Documentation
Everything you need to know to get the most out of Plotara.
From spreadsheet to publication figure
Plotara is a desktop app for scientists and students who need real, defensible figures and statistics — without writing code, and without fighting a hundred formatting menus.
Load your data, pick a chart, and you have a publication-ready plot. Everything after that — styling, statistics, multi-panel figures — is optional refinement.
The three workspaces
Plotara is organised into three tabs across the top. You can move between them freely — your data, plot and results stay loaded.
Data
Load, inspect and edit your dataset. Multiple sheets, a full spreadsheet editor, and automatic detection of what each column contains.
Plotting
Choose a chart type, map your variables, and style the figure. This is where you spend most of your time.
Statistics
Run any of 50+ statistical tests on the same dataset, and send the results straight back onto your plot as significance bars.
Your first plot in five steps
- 1Load your data. Drag in a spreadsheet, paste straight from the clipboard, or type into the built-in editor.
- 2Pick a graph type. Twenty-two chart types, from scatter and bar through to survival curves and Venn diagrams.
- 3Choose your variables. Plotara detects which columns are numeric, categorical or dates, and only offers the sensible ones.
- 4Refine the look. Adjust with the style controls, add Extras, or apply a journal style in one click.
- 5Hit Generate Plot. Export as PNG at 300 DPI, or as vector SVG or PDF.
Pro Tip: The defaults are chosen to be scientifically appropriate for the data you loaded — a diverging colour scale for correlations, a sequential one for magnitudes. You can get a clean, valid figure without touching a single option.
Runs on your machine
Plotara ships with its own Python engine — matplotlib, seaborn, pandas, NumPy and SciPy. Your figures are genuine matplotlib output, not a web preview, and your analysis runs locally on your computer.
That also means every plot and every test has real, runnable Python behind it, which you can view, edit and export at any point. See the Code Editor tab.
Get your data in, however it comes
Real research data is messy — wide-format spreadsheets, several sheets per file, MATLAB exports, a table copied out of a colleague's email. Plotara takes all of it.
Loading data
Drag a file onto the upload area, browse for it, or paste from your clipboard.
Supported formats
MATLAB .mat files up to 50 MB.
Paste from clipboard
Copy a block of cells out of Excel, Numbers or Google Sheets and click Paste data from clipboard. Tab- and semicolon-separated data is handled automatically.
Multi-sheet workbooks
Every sheet in an Excel workbook is loaded. Switch between them, or batch-plot across several sheets at once.
Sample dataset
No data to hand? Load the built-in example dataset to explore the app.
The built-in data editor
You don't have to go back to Excel to fix a typo. The Data tab is a working spreadsheet editor.
Edit in place
Type into any cell and navigate with the arrow keys, Tab and Enter, just like a spreadsheet. Click a column header to rename it, or double-click a sheet tab to rename the sheet.
Add, clear and manage sheets
Build a dataset from scratch, add extra sheets, or clear one and start again.
Export your cleaned data
Save the current sheet as CSV, or the whole workbook as an Excel file — so your tidied dataset lives on outside Plotara.
Keep it for later
Save Dataset for Editing stores the dataset in your gallery so you can pick the work back up in a later session.
Wide, long and everything between
Plotara handles your data however you organized it, no need for tedious re-formatting from wide to long format. The stats and plots can handle both!
Group, colour and facet columns
Pick a column to split your data by, a column to colour by, and a column to split into small multiples — each independently.
Aggregation and error bars
Collapse repeated measurements with mean, median or sum, and show the spread as standard deviation, standard error, or a 95% confidence interval.
Category order and colours
Drag your categories into the order you want them plotted, and override the colour of any individual category — so "Control" is always first and always grey.
Instant, publication-ready plots
You shouldn't have to be a data scientist to visualise your results like one. Plotara's plotting interface is entirely UI-based — every control maps to real matplotlib and seaborn output underneath.
Whether you're rushing to a lab meeting or finalising a manuscript, the defaults produce a figure that will impress.
Twenty-two chart types
The main grid holds the charts you reach for every day. Specialist plots live one click away under More, so the everyday choices stay uncluttered.
Everyday
Specialist
Options tailored to the chart
Every dataset has different needs. Rather than showing you every option that exists, Plotara shows only the ones that apply to the chart you've chosen.
Scatter & Bubble
Trendlines (linear, polynomial, exponential) with confidence bands, point size and opacity to manage overplotting, marker shapes, and colour or size driven by a third column.
