QUICKSTART.md

PipeFrame Quick Start Guide

Get up and running with PipeFrame in 5 minutes!

Installation

pip install pipeframe

Your First Pipeline

from pipeframe import *

# Create data
df = DataFrame({
    'name': ['Alice', 'Bob', 'Charlie'],
    'age': [25, 32, 37],
    'salary': [50000, 65000, 72000]
})

# Transform with pipes
result = (df
    >> filter('age > 30')
    >> define(bonus='salary * 0.1')
    >> select('name', 'salary', 'bonus')
    >> arrange('-salary')
)

print(result)

Core Concepts

1. The Pipe Operator >>

Chain operations naturally:

df >> operation1 >> operation2 >> operation3

2. String Expressions

Write conditions as readable strings:

df >> filter('age > 30 & salary > 50000')
df >> define(bonus='salary * 0.1')

3. Essential Verbs

Verb	What It Does
filter()	Keep rows matching condition
define()	Create/modify columns
select()	Choose columns
arrange()	Sort rows
group_by()	Group data
summarize()	Aggregate groups

Common Patterns

Filter and Transform

result = (df
    >> filter('status == "active"')
    >> define(total='quantity * price')
    >> select('customer', 'total')
)

Group and Aggregate

summary = (df
    >> group_by('category')
    >> summarize(
        count='count()',
        total='sum(amount)',
        average='mean(amount)'
    )
)

Sort and Limit

top_10 = (df
    >> arrange('-revenue')
    >> slice_rows(0, 10)
)

Next Steps

• 📘 Full Tutorial: examples/tutorial.ipynb
• 📚 Documentation: https://pipeframe.readthedocs.io
• 💡 Examples: examples/ directory
• ❓ Questions: Open an issue on GitHub

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Author: Dr. Yasser Mustafa
Email: yasser.mustafan@gmail.com