python_참고자료.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 파이썬(Python) 기초\n",
    "\n",
    "* 참고(Jump to python) [Link](https://wikidocs.net/book/1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 기본 자료형(int, float, str, list, tuple,bool) 살펴보기\n",
    "\n",
    "* 아래의 코드를 따라 실행해보세요 :D"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### int형\n",
    "* 정수형(Integer)이란 말 그대로 정수를 뜻하는 자료형을 말한다. 다음 예는 양의 정수와 음의 정수, 숫자 0을 변수 a에 대입하는 예이다.\n",
    "\n",
    "#### type()\n",
    "* 데이터 타입(int, float, str ...)을 확인하는 함수"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "# 따라 쳐보세요!\n",
    "a = 123\n",
    "print(type(a))\n",
    "a = -123\n",
    "print(type(a))\n",
    "a = 0\n",
    "print(type(a))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### float형\n",
    "* 파이썬에서 실수형(Floating-point)은 소수점이 포함된 숫자를 말한다. 다음은 실수를 변수 a에 대입하는 예이다."
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "a = 1.342\n",
    "print(type(a))\n",
    "a = -1.123\n",
    "print(type(a))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### str형\n",
    "* 문자열(String)이란 문자, 단어 등으로 구성된 문자들의 집합을 의미한다. "
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "a = \"Hello\"\n",
    "print(type(a))\n",
    "a = \"안녕하세요\"\n",
    "print(type(a))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 문자열 인덱싱(indexing)\n",
    "\n",
    "```python\n",
    "    >>> a = \"Hello\"\n",
    "```\n",
    "\n",
    "* 위의 소스코드에서 변수 a에 저장한 문자열의 각 문자마다 번호를 매겨 보면 다음과 같다.\n",
    " |H|e|l|l|o|\n",
    " |-|-|-|-|-|\n",
    " |0|1|2|3|4|\n",
    "* __\"파이썬은 0부터 숫자를 센다\"__"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "a = \"Hello\"\n",
    "print(a[0])\n",
    "print(a[1])\n",
    "print(a[-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 문자열 슬라이싱(slicing)\n",
    "\n",
    "```python\n",
    "    >>> a = \"Hello\"\n",
    "    >>> a[0:3]\n",
    "    'Hel'\n",
    "```\n",
    "* a[0:3]이 뜻하는 것은 a 문자열, 즉 \"Hello\"에서 0부터 3까지의 문자를 뽑아낸다는 뜻이다.\n",
    "* '시작번호' <= a < '끝번호' 까지의 문자를 뽑아낸다.\n",
    "> ※ 인덱싱 기법과 슬라이싱 기법은 뒤에서 배울 자료형인 리스트나 튜플에서도 사용할 수 있다."
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "a = \"Hello\"\n",
    "a[0:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### bool형\n",
    "* 불(bool) 자료형이란 참(True)과 거짓(False)을 나타내는 자료형이다. 불 자료형은 다음 2가지 값만을 가질 수 있다.\n",
    "\n"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "a = True\n",
    "print(type(a))\n",
    "a = False\n",
    "print(type(a))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### list형\n",
    "* 리스트(list)를 사용하면 숫자나 단어 모음을 다음과 같이 간단하게 표현할 수 있다.\n",
    "> list와 관련한 함수는 다음 링크를 참고하세요 :D [Link](https://wikidocs.net/14)"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "a = [1, 'Hello', '1.2']\n",
    "print(type(a))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### tuple형\n",
    "* 튜플(tuple)은 몇 가지 점을 제외하곤 리스트와 거의 비슷하며 리스트와 다른 점은 다음과 같다.\n",
    " 1. 리스트는 [ ]으로 둘러싸지만 튜플은 ( )으로 둘러싼다.\n",
    " 2. 리스트는 그 값의 생성, 삭제, 수정이 가능하지만 튜플은 그 값을 바꿀 수 없다.\n"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "a = (1, 'Hello', '1.2')\n",
    "print(type(a))\n",
    "a[0] = 3\n",
    "# 에러 발생!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### dictionary형\n",
    "* Key와 Value의 쌍 여러 개가 { }로 둘러싸여 있다. 각각의 요소는 Key : Value 형태로 이루어져 있고 쉼표(,)로 구분되어 있다."