Bar
Grouped or stacked, vertical or horizontal, custom bar width, error bars, value labels, per-category colours, and fill textures for greyscale-safe printing.
Box & Violin
Overlay the raw points with jitter, notched boxes, quartile or inner marks, whisker range and caps, and paired lines connecting matched subjects across conditions.
Heatmap
Correlation or raw-value mode, Pearson / Spearman / Kendall, row and column clustering, annotation of cell values, and colour scales appropriate to the data — diverging for correlations, sequential for magnitudes.
Survival
Kaplan–Meier curves with censoring marks, 95% confidence bands, median survival line and a numbers-at-risk table.
Forest
Choose your effect measure — odds ratio, risk ratio, hazard ratio, mean difference or standardised mean difference — with confidence intervals and a summary diamond.
3D & Surface
Elevation and rotation angles, interpolation method, grid resolution, and a contour projection on the floor.
Styling and journal presets
Full control over the parts of a figure that reviewers actually notice: axis labels and limits, custom tick labels, fonts and font sizes, legend position and title, gridlines, frame style, tick marks, figure dimensions and transparency. Charts with two Y scales get an independent right-hand axis with its own label and limits.
Colour palettes
One-click journal styles
Pick your target journal and Plotara sets the font sizes, gridlines, colour palette and column width to that journal's figure guidelines.
Pro Tip: Apply a journal style last. It only touches typography and palette, so all your data choices stay exactly as you set them.
Extras: add-ons on demand
Extras keep the main panel clean. Open the catalogue, search for what you need, and it is added to your plot with its own small set of options. Only extras compatible with your current chart are offered.
Regions & guide lines
Shade a stimulus window or a normal range, or draw the y = x identity line. (Threshold lines at a fixed value live under Annotations.)
Curve fits
Overlay a linear, polynomial or exponential fit with its equation, R² and 95% confidence band — or bring across the nonlinear curve you fitted in the Statistics tab.
Statistical overlays
Mean and median lines, mean ± SD bands, percentile bands, outlier highlighting, and an automatic n = label.
Axes & presentation
Log scales on X, Y or the secondary Y axis, and transparent backgrounds for slides and posters. Line widths, marker shapes and point sizes stay in the main panel.
Chart-specific
95% confidence ellipses on scatter plots, significance masking on correlation heatmaps, at-risk tables on survival curves, and paired or connected points on box and violin plots.
Annotations
Mark up the figure directly, without leaving the app.
Significance bars
Place brackets between groups with stars or a custom label, and control height, style and colour.
Text annotations
Add free text anywhere on the figure at your chosen position, size and colour.
Reference lines
Horizontal or vertical lines at any value, with an optional label.
Pro Tip: Run a post-hoc test in the Statistics tab and Plotara offers to turn the significant comparisons into significance bars automatically — correctly positioned, with the right number of stars.
Batch mode: automate your workflow
Why generate one plot at a time when you can generate them all? Batch mode is built for high-throughput research.
Batch by group
Select a grouping column — ten proteins, five study sites — and Plotara generates a separate, identically formatted figure for every category.
Batch by column or sheet
Or sweep across a set of X columns, Y columns, or every sheet in your workbook.
Review and export together
Page through the results, download the whole set at once, or save them into a gallery folder.
Pro Tip: Combine batch mode with a saved preset to produce a full suite of standardised supplementary figures in under a minute.
Exporting
Export the current figure in whichever format your target needs.
PNG — 300 DPI
High-resolution raster, ready for most journal submissions and slide decks.
SVG — vector
Fully editable in Illustrator or Inkscape if you need one last manual tweak.
PDF — vector
Scales without loss, and drops straight into LaTeX manuscripts.
Statistics made intuitive
Scientific discovery isn't just about showing your data — it's about proving its significance. The Statistics panel is a full suite, from a two-group comparison through to mixed-effects models and multivariate analysis.
It reads the dataset you already loaded, so there's nothing to re-import and nothing to keep in sync.
Not sure which test? Let Plotara ask.
Click Help me choose and answer a few plain-English questions — what you're trying to find out, how many groups you have, whether the same subjects were measured more than once, whether the data looks normal.
Plotara then recommends the right tests, each with a one-line reason for why it fits your design — and flags the assumption checks you should run first.
Pro Tip: Answer "Not sure — I want to check first" on the normality question and Plotara points you straight at Shapiro-Wilk and Levene's before you commit to a test.
