.
How teams use Fold Multiple Columns
Real scenarios where this transformation saves hours of manual work.
Reshape Monthly Production Columns for Time-Series Analysis
A manufacturing analytics team receives a production report where each month — Jan, Feb, Mar through Dec — is a separate column. Fold Multiple Columns reshapes the dataset into two columns: Month and Production Volume. The long-format output feeds directly into time-series visualization and trend analysis without any manual pivot table setup in Excel.
Normalize Survey Response Columns for Patient Outcome Analysis
A healthcare analytics team processes patient satisfaction surveys exported with each question — Q1, Q2, Q3 — as a separate column. Fold Multiple Columns converts the survey rows into a long format with Question and Response columns, enabling frequency analysis, filtering by specific questions, and dashboard breakdowns by question without reshaping the export manually each cycle.
Stack Regional Revenue Columns for Consolidated Reporting
A finance team receives a regional P&L report where each region — North America, EMEA, APAC, LATAM — is a separate column. Fold Multiple Columns stacks the regions into a single Region column alongside a Revenue column, enabling region-level filtering, comparison, and aggregation in the same workflow without maintaining separate region-specific report branches.
See Fold Multiple Columns in action
Input data (left) is transformed using the configuration below. The output table (right) is ready for dashboards or downstream steps.
Q1, Q2, Q3QuestionResponseInput Data
| ID | Name | Q1 | Q2 | Q3 |
|---|---|---|---|---|
| 1 | Alice | Yes | No | Yes |
| 2 | Bob | No | Yes | No |
Output Data
| ID | Name | Question | Response |
|---|---|---|---|
| 1 | Alice | Q1 | Yes |
| 1 | Alice | Q2 | No |
| 1 | Alice | Q3 | Yes |
| 2 | Bob | Q1 | No |
| 2 | Bob | Q2 | Yes |
| 2 | Bob | Q3 | No |
Configuration
Key fields to configure in the Infoveave workflow builder. Full reference available in the documentation.
Columns To Fold
List the columns to bring into long format. Each selected column produces one row per original row in the output, with the column name appearing as the label and the cell value appearing as the value. Columns not listed are kept as fixed identifier columns on every resulting row.
Folded Column and Values Column
Folded Column is the name of the new column that will hold the original column names as values — for example, Question or Month. Values Column is the name of the new column that will hold the actual data from each folded column — for example, Response or Revenue. Name these to match what the values represent so downstream steps and reports are self-explanatory.
UseRegex
When enabled, you can specify a regex pattern to match column names dynamically rather than listing them individually. This is useful when you have a large or variable number of columns following a naming pattern — for example all columns matching the pattern Month followed by a number — and you want to fold all of them without enumerating each one.
Frequently asked questions
Everything you need to know about Fold Multiple Columns in Infoveave.
Also in Pivot & Transpose — and what runs before & after
Transformations in the same family as Fold Multiple Columns, often chained together in the same Infoveave workflow.
Part of Infoveave Data Automation
80+ transformations. Zero manual steps.
Fold Multiple Columns is one of over 80 transformation activities available inside Infoveave workflows. Chain transformations together — no code, no exports, no waiting for IT.
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