Create publication-ready histograms from raw experimental measurements.
Upload values, describe the distribution you need, then generate a clean AI-made PNG with readable bins, axes, labels, and optional group overlays.
Upload data and describe the AI chart you need.
Costs 5 credits. Uses your uploaded data and prompt to generate a publication-ready PNG.
Preview
Aspect ratio: 16:9
These are sample previews. Upload your dataset to generate your own histogram.
Use these examples as visual directions for raw values, grouped overlays, thresholds, and manuscript-ready distribution figures.
Prompt
Based on the uploaded gene_expression_values.csv file, create a publication-ready histogram showing the distribution of normalized gene expression values. Use clean bins, a frequency y-axis, a subtle mean reference line, readable axis labels, and a restrained scientific color palette.
Prompt
Based on the uploaded treatment_response_groups.xlsx file, create overlaid histograms comparing response distributions for control, low-dose, and high-dose groups. Use transparent fills, shared bin widths, clear group labels, and a compact legend suitable for a manuscript figure.
Prompt
Based on the uploaded biomarker_thresholds.tsv file, create a histogram of biomarker scores with a vertical clinical cutoff line. Show sample counts, label the threshold clearly, use publication-ready typography, and keep the chart uncluttered.
Prompt
Based on the uploaded assay_signal_spread.csv file, create a histogram showing assay signal intensity across replicate wells. Use evenly spaced bins, mark the median and interquartile range, label outliers subtly, and use a clean lab-report style.
Prompt
Based on the uploaded model_residuals.csv file, create a histogram of residual values with a smooth density curve overlay. Center the x-axis around zero, include a dashed zero reference line, and use a simple statistical figure style.
Prompt
Based on the uploaded cell_size_measurements.xlsx file, create a histogram showing cell size frequency across measured cells. Use micron units on the x-axis, show sample size, choose readable binning, and produce a clean figure for a biology report.
Add CSV, TSV, TXT, or Excel data with at least one numeric measurement column.
Tell SciFigure AI the bins, labels, overlays, threshold lines, and palette you need.
Create a clean histogram, review the result, then download PNG for papers and slides.
It turns raw numeric measurements into a clean histogram for showing distribution shape, spread, skew, peaks, tails, and outliers. The result is designed for manuscripts, lab reports, posters, and research presentations.
A numeric measurement column is required. An optional group column can be used for overlays or separate panels.
Yes. Use a group column and ask for transparent overlays, shared bins, or separate small panels.
Yes. Describe the bin count, bin width, or binning rule in the prompt, then verify the result against your data.
Yes. Ask for a density-scaled histogram or a smooth density curve overlay when that better fits your figure.
Yes, but always verify the source data, binning rule, units, labels, and caption before submission.
Generate histograms, box plots, violin plots, and other research-ready visualizations with SciFigure AI.
