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 n rows 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_summary requires matplotlib, 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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Made with ❤️ by the **Atikin Data** 🚀  
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