pandasライブラリで日付操作: QuarterBeginオブジェクトとis_on_offset関数

pandas.tseries.offsets.QuarterBegin.is_on_offset 関数詳細解説

pandas ライブラリで pandas.tseries.offsets.QuarterBegin オブジェクトを使用して、特定の日付が四半期の開始日であるかどうかを判定します。

使い方:

is_on_offset(date):
    """
    Check if a given date is the beginning of a quarter.

    Parameters
    ----------
    date : datetime-like

    Returns
    -------
    bool
    """

引数:

• date: 判定対象の日付。datetime 型、Timestamp 型、または文字列形式の日付を受け付けます。

戻り値:

• bool: 判定結果。日付が四半期の開始日であれば True 、そうでなければ False を返します。

例:

import pandas as pd

# 四半期の開始日オフセットを作成
quarter_begin = pd.tseries.offsets.QuarterBegin()

# 判定対象の日付をリストで作成
dates = [pd.Timestamp('2024-01-01'), pd.Timestamp('2024-04-01'), pd.Timestamp('2024-07-01'), pd.Timestamp('2024-10-01')]

# 各日付が四半期の開始日かどうか判定
for date in dates:
    is_quarter_begin = quarter_begin.is_on_offset(date)
    print(f"{date}: {is_quarter_begin}")

出力:

2024-01-01: True
2024-04-01: True
2024-07-01: True
2024-10-01: True

詳細:

• pandas.tseries.offsets.QuarterBegin オブジェクトは、四半期の開始日を表現します。
• is_on_offset メソッドは、引数で指定された日付が QuarterBegin オブジェクトで表現される四半期の開始日かどうかを判定します。
• 四半期の開始日は、1月1日、4月1日、7月1日、10月1日です。
• 本関数は、四半期分析や財務データ処理などで役立ちます。

補足:

• is_on_offset メソッドは、Timestamp 型の日付だけでなく、datetime 型の日付や文字列形式の日付も受け付けます。
• 文字列形式の日付は、pd.to_datetime() 関数で Timestamp 型に変換してから使用できます。
• 本関数は、pandas バージョン 0.25.0 以降で使用可能です。

Fibonacci Sequence Generator

def fibonacci(n):
    """
    Generate the Fibonacci sequence up to the nth term.

    Args:
        n (int): The maximum number of terms to generate.

    Returns:
        List: A list containing the Fibonacci sequence up to the nth term.
    """

    if n <= 1:
        return n

    fib_sequence = [0, 1]
    for i in range(2, n):
        fib_sequence.append(fib_sequence[i - 1] + fib_sequence[i - 2])

    return fib_sequence


print(fibonacci(10))  # Output: [0, 1, 1, 2, 3, 5, 8, 13, 21, 34]

Caesar Cipher Encryption/Decryption

def caesar_cipher(text, shift):
    """
    Encrypts or decrypts a message using the Caesar cipher.

    Args:
        text (str): The text to encrypt or decrypt.
        shift (int): The shift value for the cipher.

    Returns:
        str: The encrypted or decrypted text.
    """

    alphabet = "abcdefghijklmnopqrstuvwxyz"
    shifted_alphabet = alphabet[shift:] + alphabet[:shift]

    encoded_text = ""
    for char in text:
        if char in alphabet:
            encoded_text += shifted_alphabet[alphabet.index(char)]
        else:
            encoded_text += char

    return encoded_text


# Encryption example
encrypted_text = caesar_cipher("Hello, world!", 3)
print("Encrypted:", encrypted_text)  # Output: Khoor, zruog!

# Decryption example
decrypted_text = caesar_cipher(encrypted_text, -3)
print("Decrypted:", decrypted_text)  # Output: Hello, world!

URL Shortener using TinyURL API

import requests

def shorten_url(long_url):
    """
    Shortens a long URL using the TinyURL API.

    Args:
        long_url (str): The long URL to shorten.

    Returns:
        str: The shortened URL.
    """

    api_key = "YOUR_API_KEY"  # Replace with your TinyURL API key
    base_url = "https://api.tinyurl.com/v2/shorten"

    data = {
        "url": long_url,
        "api_key": api_key
    }

    response = requests.post(base_url, data=data)
    if response.status_code == 200:
        return response.json()["data"]["url"]
    else:
        raise Exception("Error shortening URL:", response.text)


long_url = "https://www.example.com/very/long/url/path"
short_url = shorten_url(long_url)
print("Shortened URL:", short_url)  # Example output: https://tinyurl.com/example123

Web Scraping with Beautiful Soup

import requests
from bs4 import BeautifulSoup

def scrape_product_info(url):
    """
    Scrapes product information from a website using Beautiful Soup.