Over fifty tests, in twelve categories
T-Tests
ANOVA
Correlation
Nonparametric
Categorical
Linear Models
Mixed Models
Multivariate
Diagnostics
Curve Fitting
Power Analysis
Survival
Guidance at your fingertips
Statistics can be daunting, so the expertise is embedded in the workflow. Every test has an Info tab that acts as an on-demand methodology consultant.
What it does
Exactly what the test compares, and when you should reach for it.
Assumption checks
The requirements — normality, independence, homogeneity of variance, sphericity — and what to do when one is violated.
Example usage
A real research scenario, so you can confirm you've picked the right tool before you run it.
Run it across every group at once
Most tests support a group-by: select one or more columns and Plotara runs the same analysis separately within each group, then lays the results out side by side.
Stratified analysis
Run your correlation within each treatment arm, or your t-test within each sex × timepoint combination, in a single click.
Between-group comparison
Plotara also tests whether the effect itself differs between groups — for example, Fisher r-to-z on correlations across arms.
Multiple-comparison correction
Correct the family of p-values with Holm, Bonferroni, or Benjamini-Hochberg FDR, with a clear summary of how many comparisons survived.
Several tests in one run
Queue up multiple comparisons and run them together rather than one at a time — either as pairs of columns, or, with long-format data, as pairs of groups from a single grouping column (Control vs A, Control vs B, …).
Results you can actually read
Plotara doesn't just hand you a p-value. Alongside the full statistical output you get effect sizes, confidence intervals, post-hoc comparisons (Tukey HSD, Dunn's, or pairwise with your chosen correction) and a plain-English interpretation of what the result means.
Celebrating discovery
When your result reaches significance (p < 0.05), the screen lights up with a short flash of fireworks. A small reward for the hard work that goes into research.
From analysis to action
Once the test is done, fold the result back into your workflow:
Annotate your figure
Send significant post-hoc comparisons straight to the plot as significance bars, already positioned and starred.
Save the results
Log the full output to your gallery, or download it as a text file for your lab notebook.
Export the code
Every test generates the Python that produced it, so your analysis is reproducible line for line.
The stats engine
What Plotara runs under the hood, and how we keep it honest.
Powered by the scientific Python stack
Plotara is powered by Python. Behind the interface sits a full scientific Python stack — SciPy, statsmodels, lifelines and scikit-learn — the same open-source libraries used in published research across every field. Plotara doesn't reimplement the maths; it gives you a clean way to drive it, without writing the code yourself.
Pinned, not floating
The Python environment ships inside the app at exact versions (SciPy 1.17.1, statsmodels 0.14.6, NumPy 2.4.6, pandas 2.3.3, lifelines 0.30.3, scikit-learn 1.9.0). Nothing is downloaded at runtime and nothing drifts between updates, so the Windows build and the Mac build of a given Plotara version compute identical numbers — as does the same version a year from now.
Conventions matched to R
Where a test has more than one defensible convention, Plotara follows the one used by R and SPSS, so results line up with what reviewers and collaborators expect:
Mann–Whitney
Uses the exact distribution when the data allow it and the normal approximation when they don't — the same rule as R's wilcox.test, rather than a library default that switches over at a much smaller sample.
Factorial ANOVA
Reports Type II sums of squares.
Repeated-measures designs
Use listwise deletion of incomplete subjects and compute the Greenhouse–Geisser correction separately for each effect.
Confidence intervals, effect sizes and post-hoc corrections
Follow the standard definitions for each test, not a single blanket approach.
Cross-checked against R
Agreement with R is part of how Plotara is built, not an afterthought. The statistics engine is run against an independent implementation of every test written in R 4.6.1 (base stats plus MASS, nlme, survival, pwr, mvtnorm and geepack) on identical data.
Every one of those 4,817 values — test statistics, p-values, degrees of freedom, effect sizes, confidence intervals, regression coefficients, survival estimates and post-hoc p-values — agrees with R to the precision Plotara displays.
The sweep deliberately covers the awkward cases as well as the tidy ones: five datasets ranging from clean and balanced to unbalanced, outlier-heavy and missing-data; every post-hoc method (Tukey, Bonferroni, Holm, Dunnett, FDR); every sphericity correction; one- and two-tailed alternatives; equal- and unequal-variance options; long- and wide-format input.
