Hassan Ijaz
Ai, Web & Design
Data visualization and EDA
Dashboard builder where users drag different chart types and see how same data tells different stories
Concept Overview
Data visualization and exploratory data analysis (EDA) are essential first steps in any data analysis project. Good visualizations reveal patterns, outliers, and relationships that might be hidden in raw numbers.
Core Visualization Types
Histogram
Shows distribution shape, spread, and outliers
Best for: Single continuous variable
Scatter Plot
Reveals relationships between two variables
Best for: Bivariate continuous data
Box Plot
Shows quartiles, median, and outliers
Best for: Comparing distributions
Bar Chart
Compares categorical values
Best for: Categorical data counts
Line Plot
Shows trends over time or sequence
Best for: Time series data
Heatmap
Displays correlation or 2D density
Best for: Matrix data, correlations
EDA Process
- Check Data Quality - Missing values, duplicates, data types
- Univariate Analysis - Examine each variable individually
- Bivariate Analysis - Explore relationships between pairs
- Multivariate Analysis - Look at multiple variables together
Visual Encoding Principles
Effectiveness of visual channels (in order):
- Position along a scale
- Length/Distance
- Area
- Volume
- Color/Density
Use position for most important comparisons!
Common Pitfalls
- Starting y-axis above zero (misleading bar charts)
- Using 3D effects (distorts perception)
- Too many colors or categories
- Pie charts for many categories
- Ignoring aspect ratios
The Power of Multiple Views
The same data can tell different stories depending on visualization choice. Always try multiple chart types to gain different perspectives. What looks random in a table might show clear patterns in a scatter plot!
The dashboard builder below lets you drag different chart types onto the same dataset. See how different visualizations reveal different aspects of the data's story.
Interactive Visualization
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Dashboard builder where users drag different chart types and see how same data tells different stories