chengyc17

chengyc17 / mini-panda

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mini-panda: Java version of pandas for data engineers. DataFrame/Series, group/merge/pivot, CSV/JSON/Excel/SQL, 18 ECharts, .show() to visualize. Java 17, immutable, lightweight.

dataframes java pandas
12
0
100% credibility
Found May 09, 2026 at 12 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Java
AI Summary

mini-panda is a Java library replicating Python pandas core functionality for immutable tabular data manipulation, including DataFrames, Series, I/O support, grouping, merging, and integrated charting.

How It Works

1
📖 Discover mini-panda

You hear about a friendly tool that handles tables like your spreadsheets, making data easy to organize and explore.

2
🛠️ Set it up quickly

You add this handy helper to your work with a simple step, no hassle involved.

3
📥 Load your table

Upload your CSV, Excel, or other file, and watch it turn into a clean, ready-to-use table right away.

4
🔍 Explore and tidy up

Peek at the first rows, filter what you need, fill gaps, and sort everything neatly.

5
📈 Analyze and group

Group similar items, calculate totals or averages, and reshape your data effortlessly.

6
🎨 Create stunning charts

Pick a chart type like bars or lines, and see interactive visuals open in your browser instantly.

💾 Save and share

Export your cleaned insights back to files or databases, ready to use or show others.

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Star Growth

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AI-Generated Review

What is mini-panda?

Mini-panda brings pandas-style data manipulation to Java 17+, letting data engineers work with immutable DataFrame and Series objects for CSV/JSON/Excel/SQL files. You get group/merge/pivot operations, filtering, aggregation, and 18 ECharts visualizations via a simple .show() call—no extra setup needed. It's lightweight and familiar for Python users transitioning to Java backends.

Why is it gaining traction?

Unlike heavy Java data libs, mini-panda stays lean with copy-on-write immutability for thread-safe pipelines and zero-config viz that pops open in your browser. The API mirrors pandas closely, so you chain selects, groupbys, and plots without relearning syntax. Built-in I/O and ECharts handle common ETL + dashboard needs out of the box.

Who should use this?

Java data engineers processing CSV/JSON/Excel/SQL in microservices or batch jobs. Backend devs building lightweight analytics tools, or teams migrating pandas scripts to JVM for performance. Ideal if you want quick pivots, merges, and interactive charts without Spark or full BI stacks.

Verdict

Promising early prototype (12 stars, 1.0% credibility score) with solid docs and tests—try for side projects or proofs-of-concept where immutable Java data frames shine. Skip for production until Maven Central lands and maturity grows.

(178 words)

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