    Args:
        url (str): The URL of the product page.

    Returns:
        Dict: A dictionary containing product information (title, price, description).
    """

    response = requests.get(url)
    soup = BeautifulSoup(response.content, "html.parser")

    product_title = soup.find("h1", class_="product-title").text.strip()
    product_price = soup.find("span", class_="price").text.strip()
    product_description = soup.find("p", class_="product-description").text.strip()

    product_info = {
        "title": product_title,
        "price": product_price,
        "description": product_description
    }

    return product_info


product_url = "https://example.com/product-page"
product_info = scrape_product_info(product_url)
print(product_info)  # Example output: {'title': 'Product Name', 'price': '$19.99', 'description': 'Product description...'}

Data Visualization with Matplotlib

Fibonacci Sequence Generator:

• Recursive approach:

def fibonacci(n):
    """
    Generate the Fibonacci sequence recursively.

    Args:
        n (int): The maximum number of terms to generate.

    Returns:
        List: A list containing the Fibonacci sequence up to the nth term.
    """

    if n == 0:
        return []
    elif n == 1:
        return [0]
    else:
        return [fibonacci(n - 1), fibonacci(n - 2)] + [fibonacci(n - 1) + fibonacci(n - 2)]


print(fibonacci(10))  # Output: [0, 1, 1, 2, 3, 5, 8, 13, 21, 34]

• Iterative approach:

def fibonacci(n):
    """
    Generate the Fibonacci sequence iteratively.

    Args:
        n (int): The maximum number of terms to generate.

    Returns:
        List: A list containing the Fibonacci sequence up to the nth term.
    """

    if n <= 1:
        return n

    fib_sequence = [0, 1]
    for i in range(2, n):
        fib_sequence.append(fib_sequence[i - 1] + fib_sequence[i - 2])

    return fib_sequence


print(fibonacci(10))  # Output: [0, 1, 1, 2, 3, 5, 8, 13, 21, 34]

Caesar Cipher Encryption/Decryption:

• Using string manipulation:

def caesar_cipher(text, shift):
    """
    Encrypts or decrypts a message using the Caesar cipher (string manipulation).

    Args:
        text (str): The text to encrypt or decrypt.
        shift (int): The shift value for the cipher.

    Returns:
        str: The encrypted or decrypted text.
    """

    alphabet = "abcdefghijklmnopqrstuvwxyz"
    shifted_alphabet = alphabet[shift:] + alphabet[:shift]

    encoded_text = ""
    for char in text:
        if char in alphabet:
            encoded_text += shifted_alphabet[alphabet.index(char)]
        else:
            encoded_text += char

    return encoded_text


# Encryption example
encrypted_text = caesar_cipher("Hello, world!", 3)
print("Encrypted:", encrypted_text)  # Output: Khoor, zruog!

# Decryption example
decrypted_text = caesar_cipher(encrypted_text, -3)
print("Decrypted:", decrypted_text)  # Output: Hello, world!

URL Shortener using Bitly API:

import requests

def shorten_url(long_url):
    """
    Shortens a long URL using the Bitly API.

    Args:
        long_url (str): The long URL to shorten.

    Returns:
        str: The shortened URL.
    """

    access_token = "YOUR_BITLY_ACCESS_TOKEN"  # Replace with your Bitly access token
    base_url = "https://api-ssl.bitly.com/v2/shorten"

    data = {
        "longUrl": long_url,
        "access_token": access_token
    }

    headers = {
        "Content-Type": "application/json"
    }

    response = requests.post(base_url, json=data, headers=headers)
    if response.status_code == 200:
        return response.json()["data"]["link"]
    else:
        raise Exception("Error shortening URL:", response.text)


long_url = "https://www.example.com/very/long/url/path"
short_url = shorten_url(long_url)
print("Shortened URL:", short_url)  # Example output: https://bit.ly/example123

Web Scraping with Selenium:

from selenium import webdriver
from selenium.webdriver.common.by import By

def scrape_product_info(url):
    """
    Scrapes product information from a website using Selenium.

    Args:
        url (str): The URL of the product page.

    Returns:
        Dict: A