And it stays that way
The R reference values are stored in the codebase and re-checked whenever the statistics code is touched, so the comparison is a standing regression test rather than a one-off exercise. Every release is re-checked against it before it ships.
You can check it yourself
Every analysis comes with a Save code button that exports the exact Python used to produce it. Run it outside Plotara and it prints the same output, line for line — which also means you can drop it into a supplementary methods file, or re-run it in R against your own reference if you'd rather verify than take our word for it.
Download verification results (CSV)Precision without compromise
Every scientific study is unique, and presenting data meaningfully sometimes needs nuance that standard UI buttons can't capture — a specialised experimental layout, a niche formatting requirement for publication.
But coding every graph from scratch is slow and frustrating. The editable code viewer bridges the two: the speed of a modern interface, with the limitless customisation of writing it yourself.
How it works
Every toggle you flip and every slider you move rewrites the underlying Python when you click Generate Plot. That gives you a complete, working matplotlib script as a starting point rather than a blank file.
Edit and re-run
Change anything in the script and click Run Modified Code. The plot updates in place.
Reset at any time
Reset to UI-generated code discards your edits and hands the script back to the controls. Nothing is ever locked in.
Statistics too
The Statistics panel generates the same runnable Python, so a reviewer can reproduce your analysis exactly.
Use an AI collaborator
You don't need to be a Python expert to get professional results. Let an AI assistant do the heavy lifting:
- 1Copy the code out of your Plotara viewer.
- 2Paste it into Claude, ChatGPT or Gemini.
- 3Describe the change you want in plain English.
- 4Paste the revised script back into Plotara and click Run Modified Code.
Example: shading a significant region
Ask for a shaded band over the 15–30 s task window, and you get back a single line to drop in before the plot is saved:
ax.axvspan(15, 30, alpha=0.2)Custom overlays
If you find yourself pasting the same snippet in every time, save it as a custom overlay: give it a name and an icon, and it becomes a reusable button that applies your own Python to any future plot.
Pro Tip: Custom overlays and edited code are both saved inside presets — so your hand-tuned script comes back with one click on your next dataset.
Do the work once
Consistency matters in scientific communication. Once you've dialled in the right look, Plotara keeps it — and gives you the tools to assemble, store and reuse everything you've made.
Presets: your signature style
A preset captures the whole recipe — chart type, variable mapping, styling, extras, annotations and any code you've edited by hand.
Save it once
Name your preset, give it an icon, and pin it to Quick Access next to the chart types.
Apply it in one click
Load a new dataset, click the preset, generate. Every figure in your paper looks like it belongs to the same study.
Pro Tip: Presets store your edited Python too — so a hand-tuned layout is reusable, not a one-off.
Figure Builder: multi-panel figures
Journals rarely want a single plot. The Figure Builder assembles the plots you've already made into a finished multi-panel figure, without a trip through Illustrator.
Arrange your panels
Pick two or more saved plots and lay them out in rows. Panel labels A, B, C are added automatically — and each one is editable, or removable, if your journal numbers them differently.
Journal column widths
Single column (90 mm) and double column (180 mm) presets size the whole figure correctly the first time. Control the margin between panels, and toggle a transparent background.
Annotate across panels
Draw arrows and lines, highlight boxes, significance bars and text anywhere on the assembled figure — including across panel boundaries.
Export at full resolution
Render the finished figure at 300 DPI as PNG, SVG or PDF.
Come back and change it
Figures are saved to your gallery as editable objects. Reopen one, swap a panel, and re-export.
The gallery
Everything you save lands in one place: plots, assembled figures, Python scripts, statistical results and datasets.
Organise into folders
Group by project, paper or experiment. Move items between folders as the work evolves.
Download what you need
Grab a single image, download the code as a .py file, save results as .txt, or export every plot in a folder at once.
Pick work back up
Reopen a saved plot or dataset and carry on from exactly where you left it.
Where your work lives
Your saved work is stored on your own machine, in a folder you choose - fully accessible even if you cancel your subscription.
Choose your storage location
Point Plotara at a project folder, a synced drive, or wherever your lab keeps its data.
Migrate cleanly
Moving to a new machine? Transfer your local 'Plotara' folder to your new device and once you re-install the app, it will look exactly as your old machine did with all of your presets and saved work ready to go.
No proprietary file formats
Plotara saves everything in common file formats that you can access even if you cancel your subscription, so you're never locked out of your own analyses.
- .png for plot images, .py for code, .txt for stats