Creating Charts and Visualizations from CSV Data
Numbers in a table tell part of the story. A chart reveals patterns that columns of figures hide: a revenue dip in Q3, a spike in support tickets after a release, a long tail in order values. ExploreMyData includes a chart builder that creates bar charts, line charts, and more directly from your data, with no plugins and no export-to-another-tool step.
Getting started
Load a CSV (or any supported format: JSON, Parquet, Excel, XML). Once your data is in the table, click the chart icon in the toolbar to open the Chart Builder panel. The panel appears alongside your data so you can see both the table and the chart at the same time.
The chart builder needs two things from you: which column goes on the X axis and which goes on the Y axis. Everything else has sensible defaults that you can override.
Bar charts
Bar charts are the right choice when your X axis is categorical: product names, regions, departments, status codes. Pick the category column for X and a numeric column for Y, then choose an aggregation function.
Example: revenue by product category
Given this source data:
| order_id | category | revenue |
|---|---|---|
| 1001 | Electronics | 250 |
| 1002 | Clothing | 75 |
| 1003 | Electronics | 430 |
| 1004 | Home | 120 |
| 1005 | Clothing | 95 |
Set X to category, Y to revenue, and aggregation to SUM. The chart builder groups the rows by category and sums the revenue for each group, producing three bars:
| category | SUM(revenue) |
|---|---|
| Electronics | 680 |
| Clothing | 170 |
| Home | 120 |
Line charts
Line charts work best when the X axis is a date or time column. They show trends over a continuous dimension.
Example: monthly order count
If your data has an order_date column and you want to see how many orders were placed each month, set X to order_date, Y to any column (or use order_id), and aggregation to COUNT. The chart builder groups by month automatically when it detects a date column.
| month | COUNT(order_id) |
|---|---|
| 2025-10 | 312 |
| 2025-11 | 287 |
| 2025-12 | 445 |
| 2026-01 | 398 |
| 2026-02 | 361 |
| 2026-03 | 410 |
The line chart draws a point for each month and connects them, making the December spike and January correction immediately visible.
Secondary grouping
A single bar or line chart answers "how much per X." Adding a secondary grouping column answers "how much per X, broken down by Z."
Example: revenue by month, split by region
Set X to order_date, Y to revenue with SUM, and the secondary group to region. The result is one line per region, all on the same chart:
| month | North | South | West |
|---|---|---|---|
| 2026-01 | 18,400 | 12,100 | 9,800 |
| 2026-02 | 16,200 | 13,500 | 11,300 |
| 2026-03 | 21,000 | 14,200 | 10,600 |
Each region gets its own line. Diverging trends between regions become visible at a glance.
Aggregation options
The chart builder groups data automatically based on your X axis. You control how the Y values are combined within each group:
- SUM - total value per group. Revenue, quantity, cost.
- AVG - average value per group. Mean order value, average response time.
- COUNT - number of rows per group. Order count, ticket volume, event frequency.
- MIN / MAX - boundary values per group. Lowest price, highest score, earliest date.
Changing the aggregation updates the chart immediately. You can switch from SUM to AVG and back without reconfiguring anything else. This makes it fast to explore the same data from different angles.
Chart builder configuration summary
- X axis: category or date column
- Y axis: numeric column
- Aggregation: SUM, AVG, COUNT, MIN, MAX
- Secondary group (optional): splits bars or lines by a second column
The chart updates live as you change any setting. No need to click a separate "refresh" button.
For more complex aggregations or multi-step analysis before charting, see the grouping and aggregation guide. You can run pipeline transformations first, then chart the result.