# Guides

Tips and suggestions for working with and designing with data.

#### Why Line Chart Baselines Can Start at Non-Zero

There is a recurring argument that line chart baselines must start at zero, because anything else would be misleading. The critique is misguided.

Let's work through a practical example to see how asking and answering questions helps guide you towards more focused data graphics.

#### Visualizing Patterns on Repeat

Things have a way of repeating themselves, and it can be useful to highlight these patterns in data.

#### Why People Make Bad Charts (and What to Do When it Happens)

It's important to consider the reasons so that we don't overreact. Otherwise, we're just berating, pointing, and laughing all of the time, and that's not good for anyone.

#### Visualizing Differences

Focus on finding or displaying contrasting points, and some visual methods are more helpful than others. A guide.

#### Visualizing Outliers

Step 1: Figure out why the outlier exists in the first place. Step 2: Choose from these visualization options to show the outlier.

#### Visualizing Incomplete and Missing Data

We love complete and nicely formatted data. That's not what we get a lot of the time.

#### Visualizing the Uncertainty in Data

Data is an abstraction, and it's impossible to encapsulate everything it represents in real life. So there is uncertainty. Here are ways to visualize the uncertainty.

#### 4 Tools to Pick Your Chart Colors

These are the quick and simple tools I use to pick colors to represent data.

#### Falling is Learning

I’ve been teaching my three-year-old son how to ride his bike on two…

#### Useless Data Comparisons

Apples and oranges situations where the comparisons make no sense.

#### Summary Statistics Tell You Little About the Big Picture

Mean, median, and mode. These are the first things you learn about in…

#### How Histograms Work

The histogram is one of my favorite basic chart types, because it lets…

#### How to Spot Visualization Lies

Many charts don't tell the truth. This is a simple guide to spotting them.

#### One Dataset, Visualized 25 Ways

"Let the data speak" they say. But what happens when the data rambles on and on?