Distribution
Static

Histogram

Histograms visualize the distribution of continuous numerical data by dividing values into bins and displaying the frequency of observations in each bin. They reveal the shape of your data distribution—whether it's normal, skewed, bimodal, or uniform. Histograms are essential for exploratory data analysis and help identify outliers, central tendency, and spread.

Try this prompt

"Use seaborn to create a histogram of the 'Age' distribution with 20 bins and add a kernel density estimate (KDE) overlay. Generate a proper example dataset to demonstrate this visualization."
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Common Use Cases

  • 1Analyzing age demographics
  • 2Examining test score distributions
  • 3Quality control measurements
  • 4Financial return distributions

Pro Tips

Experiment with different bin sizes

Add KDE overlay for smooth distribution curve

Use logarithmic scales for highly skewed data