I believe that visualization is one of the most powerful means of achieving personal goals
– Harvery Mackay
A fundamental part of the data scientist toolkit is data visualization. Although it is very easy to create visualizations, it’s much harder to produce good ones. There are two primary uses of data visualization:
- To explore data
- To communicate data
On this occasion, I will take the time to explain how we can assess whether a visualization is effective and meets its intended purpose, as well as highlight the key factors that indicate when a visualization fails to convey the message clearly or efficiently
BAR CHART
A bar chart is a good choice when you want to show how some quantity varies among some discrete set of items. For instance, From the bar chart as shown below we can conclude that C has the largest value when slammed with other values
LINE CHART
Line Chart, helps us understand patterns and changes in data visually. By using line charts, we can see changes in an easy-to-read graphical form allowing us to identify important trends and patterns.
SCATTERPLOTS
A scatterplot is the right choice for visualizing the relationship between two paired sets of data. For example, the image below is a visualization of a scatter plot.
Thats it, This is a brief explanation of how a graph is used for certain data needs. Thank you for reading!
If you enjoyed this post on How to Visualise Data 101, feel free to get in touch with me (Febrian Nur Alam) regarding any thoughts or queries!
Read More: Introduction to Natural Language Processing (NLP)