In this course, you will learn :
- Understand why visualisation is crucial in data analysis practise, as well as the differences between exploratory and explanatory analysis and the function of data visualisation in each.
- Interpret features in terms of measurement level and be familiar with the various encodings that can be used to portray data in visualisations.
- To represent categorical variable distributions, use bar charts.
- Scatterplots can be used to demonstrate correlations between numerical variables.
- Encodings like as size, shape, and colour can be used to encode values of a third variable in a visualisation.
- Learn what it means to create a captivating tale with data and how to select the right plot type, encodings, and annotations to polish your plots.
- Apply your knowledge of data visualization to a dataset involving the characteristics of diamonds and their prices.
- Data Visualization in Data Analysis
- Design of Visualizations
- Univariate Exploration of Data
- Bivariate Exploration of Data
- Multivariate Exploration of Data
- Explanatory Visualizations
- Visualization Case Study