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BUILT AROUND YOUR WORK

Calculators and data tools for analysts

Prepare an export for analysis. Start with a sample with headers, identifiers, and missing values. Use the relevant tools below to clean the fields and compare distributions, then keep a reconciled dataset and method note alongside the source material.

USE WITH CONTEXT

Before you use these tools

Confirm source definitions, units, missing-value handling, and sample assumptions before presenting results. Keep the original data and document any transformations.

A PRACTICAL ROUTE THROUGH THE SHELF

From raw input to reviewed output

  1. 1

    Gather the inputs

    Bring a sample with headers, identifiers, and missing values. Record where the values came from and which assumptions are still uncertain.

  2. 2

    Prepare an export for analysis

    Choose a tool to clean the fields and compare distributions. Read its method and limits, then run a small example before working through the full scenario.

  3. 3

    Review the deliverable

    Keep a reconciled dataset and method note. Compare record counts and totals with the source before interpreting a chart.

Choose a focused workspace

Questions before you start

Where should data analysts start?

For this workflow, begin with a sample with headers, identifiers, and missing values. Choose the tool whose inputs match the task, rather than entering incomplete values into a broader calculator. The intended outcome is a reconciled dataset and method note.

What should I verify when I clean the fields and compare distributions?

Compare record counts and totals with the source before interpreting a chart. Confirm source definitions, units, missing-value handling, and sample assumptions before presenting results. Keep the original data and document any transformations.