Atikin-Data — lightweight smart data toolkit (mini-pandas style utilities for daily use)
Project description
Atikin-Data
Atikin-Data is a smart, lightweight, and advanced daily-use data toolkit for Python developers.
It helps you handle CSV, Excel, JSON files, summarize, filter, sort, merge, convert, and even visualize datasets effortlessly.
Developed by: Atikin Verse
🚀 Features
1. Quick Summary
from atikin_data import quick_summary
summary = quick_summary("data.csv")
print(summary)
- Rows, Columns
- Column names & data types
- Mini alternative to Pandas profiling
2. Quick Preview
from atikin_data import quick_preview
preview = quick_preview("data.csv", n=5)
print(preview)
- Preview first
nrows of your dataset
3. Missing Report
from atikin_data import missing_report
report = missing_report("data.csv")
print(report)
- Count missing values per column
4. Column Stats
from atikin_data import column_stats
stats = column_stats("data.csv")
print(stats)
- Min, Max, Mean for numeric columns
5. Merge Files
from atikin_data import merge_files
output = merge_files(["file1.csv","file2.csv"], output="merged.csv")
- Merge multiple CSV files into one
6. Auto Convert
from atikin_data import auto_convert
auto_convert("data.csv", "data.xlsx")
- Convert CSV ⇄ Excel ⇄ JSON automatically
7. Filter Rows
from atikin_data import filter_rows
filtered = filter_rows("data.csv", "Age > 25 and City == 'Delhi'")
print(filtered)
- Filter rows using conditions (Pandas query syntax)
8. Sort Columns
from atikin_data import sort_columns
sorted_df = sort_columns("data.csv", "Age", ascending=True)
print(sorted_df)
- Sort dataset by any column
9. Visual Summary
from atikin_data import visual_summary
visual_summary("data.csv")
- Quick histogram/plots for numeric columns
- Requires
matplotlib(pip install matplotlib)
📦 Installation
pip install pandas numpy openpyxl matplotlib
pip install -e .
🧪 Testing
pytest -q
- All tests should pass ✅
⚡ Notes
visual_summaryrequiresmatplotlib, but rest of the functions work without it.- Supports CSV, Excel (
.xls,.xlsx), and JSON files. - Lightweight, fast, and easy-to-use for daily data tasks.
💡 Example Usage
from atikin_data import quick_summary, filter_rows, merge_files
# Quick summary
summary = quick_summary("data.csv")
print(summary)
# Filter rows
filtered = filter_rows("data.csv", "Age > 30")
print(filtered)
# Merge multiple files
merge_files(["data1.csv","data2.csv"], "merged.csv")
🔗 Author
Atikin Verse For more tools & libraries: https://atikinverse.com
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<div align="center">
Made with ❤️ by the **Atikin Data** 🚀
</div>
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