Histogram maker
Click to upload or drag and drop
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
- Upload data
Upload your data file in CSV or Excel format - Select variable
Choose the variable to analyze - Configure bins
Adjust bin width and range - 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
Graph makers
Bar graph
Compare values across categories. Perfect for showing differences between groups.
Column graph
Similar to bar graphs but with vertical bars. Great for comparing values.
Scatter plot
Show relationships between two variables. Identify correlations and patterns.
X-Y plot
Create X-Y plots to show correlations and trends between variables.
Line graph
Compare trends and patterns over a continuous range. Perfect for showing changes over time or sequences.
Time series graph
Visualize data over time. Perfect for temporal analysis and trend discovery.
Box plot
Visualize data distributions with quartiles and outliers. Perfect for understanding data spread and identifying anomalies.
Histogram
Show frequency distributions of numeric data. Great for understanding data patterns and distributions.
Pie chart
Display parts of a whole as proportions or percentages. Perfect for showing composition and relative sizes.
Donut chart
A variation of pie charts with a hollow center. Great for showing proportional data while leaving space for additional information.
Nightingale chart
A radial visualization that combines aspects of a pie chart and bar chart. Perfect for showing cyclic patterns and comparing proportions.
Radar chart
Compare multiple variables in a circular format. Perfect for multivariate data comparison and pattern analysis.
Heatmap
Visualize data patterns across two categorical dimensions with color intensity representing values.
Sankey diagram
Visualize flow between nodes, perfect for showing transfers or relationships between categories.
Stacked bar chart
Compare parts of a whole across categories or show composition changes over time.