CSV: Working with Tables 📊

Goal: Learn to read and write tabular data in CSV format.

🤔 What Is CSV?

CSV (Comma-Separated Values) is a text file format for storing tabular data.

Example CSV file:

name,age,balance
Алиса,25,1000
Боб,30,500
Чарли,22,2000

How it looks in Excel:
| name | age | balance |
|------|-----|---------|
| Алиса | 25 | 1000 |
| Боб | 30 | 500 |
| Чарли | 22 | 2000 |

Features:
- ✅ Simple text format
- ✅ Opens in Excel, Google Sheets
- ✅ Used for data export/import
- ✅ Built-in Python support!

📝 Importing the CSV Module

import csv

Main functions:
- csv.writer() — write CSV
- csv.reader() — read CSV
- csv.DictWriter() — write with dicts
- csv.DictReader() — read with dicts

💾 Writing CSV — csv.writer()

Basic Writing

import csv

# Data to write
data = [
    ["name", "age", "balance"],
    ["Алиса", 25, 1000],
    ["Боб", 30, 500],
    ["Чарли", 22, 2000]
]

# Write to file
with open("users.csv", "w", encoding="utf-8", newline='') as file:
    writer = csv.writer(file)
    writer.writerows(data)  # Write all rows at once

print("CSV file created!")

What happens:
1. csv.writer(file) — create a writer object
2. writerows(data) — write all rows at once
3. File users.csv is created!

Result (users.csv):

name,age,balance
Алиса,25,1000
Боб,30,500
Чарли,22,2000

Writing Row by Row

import csv

with open("accounts.csv", "w", encoding="utf-8", newline='') as file:
    writer = csv.writer(file)

    # Headers
    writer.writerow(["name", "balance", "status"])

    # Data
    writer.writerow(["Алиса", 1000, "active"])
    writer.writerow(["Боб", 500, "blocked"])

print("Done!")

writerow() — write one row
writerows() — write multiple rows

📂 Reading CSV — csv.reader()

import csv

with open("users.csv", "r", encoding="utf-8") as file:
    reader = csv.reader(file)

    for row in reader:
        print(row)

# Output:
# ['name', 'age', 'balance']
# ['Алиса', '25', '1000']
# ['Боб', '30', '500']
# ['Чарли', '22', '2000']

What happens:
- csv.reader(file) — create a reader
- Each row is a list of strings
- The first row contains headers

Skipping Headers

import csv

with open("users.csv", "r", encoding="utf-8") as file:
    reader = csv.reader(file)
    next(reader)  # Skip the first row (headers)

    for row in reader:
        name = row[0]
        age = int(row[1])
        balance = int(row[2])
        print(f"{name}: {age} years old, balance {balance}")

# Output:
# Алиса: 25 years old, balance 1000
# Боб: 30 years old, balance 500
# Чарли: 22 years old, balance 2000

next(reader) — read and skip one row.

📚 Working with Dicts — DictWriter/DictReader

Writing with Dicts — csv.DictWriter()

import csv

accounts = [
    {"name": "Алиса", "balance": 1000, "currency": "RUB"},
    {"name": "Боб", "balance": 500, "currency": "USD"},
    {"name": "Чарли", "balance": 2000, "currency": "RUB"}
]

with open("accounts.csv", "w", encoding="utf-8", newline='') as file:
    fields = ["name", "balance", "currency"]
    writer = csv.DictWriter(file, fieldnames=fields)

    writer.writeheader()      # Write headers
    writer.writerows(accounts)  # Write data

print("CSV created!")

Advantages:
- ✅ Works with dicts (more convenient)
- ✅ No need to remember column order
- ✅ Automatic headers

Reading with Dicts — csv.DictReader()

import csv

with open("accounts.csv", "r", encoding="utf-8") as file:
    reader = csv.DictReader(file)

    for row in reader:
        print(f"{row['name']}: {row['balance']} {row['currency']}")

