Histogram maker

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Accepts csv, parquet, tsv and json

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Create histograms online

Create informative histograms to visualize data distributions. Perfect for analyzing data patterns and statistical distributions.

Upload your data and create histograms instantly

Visualize data distributions

Interactive bin controls

Multiple distribution types

Statistical overlay options

Free to use, no account required

How to create a histogram

  1. Upload data
    Upload your data file in CSV or Excel format
  2. Select variable
    Choose the variable to analyze
  3. Configure bins
    Adjust bin width and range
  4. Export
    Download your histogram as a high-quality image

Histogram examples

Normal distribution

Histograms are perfect for visualizing normal (Gaussian) distributions, showing the classic bell curve shape.

Key features:

  • Bell curve visualization
  • Automatic bin sizing
  • Frequency counts
  • Interactive tooltips

Right-skewed distribution

A right-skewed (or positively skewed) distribution has a longer tail on the right side, common in data like salaries or prices.

Key features:

  • Longer right tail
  • Mode less than mean
  • Common in financial data
  • Positive skewness

Left-skewed distribution

A left-skewed (or negatively skewed) distribution has a longer tail on the left side, often seen in age-related or bounded data.

Key features:

  • Longer left tail
  • Mode greater than mean
  • Common in age distributions
  • Negative skewness

Log-normal distribution

A log-normal distribution appears when the logarithm of the variable follows a normal distribution, common in natural and economic phenomena.

Key features:

  • Always positive values
  • Heavy right tail
  • Common in biological and financial data
  • Multiplicative processes

Uniform distribution

Visualize uniform distributions where all values are equally likely to occur.

Key features:

  • Uniform distribution
  • Equal bin heights
  • Range visualization
  • Frequency analysis

Bimodal distribution

Show data with two distinct peaks, common in mixed populations or processes.

Key features:

  • Dual peak visualization
  • Mixed distribution analysis
  • Population separation
  • Density estimation

Multi-modal distribution (Trimodal)

A trimodal distribution shows three distinct peaks, common in mixed populations with three subgroups or processes with three stable states.

Key features:

  • Three distinct peaks
  • Mixed population analysis
  • Subgroup identification
  • Process state analysis

Chi-square distribution

The chi-square distribution is fundamental in statistical hypothesis testing and modeling variability in positive-valued data.

Key features:

  • Always positive values
  • Right-skewed shape
  • Used in variance analysis
  • Degrees of freedom parameter

Student's t-distribution

The t-distribution is crucial for statistical inference with small sample sizes and unknown population variance.

Key features:

  • Bell-shaped but heavier tails
  • Symmetric around mean
  • Used in small sample inference
  • Approaches normal as df increases

Discrete data histogram

A histogram for discrete data shows the frequency of distinct values, common in count data or categorical measurements.

Key features:

  • Integer-valued data
  • Poisson-like distribution
  • Count data analysis
  • Discrete probability

Distribution comparison

Compare two distributions side by side to analyze differences in shape, center, and spread.

Key features:

  • Side-by-side comparison
  • Shape differences
  • Location comparison
  • Spread analysis

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Compare values across categories. Perfect for showing differences between groups.

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Column graph

Similar to bar graphs but with vertical bars. Great for comparing values.

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Scatter plot

Show relationships between two variables. Identify correlations and patterns.

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X-Y plot

Create X-Y plots to show correlations and trends between variables.

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Line graph

Compare trends and patterns over a continuous range. Perfect for showing changes over time or sequences.

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Time series graph

Visualize data over time. Perfect for temporal analysis and trend discovery.

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Box plot

Visualize data distributions with quartiles and outliers. Perfect for understanding data spread and identifying anomalies.

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Histogram

Show frequency distributions of numeric data. Great for understanding data patterns and distributions.

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Pie chart

Display parts of a whole as proportions or percentages. Perfect for showing composition and relative sizes.

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Donut chart

A variation of pie charts with a hollow center. Great for showing proportional data while leaving space for additional information.

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Nightingale chart

A radial visualization that combines aspects of a pie chart and bar chart. Perfect for showing cyclic patterns and comparing proportions.

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Radar chart

Compare multiple variables in a circular format. Perfect for multivariate data comparison and pattern analysis.

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Heatmap

Visualize data patterns across two categorical dimensions with color intensity representing values.

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Sankey diagram

Visualize flow between nodes, perfect for showing transfers or relationships between categories.

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Stacked bar chart

Compare parts of a whole across categories or show composition changes over time.

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