# Matplotlib教程 vs Pythona

The clearest difference is price: Pythona at Free against Matplotlib教程's $1.99. Pythona also leads on rating (5.0 vs 3.0) and review sentiment (71% vs 33%). Matplotlib教程's advantage is in-app purchases (none vs 1) and iOS requirement (12.0 vs 17.0). On ratings volume, ads, chart position and device support there is nothing between them.

Pythona is free to download; Matplotlib教程 costs $1.99 up front. Pythona sells 1 one-off in-app purchase. Matplotlib教程 asks for nothing beyond the download.

Pythona holds the better App Store score, 5.0 against 3.0. Both are backed by a comparable volume of ratings — 2 and 5 respectively. Written reviews point the same way: 33% of Matplotlib教程's written reviews are positive against 71% of Pythona's.

Matplotlib教程 ships an update every 21 months, Pythona every 6 days. The most recent releases landed on October 7, 2026 and October 18, 2026 respectively.

## The numbers

| Metric | Matplotlib教程 | Pythona |
| --- | --- | --- |
| Price | $1.99 | **Free** |
| Rating | [3.0 (2 ratings)](https://appshunter.io/ios/app/matplotlib/id1583770274/reviews) | **[5.0 (5 ratings)](https://appshunter.io/ios/app/pythona-python-3-ide/id6760310359/reviews)** |
| Number of ratings | 2 | **5** |
| Positive reviews | 33.3% of reviews | **71.4% of reviews** |
| In-app purchases | **No** | Yes |
| Ads | No | No |
| Update frequency | Every 21 months | **Every 6 days** |
| Monetization | Paid | **Free** |
| Best chart rank | #197 | **#184** |
| Size | 15 MB | 560 MB |
| Requires iOS | **12.0** | 17.0 |
| Devices | **iPhone, iPad, iPod** | iPhone, iPad |
| Age rating | 4+ | 4+ |
| Developer | [强 马](https://appshunter.io/developer/687218962) | [志远 刘](https://appshunter.io/developer/1703944678) |

## What reviewers say

### Matplotlib教程

[App page](https://appshunter.io/ios/app/matplotlib/id1583770274)

**Currently charting:** #197 Top Paid · Developer Tools (US App Store)

This app teaches users how to create various static, dynamic, and interactive charts using Python's Matplotlib library. It covers a wide range of plot types, from simple line graphs to complex 3D visualizations and animations, making data presentation more intuitive.

**Highlights:** Learn data visualization with Python, Create static, dynamic, and interactive charts, Draw line plots, scatter plots, and contour plots, Generate bar charts, histograms, and 3D graphics, Explore animated visualizations, Multiple output formats supported

**Features:** macOS Compatibility, Vision Pro support

**In-app purchases:** none


### Pythona

[App page](https://appshunter.io/ios/app/pythona-python-3-ide/id6760310359)

**Currently charting:** #184 Top Free · Developer Tools (US App Store)

Run Python 3.14 and large language models entirely on-device with a full-featured IDE. Supports Jupyter-style notebooks, scientific computing libraries, and local AI inference without API keys.

**Highlights:** Jupyter-style notebooks, On-device AI & machine learning, Preinstalled scientific computing libraries, Local Python 3.14 environment, Smart code completion, Markdown file preview

**Features:** macOS Compatibility, Vision Pro support

**In-app purchases (1)**

| Purchase | Price | Billing |
| --- | --- | --- |
| Pythona Pro | $9.99 | one-time |


## Frequently asked questions

### Is Matplotlib教程 free?

Matplotlib教程 costs $1.99, with no in-app purchases.

### Is Pythona free?

Pythona is free to download, with in-app purchases available.

### Which has better reviews, Matplotlib教程 or Pythona?

Pythona is rated higher. Matplotlib教程 averages 3.0 out of 5 from 2 ratings, while Pythona averages 5.0 from 5 ratings.

### Do Matplotlib教程 or Pythona have ads?

Neither Matplotlib教程 nor Pythona shows ads.

### Which is updated more often, Matplotlib教程 or Pythona?

Matplotlib教程 ships an update every 21 months, and Pythona every 6 days. Most recently, Matplotlib教程 was updated on October 7, 2026 and Pythona on October 18, 2026.

### Which is more popular, Matplotlib教程 or Pythona?

Matplotlib教程 currently peaks at #197 in the App Store charts, and Pythona at #184. Chart position reflects recent download velocity rather than total install base.

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*Compared by [AppsHunter](https://appshunter.io/) from daily US App Store data. Review summaries are generated from verbatim App Store reviews.*