Explain the following data visualisation techniques:

(a) Scatter Plot (b) Line Chart (c) Bar Graph (d) Heat Map (e) Timeline (f) Choropleth Map

(a) Scatter Plot — A scatter plot is a two-dimensional data visualisation that uses dots to represent the values for two different variables plotted against the horizontal and vertical axes. Each point implies the value for each observation. It is useful in illustrating relationships between variables and can be used to identify trends or correlations in data.

(b) Line Chart — A line chart is used to plot the relationship or dependence of one variable on another to display changes or trends. It is most often used to evaluate how data has changed over time and is ideal for visualising continuous data and identifying trends and fluctuations.

(c) Bar Graph — A bar graph is one of the most popular ways to visualise data using rectangular bars where each bar represents a category. The two types are Vertical Column chart (data with vertical bars) and Horizontal Column chart (data with flat horizontal bars). It is highly effective for comparing different categories and analysing data changes.

(d) Heat Map — A heat map is a data visualisation tool that uses colour gradients to represent value magnitudes within a matrix. Each cell is coloured based on its value, with different colours indicating various data ranges. Heat maps effectively display large, complex datasets, making patterns, correlations and anomalies easily identifiable.

(e) Timeline — A timeline is a graphical representation that shows events in chronological order along a linear scale. It can be horizontal or vertical and typically includes dates, labels and brief event descriptions. Timelines are effective for visualising historical developments, project schedules or process evolution.

(f) Choropleth Map — Choropleth maps are thematic maps that depict the geographic distribution of a specific subject across areas like countries, states or regions. They use colour shading to represent data values, with darker colours indicating higher values and lighter colours indicating lower values. Examples include India's map of Covid 19 spread.