> ## Documentation Index
> Fetch the complete documentation index at: https://parabola.io/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# How do I do advanced math calculations (like logarithms) and statistical analysis?

> The best way to handle these more complex operations is by using the **Custom Transform** step, which gives you the flexibility to perform nearly any calculation by describing what you want the system to do.

### Step-by-Step:

<Steps>
  <Step>
    Add a **Custom Transform** step to your canvas from the sidebar.
  </Step>

  <Step>
    Connect your data
  </Step>

  <Step>
    Open the **Custom Transform** step, and in the instructions box, explain your desired calculation in plain language.
  </Step>

  <Step>
    Once you've written out the transformation you want, click *Update Results* and the step will output your updated dataset with the new calculations included.
  </Step>
</Steps>

### Example 1: Logarithmic Transformation

If you want to create a new column that shows the logarithm of the 'Sales Volume' column, you could write:

"Create a new column that contains the base 10 logarithm of the Sales Volume column."

This is helpful when you want to compress the range of large values, or when you're prepping data for more advanced modeling.

## **Example 2: Calculate Standard Deviation**

If you want to understand how spread out your 'Lead Time' values are, you could write:

"Create a new column that shows how far each row's Lead Time is from the average (i.e., the z-score)."

This is useful for identifying unusually fast or delayed shipments compared to the norm.

## **Example 3: Normalize a Value**

To scale values to better compare them, you might say:

"Add a column that shows the normalized value of Unit Cost between 0 and 1."

This helps when you're blending data from different sources with different scales.