---
title: "Exploratory Analysis and an Honest Chart"
description: "Before modelling anything, look: distributions, outliers, relationships between pairs. Then the chart that reports it has to make the truth easy to read, which rules out a truncated axis, a misleading"
canonical: https://lightmysky.com/learn/computing/exploratory-analysis-and-an-honest-chart-mt_Jpb78Z6Ytu
source: https://lightmysky.com/learn/computing/exploratory-analysis-and-an-honest-chart-mt_Jpb78Z6Ytu.md
retrieved: 2026-09-12
---

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# Exploratory Analysis and an Honest Chart

Before modelling anything, look: distributions, outliers, relationships between pairs. Then the chart that reports it has to make the truth easy to read, which rules out a truncated axis, a misleading area, and a colour scale nobody can order.

Subject: Computing · Area: Data & Databases · Ages 21 to 22
Page: https://lightmysky.com/learn/computing/exploratory-analysis-and-an-honest-chart-mt_Jpb78Z6Ytu

## Ready when they can

- Choose the chart that suits a distribution, a comparison and a relationship
- Redraw a chart with a truncated axis and say what changed in the reader's impression
- Say what an outlier in an exploratory plot should prompt before it is removed

## Lesson: Look first, then chart it honestly

Before modelling anything, you look: shapes of distributions, strange points, and how pairs move together. A scatterplot comes before any correlation number, because numbers alone hide shape.

**Example.** You plot hours of practice against quiz score, one dot per student. The cloud slopes upward with one far dot. You check that student first instead of deleting the dot. If the check proves an error, like a broken sensor, you may remove it and write down why.

Match the chart to the job: a histogram or box plot for a distribution, a bar chart for a comparison, a scatter or line for a relationship over time. A pie shows one set as fractions of a whole. Correlation needs two numbers per item, like height and weight.

**Tip.** A truncated axis stretches small gaps into big drama, so start bars at zero. When you redraw it honestly, say what the first version made the reader believe.

**Recap.** Plot first, match the chart to the question, start bars at zero, and question outliers before you touch them.

## Practice

16 questions on this page, each with its working shown.

## Needs first

- [Cleaning Real Data: Missing, Duplicated and Wrong](https://lightmysky.com/learn/computing/cleaning-real-data-missing-duplicated-and-wrong-mt_qIsLXA-7EC)
- [Straightening Data with Logarithmic Graphs](https://lightmysky.com/learn/mathematics/straightening-data-with-logarithmic-graphs-mt_TVar2jxRMI)

## Opens up

- [Reading a Systems or Machine-Learning Paper](https://lightmysky.com/learn/computing/reading-a-systems-or-machine-learning-paper-mt_4LsuT0TdxT)
- [Reading a Paper: the Claim, the Evidence and the Assumption](https://lightmysky.com/learn/science/reading-a-paper-the-claim-the-evidence-and-the-assumption-mt_YFgMvbohC0)