# Output:
# Алиса: 1000 RUB
# Боб: 500 USD
# Чарли: 2000 RUB

Each row is a dict!
- Keys — column names
- Values — data from the row

🎯 Example: Exporting Bank Transactions

import csv

class BankAccount:
    def __init__(self, name, balance=0):
        self.name = name
        self.balance = balance
        self.transactions = []

    def deposit(self, amount):
        """Deposit money."""
        self.balance += amount
        self.transactions.append({
            "type": "deposit",
            "amount": amount,
            "balance": self.balance
        })

    def withdraw(self, amount):
        """Withdraw money."""
        if amount > self.balance:
            return False

        self.balance -= amount
        self.transactions.append({
            "type": "withdraw",
            "amount": amount,
            "balance": self.balance
        })
        return True

    def export_transactions(self, filename):
        """Export transactions to CSV."""
        with open(filename, "w", encoding="utf-8", newline='') as file:
            fields = ["type", "amount", "balance"]
            writer = csv.DictWriter(file, fieldnames=fields)

            writer.writeheader()
            writer.writerows(self.transactions)

        print(f"Transactions exported to {filename}")

# Usage
account = BankAccount("Алиса", 1000)
account.deposit(500)
account.withdraw(200)
account.deposit(300)
account.export_transactions("alice_transactions.csv")

Result (alice_transactions.csv):

type,amount,balance
deposit,500,1500
withdraw,200,1300
deposit,300,1600

🎯 Example: Exporting All Bank Accounts

import csv

class Bank:
    def __init__(self):
        self.accounts = []

    def create_account(self, name, balance=0):
        """Create an account."""
        account = {"name": name, "balance": balance}
        self.accounts.append(account)

    def export_all_accounts(self, filename):
        """Export all accounts to CSV."""
        with open(filename, "w", encoding="utf-8", newline='') as file:
            fields = ["name", "balance"]
            writer = csv.DictWriter(file, fieldnames=fields)

            writer.writeheader()
            writer.writerows(self.accounts)

        print(f"All accounts exported to {filename}")

# Usage
bank = Bank()
bank.create_account("Алиса", 1000)
bank.create_account("Боб", 500)
bank.create_account("Чарли", 2000)
bank.export_all_accounts("bank_accounts.csv")

Result (bank_accounts.csv):

name,balance
Алиса,1000
Боб,500
Чарли,2000

🛡️ Safe CSV Reading

import csv

def load_accounts_from_csv(filename):
    """Load accounts from CSV."""
    accounts = []

    try:
        with open(filename, "r", encoding="utf-8") as file:
            reader = csv.DictReader(file)

            for row in reader:
                try:
                    account = {
                        "name": row["name"],
                        "balance": float(row["balance"])
                    }
                    accounts.append(account)
                except (KeyError, ValueError) as e:
                    print(f"Error in row: {row}. Skipping.")

        print(f"Loaded {len(accounts)} accounts")
        return accounts

    except FileNotFoundError:
        print("File not found!")
        return []

# Usage
accounts = load_accounts_from_csv("bank_accounts.csv")
for account in accounts:
    print(f"{account['name']}: {account['balance']}")

📊 Using Delimiters

By default, CSV uses a comma ,, but you can change it:

Semicolon (;)

import csv

data = [["name", "balance"], ["Алиса", 1000]]

with open("data.csv", "w", encoding="utf-8", newline='') as file:
    writer = csv.writer(file, delimiter=';')
    writer.writerows(data)

# Result: name;balance

Tab (\t)

writer = csv.writer(file, delimiter='\t')

⚡ Best Practices

✅ Do:

1. Use encoding="utf-8" for non-ASCII characters
2. Use newline='' when writing
3. Use DictWriter/DictReader for convenience
4. Wrap file reads in try/except
5. Validate data when reading

❌ Don’t:

1. Don’t forget headers (writeheader())
2. Don’t mix delimiters
3. Don’t ignore errors when reading

🎓 Summary

CSV is:
- ✅ A tabular data format
- ✅ Opens in Excel
- ✅ Simple export/import
- ✅ Built-in Python support

Main functions:
- csv.writer() → write lists
- csv.reader() → read lists
- csv.DictWriter() → write dicts
- csv.DictReader() → read dicts

Golden rule: Use DictWriter/DictReader for dict-based work — it’s more convenient and readable!

🔗 Related Topics

• JSON: Сохранение данных 💾
• With: Работа с файлами 📄
• Try/Except: Обработка ошибок ❗

Now you can export data to Excel! 📊✨