Choosing the right chart is not a matter of taste — it is a matter of clarity. The wrong chart type can obscure meaning just as easily as the wrong data. Below is a plain-language overview of nine of the most widely used chart types, what each one does, and when it works best.

Pie Chart A pie chart shows how a few categories compare to one another and to the whole. It is common but limited — it works only when the number of categories is small and the differences between them are obvious enough to read visually.

Bar Chart A bar chart organises elements by size and is one of the most versatile tools available. Bars can be ordered or unordered depending on whether the categories have a natural sequence. It is a reliable default when comparing distinct groups.

Line Chart Line charts are best suited for showing how something changes over time. When multiple lines are used, they allow direct comparison of different categories across the same time intervals.

Scatterplot A scatterplot plots two separate measures against each other on independent axes, making it useful for exploring whether a relationship — or correlation — exists between them. It is often paired with a trendline to make that relationship easier to see.

Histogram A histogram takes a single continuous measure — such as age, price, or response time — and divides it into groups (called bins) to show how the values are distributed across a range. It is the standard tool for understanding distribution.

Bullet Graph A bullet graph builds on the familiar bar chart by adding reference lines or bands, creating a compact way to assess actual performance against a target or acceptable range. It is particularly useful in dashboards where space is limited.

Packed Bubble Chart A packed bubble chart uses the size of each circle as its primary means of comparison. Larger bubbles represent larger values, making it straightforward to compare categories at a glance — though it is less precise than a bar chart for small differences.

Box and Whisker Plot A box and whisker plot shows the full range of values for a dataset alongside the median and the interquartile range (the middle 50% of values). It is especially useful when you want to understand the spread and variability of data, not just the average.

Treemap A treemap breaks a whole down into its component parts, using the size of each rectangle to represent a quantitative measure. It is effective when showing proportions within a larger whole, particularly when there are many sub-categories.

Choosing the right chart begins with a simple question: what is the story you are trying to tell? Each of the types above is the right answer to a specific question — and the wrong answer to most others.

Source: https://www.tableau.com/chart 

Trifonas Mamas 

Property Valuer (MRICS–ΕΤΕΚ) 

Registered Estate Agent