There are several types of data visualization techniques used in analysis. Some common types include:

  1. Bar Charts: Bar charts are used to compare different categories or groups. They use rectangular bars with lengths proportional to the values being represented.

  2. Line Charts: Line charts are used to show trends over time. They connect data points with straight lines, allowing for easy visualization of changes and patterns.

  3. Pie Charts: Pie charts are used to represent proportions and percentages. They divide a circle into sectors, with each sector representing a different category.

  4. Scatter Plots: Scatter plots are used to show the relationship between two variables. They plot points on a graph, with one variable on the x-axis and the other on the y-axis.

  5. Heatmaps: Heatmaps are used to visualize values in a two-dimensional matrix. They use colors to represent the intensities of the values, allowing for easy identification of patterns and outliers.

  6. Tree Maps: Tree maps are used to display hierarchical data. They use nested rectangles to represent each level of the hierarchy, with the size of the rectangles indicating the magnitude of the values.

  7. Histograms: Histograms are used to visualize the distribution of a single variable. They group data into bins and display the frequencies or proportions of the values within each bin.

  8. Bubble Charts: Bubble charts are used to display three dimensions of data. They use bubbles of different sizes and colors to represent values for the x-axis, y-axis, and a third variable.

  9. Geographic Maps: Geographic maps are used to visualize data with a geographical component. They can show data on a global, regional, or local scale, allowing for spatial analysis and pattern recognition.

  These are just a few examples of data visualization techniques that are commonly used in analysis. The choice of technique depends on the nature of the data and the goals of the analysis.