Visualization for each data type

1. Categorical data

• Bar Chart:
  • Suitable for visualizing the distribution of categorical variables.
  • Nominal data: Each category is represented by a separate bar. (data that cannot be ordered)
  • Ordinal data: Bars are ordered based on the ranking. (data that can be ordered)
• Pie Chart:
  • Shows the proportion of each category within a whole.
• Countplot:
  • Specifically designed for counting the occurrences of each category.
• Heatmap:
  • Useful for visualizing relationships between two categorical variables.

2. Numerical data

2.1. Continuous data (measurement, higher precision)

• Histogram:
  • Provides a visual representation of the distribution of continuous data.
• Kernel Density Plot:
  • Estimates the probability density function of continuous data.
• Box Plot (Box-and-Whisker Plot):
  • Displays the distribution, central tendency, and spread of continuous data.
• Violin Plot:
  • Combines aspects of box plots and kernel density plots, useful for visualizing the distribution of continuous data.
• Scatter Plot:
  • Shows the relationship between two continuous variables.

2.2 Discrete data

• Bar Chart:
  • Suitable for visualizing the counts or frequencies of different discrete values.
• Dot Plot:
  • Shows individual data points along a number line.
• Histogram (for count data):
  • Similar to continuous histograms but used for discrete count data.
• Strip Plot:
  • Displays individual data points along a single axis.

3. Time series data