Visualisation

What is Data Visualisation?

Data visualisation is an important concept of any data related science, as it offers an accessible graphical representation of the data, and as such can create a better understanding of trends and hidden patterns.

There are many visualisation tools (graphs, charts, histograms, etc.), with each one suitable for different scenarios.
Note: the data of the visualisation tools within the content of this page is NOT actual (real) data.

Frequency table

A frequency table is used to organise and analyse data. Frequency values show how many times datapoints appear in the dataset.

Use cases (examples of frequency tables):
1. Number of people in a region, separated by blood type.
2. Number of students in every university campus.

Bar Chart (bar graph/bar diagram)

Bar charts present the distribution of categorical data. A bar in a bar graph shows the frequency of the specific category it represents – bars can be vertical or horizontal.

Use cases (examples of bar charts):
1. Number of people that have won Nobel prizes in each scientific subject.
2. Album sales by music genre.

Pie Charts (pie graph)

Pie charts show the distribution of categorical data. A pie chart is a circular graph, divided into slices, with each slice representing the proportion of the category of the overall dataset.

Use cases (examples of pie charts):
1. Time spent (by activities) on smartphones.
2. Company spending of every department for a particular month.

Histogram

Histograms visually describe the distribution of numerical data (as opposed to categorical data in bar charts). The bars in histograms are called bins (also intervals or buckets).

Use cases (examples of histograms):
1. Number of properties sold, grouped on multiple categories.
2. Groups of people (measured by age) enrolled in a university.

Boxplot (box plot/whiskers chart)

Boxplots show the distribution of numerical data, with the addition of several important statistical features. Features: minimum value and maximum value, first and third quartile as well as interquartile range, median, and any outliers.