Chapter 6 — Strings, Files, and Object-Oriented Programming

Real data arrives as text and files. This chapter deepens string handling and regular expressions, covers file I/O and exception handling, then introduces object-oriented programming — the paradigm behind the pandas and scikit-learn objects you will use throughout the book.

Learning Objectives

Apply common string methods for cleaning text.
Use regular expressions to extract and replace patterns.
Read and write text and CSV files.
Handle exceptions with try/except/else/finally.
Define classes with constructors, attributes, and methods.
Implement special methods like __str__ and __eq__.
See how OOP underpins pandas and scikit-learn.

Prerequisites / Imports

Uses the standard re and csv modules.

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import re
import csv
import os

1 The str Class

Strings are immutable; methods return new strings. Common tools: strip, split, join, replace, find, count, upper/lower.

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raw = '  Data Science, 2026  '
clean = raw.strip()
print('stripped:', repr(clean))
print('upper:', clean.upper())
print('words:', clean.split())
print('joined:', '-'.join(clean.split()))
print('replace:', clean.replace('Science', 'Engineering'))

stripped: 'Data Science, 2026'
upper: DATA SCIENCE, 2026
words: ['Data', 'Science,', '2026']
joined: Data-Science,-2026
replace: Data Engineering, 2026

2 Regular Expressions for Data Cleaning

re finds and substitutes patterns — essential for messy text.

In [1]:

text = 'Call 555-1234 or 555.5678 for help'
phones = re.findall(r'\d{3}[-.]\d{4}', text)
print('phones found:', phones)

cleaned = re.sub(r'[^a-zA-Z0-9 ]', '', 'Price: $19.99! #deal')
print('cleaned:', cleaned)

phones found: ['555-1234', '555.5678']
cleaned: Price 1999 deal

3 Files: Reading and Writing

Use with open(...) so files close automatically. We write and read a small CSV.

In [1]:

path = 'ch06_sales.csv'
with open(path, 'w', newline='') as f:
    w = csv.writer(f)
    w.writerow(['item', 'qty', 'price'])
    w.writerows([('Widget', 3, 4.50), ('Gadget', 2, 12.75), ('Cable', 5, 1.20)])

with open(path, 'r') as f:
    for row in csv.DictReader(f):
        print(row)

{'item': 'Widget', 'qty': '3', 'price': '4.5'}
{'item': 'Gadget', 'qty': '2', 'price': '12.75'}
{'item': 'Cable', 'qty': '5', 'price': '1.2'}

4 Exception Handling

Catch errors to keep programs robust. try/except/else/finally.

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try:
    with open('does_not_exist.csv') as f:
        data = f.read()
except FileNotFoundError:
    print('File not found — handled gracefully.')
finally:
    print('Cleanup runs no matter what.')

File not found — handled gracefully.
Cleanup runs no matter what.

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def safe_divide(a, b):
    try:
        return a / b
    except ZeroDivisionError:
        return float('inf')

print(safe_divide(10, 0))

inf

5 Defining Classes

A class bundles data (attributes) and behavior (methods). __init__ is the constructor; self refers to the instance.

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class Student:
    def __init__(self, name, scores):
        self.name = name
        self.scores = scores

    def average(self):
        return sum(self.scores) / len(self.scores)

    def __str__(self):
        return f'Student({self.name}, avg={self.average():.1f})'

s = Student('Ada', [88, 92, 79])
print(s)
print('average:', s.average())

Student(Ada, avg=86.3)
average: 86.33333333333333

6 Special Methods and Operator Overloading

Dunder methods customize object behavior, e.g. __eq__ for ==.

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class Money:
    def __init__(self, dollars, cents=0):
        self.total_cents = dollars * 100 + cents

    def __eq__(self, other):
        return self.total_cents == other.total_cents

    def __add__(self, other):
        return Money(0, self.total_cents + other.total_cents)

    def __str__(self):
        return f'${self.total_cents/100:.2f}'

print(Money(5, 50) + Money(2, 75))
print(Money(1, 0) == Money(0, 100))

$8.25
True

7 Encapsulation

Prefix attributes with _ to signal "internal". Provide methods to control access.

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class Account:
    def __init__(self, owner, balance=0):
        self.owner = owner
        self._balance = balance

    def deposit(self, amount):
        if amount <= 0:
            raise ValueError('Deposit must be positive')
        self._balance += amount

    def withdraw(self, amount):
        if amount > self._balance:
            raise ValueError('Insufficient funds')
        self._balance -= amount

    @property
    def balance(self):
        return self._balance

acc = Account('Bo', 100)
acc.deposit(50)
acc.withdraw(30)
print('balance:', acc.balance)

balance: 120

8 OOP Underpins the Data-Science Stack

A pandas DataFrame is an object with methods (head, describe, groupby). A scikit-learn estimator is an object with fit and predict. Understanding classes helps you read documentation and extend these tools.

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# Preview: a DataFrame is an object with methods
import pandas as pd
df = pd.DataFrame({'x': [1, 2, 3], 'y': [4, 5, 6]})
print(type(df))
print('methods include:', [m for m in ['head','describe','groupby','sum'] if hasattr(df, m)])
df.sum()

<class 'pandas.core.frame.DataFrame'>
methods include: ['head', 'describe', 'groupby', 'sum']

x     6
y    15
dtype: int64

Case Study: A Customer Record Class with File Persistence

Define a Customer class, create instances, persist them to CSV, read them back, and handle a missing file gracefully.

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class Customer:
    def __init__(self, cid, name, email, balance=0.0):
        self.cid = cid
        self.name = name
        self.email = email
        self.balance = balance

    def apply_transaction(self, amount):
        self.balance += amount
        return self.balance

    def __str__(self):
        return f'{self.cid}|{self.name}|{self.email}|{self.balance:.2f}'

customers = [
    Customer(1, 'Ada Lovelace', 'ada@example.com', 500),
    Customer(2, 'Bo Yang', 'bo@example.com', 320),
    Customer(3, 'Cy Patel', 'cy@example.com', -50),
]

# Persist to CSV
path = 'ch06_customers.csv'
with open(path, 'w', newline='') as f:
    w = csv.writer(f)
    w.writerow(['id', 'name', 'email', 'balance'])
    for c in customers:
        w.writerow([c.cid, c.name, c.email, c.balance])
print('Saved', path)

# Read back into Customer objects
loaded = []
try:
    with open(path, 'r') as f:
        for row in csv.DictReader(f):
            loaded.append(Customer(int(row['id']), row['name'], row['email'], float(row['balance'])))
except FileNotFoundError:
    print('No customer file found.')

for c in loaded:
    print(c)

Saved ch06_customers.csv
1|Ada Lovelace|ada@example.com|500.00
2|Bo Yang|bo@example.com|320.00
3|Cy Patel|cy@example.com|-50.00

Exercises

Strip whitespace and title-case the string ' data science '.
Use re.findall to extract all numbers from 'order 3 of 14 items, total 99'.
Write a list of dicts to a CSV file and read it back.
Write a try/except that catches a ValueError from int('abc').
Add a grade() method to the Student class that returns a letter grade.
Implement __eq__ on a Point class comparing x and y.
Add validation to Account.withdraw and test it raises on overdraft.
Explain the difference between self._balance and self.balance.
Write a function that counts words in a text file.
Describe two ways pandas/scikit-learn objects use OOP.

Python Data Science: From Foundations to Applications — Chapter 6