Data Pipeline Steps

Data Pipeline Steps allow you to perform a variety of post-query manipulations in Chartio. Steps can be added to the pipeline under any dataset to edit the results of that specific dataset’s query. Steps can also be added after merging datasets to manipulate the merged data.

Use Advance Mode to reorder your pipeline steps

Pipeline Steps
Columns Rows Transform
Add Column Sort Rows Pivot Data
Rename Columns Limit Rows Unpivot Data
Hide Columns Filter Rows Zero Fill Data
Reorder Columns   Group Rows
Combine Columns   Bucket Data
Edit Column   Extrapolate Data
Case Statement   Transpose

Add Column

Add a calculated column to your query results. Use one of our built-in functions, or choose Custom Formula in the Formula Type dropdown to create your own. See Formulas to view some examples of functions you can use.

Add addition columns to your dataset

Bucket Data

The Bucket Data pipeline step divides the values from one column into a series of ranges, and then counts how many values fall within each range. This data format can be used to create a histogram chart.

Histograms generally use COUNT as the Aggregation, but you may also choose MIN, MAX, SUM, or AVERAGE.

Define your buckets using any of the following options: Standard Deviation, Bucket Size (amount in each range), Number of Buckets, or Custom to choose custom ranges.

Aggregate your data with the bucket data pipeline step

Bucket Data Example

Click to view example

Case Statement

Case Statement Step

Add a column to your query results (or edit an existing column) where values are set based on certain “if… then” conditions.

Dashboard variables can be used in any part of a Case Statement pipeline step.

Note: If you find that you use the same CASE statement across multiple charts, you may want to consider putting the generated column data into a Data Store or a custom column in your database.

Else statements in case pipeline step

To pass through column values in THEN or ELSE, select Column from the dropdown and choose your column.

Case Statement Example

Case Statement Example

Combine Columns

Combine columns either by applying a mathematical operation or by concatenation. Check the Hide Combined Columns checkbox to hide your original columns.

Combining columns in the pipeline

Edit Column

Use this step to edit an existing column. All column types (text, date, number, etc.) allow entering a custom formula, and numerical columns have additional formula types including simple math operations and rounding.

Edit column pipeline step

Extrapolate Data

The Extrapolate Data step provides predictive data for a column in your query results. Choose whether to add data to the existing column or create a new one, the number of rows returned, and the type of extrapolation used (Cubic, Quadratic, or Linear).

Extrapolate Data Pipeline Step

Filter Rows

Filter rows on certain conditions. Choose Include or Exclude, then choose:

  • Matching all conditions
    Uses AND logic. Row will be included or excluded only if it matches every condition.
  • Matching any conditions
    Uses OR logic. Row will be included or excluded if it matches one or more conditions.

Regular Expression Matching

Any text column supports filtering by Java-style regular expressions in the Filter Rows Pipeline step. Matching is case-sensitive and unicode-aware by default. For case-insensitive matching, add (?i) to the beginning of your regular expression.

Filter rows in the pipeline

For examples of ways to use the Filter Rows Pipeline step, see our Filter Pipeline Step Example Scenarios article.

Group Rows

Group step works the same as GROUP BY in SQL. It allows you to group your query results based on a certain column. You’ll need to choose which column you want your chart to be grouped by, and which aggregation you would like for the other columns. Aggregation types include SUM, AVG, CONCATENATE (comma-separated list), COUNT, COUNT DISTINCT, MAX, and MIN.

Group rows together

Group Step Example

Group Step Example

Hide Columns

Hide one or more columns in your query results. If you need to use hidden columns in a Formula, hide the columns as the last step.

Hide Columns in the pipeline

Limit Rows

Limit the number of rows included in your query results. Can be useful when applied after a sort—for example, sort sales descending and limit 10 to include the top 10 sales. Offset allows you to select a specific range of rows. For example, to include only rows 10-30, set the limit to 20 and the offset to 10.

Limit rows in the pipeline

Pivot Data

If your chart has one measure grouped by two dimensions, such as count of activity grouped by month and by activity type, you’ll want to pivot the data so you can use it in a chart.

Pivot tables require 3 columns. Your data is pivoted on the second column—e.g., the second column becomes the column headers.

Pivot the data in the Pipeline to see the transformation

Select Ascending, Descending, or None in the Column sort direction dropdown to customize the column order in your pivot table. Aggregate Function allows you to choose the aggregation for duplicate group values. Available aggregations are: SUM, AVG, MIN, MAX, GROUP_CONCAT, and Auto. Auto will choose either SUM or GROUP_CONCAT, depending on the data type.

Pivot data in the pipeline step

For more information on how to use the Pivot Data Step, please see our tutorial on How to Pivot a Table.

To pivot on more than 3 columns, refer to Pivot on more than 3 columns.

Pivot Data Example

Pivot Data example in the pipeline

Rename Columns

Rename one or more columns. Useful for display purposes, or shortening column names for ease of use in formulas.

Rename columns in the pipeline

Reorder Columns

Easily click and drag your column names to reorder how they will appear in your chart. Note: It’s generally best to reorder columns in one of the last steps, as any editing that involves column changes will affect your reordering settings.

Reorder columns in the pipeline

Sort Rows

Apply a sort to one or more columns.

Sort rows in the pipeline


The Transpose step simply switches rows and columns.

There are no limits on the input table format, but the resulting table cannot contain more than 1000 columns.

Transpose data to convert rows to columns

Transpose Data Example

Transpose example in the pipeline

Unpivot Data

Unpivot data is useful when you have multiple single value columns that you want to use in a visualization, such as a pie, line, or bar chart.

If each layer returns a single value, choose Cross Join as your merge type.

Unpivot data to convert back

Unpivot Data Example

Unpivot example in the pipeline

Zero Fill Data

Zero fill fills in missing values in your data with zeros. It’s important when charting a time series with missing dates, or when performing calculations on columns that contain NULL values.

Note: Zero-fill will fill in all date and numeric columns in your query results.

Zero Fill Data

Zero Fill Example

Zero fill example in the pipeline