The free alternatives to GraphPad Prism, honestly assessed

Plotara is not free, so let's deal with that immediately. If free is a hard requirement, this page still tells you which option to pick, because several of them are genuinely good.

The reason to read on is that "free" software is rarely free. It is paid for in hours, usually yours, usually the week before a deadline.

The genuinely free options

R with ggplot2. The most capable option on this list, and it costs nothing. Publication figures from ggplot2 are excellent. The cost is the learning curve, and it is real. Budget weeks, not evenings, if you are starting from zero.

Python with matplotlib or seaborn. Same trade as R. Enormous power, complete control, and a lot of time spent on things that are not your research.

JASP and jamovi. Both free, both open source, both with a proper graphical interface. Genuinely strong statistics. The weak point for most people is figure production, which is functional rather than publication-grade.

Veusz and SciDAVis. Free scientific plotting with good vector output. Plotting only, so you will need something else for the statistics.

Excel. It is on every machine and it will make a chart. It should not be used for statistical testing, and its default charts are recognisable as Excel charts from across a lecture theatre.

What the free options cost

The honest accounting is time. Learning ggplot2 well enough to produce a journal-ready multi-panel figure is a multi-week project. Doing it once a year means relearning it annually. If your time is worth anything at all, the arithmetic changes.

The second cost is inconsistency. Hand-built figures drift. Panel A and panel B end up with different fonts, different axis weights, different colours.

Where Plotara sits

Paid, and priced for individuals rather than institutions: £10 a month or £84 a year for students, £20 a month or £180 a year professional, with a 30-day trial and no card required. Subscriptions can be paused without limit, so you pay for the months you actually use it.

What you get for it is the middle ground the free tools miss. A graphical interface, 50+ statistical tests, 22 graph types, journal-width multi-panel layout, and the Python code for everything you do, so you keep the reproducibility that R and Python users rightly value.

If free is non-negotiable, use JASP for the statistics and ggplot2 for the figures. That is a good, honest answer, and it costs nothing.