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "dic = {'name':'pey', 'phone':'0119993323', 'birth': '1118'}\n",
    "dic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 기본 연산자(+,-,*,/) 살펴보기"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "a = 5\n",
    "b = 3\n",
    "print(a + b)\n",
    "print(a - b)\n",
    "print(a * b)\n",
    "print(a / b)\n",
    "print(a % b)\n",
    "print(a // b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 주석(Comment)\n",
    "* 코드 영향을 미치지 않음"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "# 한 줄 주석\n",
    "\n",
    "\"\"\"\n",
    "여러 줄\n",
    "주석 예시\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Markdown \n",
    "\n",
    "* Markdown은 문서 작성을 지원하는 태그(Tag) 형식의 문법이다.\n",
    "> What is Markdown? (출처 - 위키백과)\n",
    "마크다운(markdown)은 일반 텍스트 문서의 양식을 편집하는 문법이다. README 파일이나 온라인 문서, 혹은 일반 텍스트 편집기로 문서 양식을 편집할 때 쓰인다. 마크다운을 이용해 작성된 문서는 쉽게 HTML 등 다른 문서형태로 변환이 가능하다."
   ]
  },
  {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Markdown 작성 방법\n",
    "![image.png](attachment:image.png)\n",
    "\n",
    "> Markdown 연습 및 문법 [Link](https://dooray.com/htmls/guides/markdown_ko_KR.html)"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "# 마크다운\n",
    "## 연습해보기\n",
    "---\n",
    "* markdown\n",
    " - 연습\n",
    "* code를 눌러서\n",
    " - __바꿔보세요!__\n",
    "> Basic 화이팅!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### if 조건문\n",
    "* 프로그래밍에서 조건을 판단하여 해당 조건에 맞는 상황을 수행하는 데 쓰는 것이 바로 if문이다.\n",
    "\n",
    "\n",
    "* 아래는 if와 else를 사용한 조건문의 기본 구조이다\n",
    "```python\n",
    "if 조건문:\n",
    "    수행할 문장1\n",
    "    수행할 문장2\n",
    "    ...\n",
    "elif 조건문:\n",
    "    수행할 문장a\n",
    "    수행할 문장b\n",
    "    ...\n",
    "else:\n",
    "    수행할 문장A\n",
    "    수행할 문장B\n",
    "    ...\n",
    "```\n",
    "* __들여쓰기를 하지 않으면 오류가 발생한다__"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {
    "scrolled": true
   },
   "source": [
    "money = 2000\n",
    "card = True\n",
    "if money >= 3000 or card:\n",
    "     print(\"택시를 타고 가라\")\n",
    "else:\n",
    "     print(\"걸어가라\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### for 반복문\n",
    "* for문의 기본 구조는 다음과 같다.\n",
    "```python\n",
    "for 변수 in 리스트(또는 튜플, 문자열) 혹은 range():\n",
    "    수행할 문장1\n",
    "    수행할 문장2\n",
    "    ...\n",
    "```"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "test_list = ['one', 'two', 'three'] \n",
    "for i in test_list: \n",
    "     print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "for i in range(10): \n",
    "     print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 함수\n",
    "* 파이썬 함수의 구조는 다음과 같다.\n",
    "\n",
    "```python\n",
    "def add(a, b): \n",
    "    return a + b\n",
    "```\n",
    "\n",
    "* def는 함수를 만들 때 사용하는 예약어이며, 함수 이름은 함수를 만드는 사람이 임의로 만들 수 있다. 함수 이름 뒤 괄호 안의 매개변수는 이 함수에 입력으로 전달되는 값을 받는 변수이다. 이렇게 함수를 정의한 다음 if, while, for문 등과 마찬가지로 함수에서 수행할 문장을 입력한다.\n",
    "\n"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "def add(a, b): \n",
    "    return a + b\n",
    "add(1, 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### lambda\n",
    "* lambda는 함수를 생성할 때 사용하는 예약어로 def와 동일한 역할을 한다. 보통 함수를 한줄로 간결하게 만들 때 사용한다. 우리말로는 \"람다\"라고 읽고 def를 사용해야 할 정도로 복잡하지 않거나 def를 사용할 수 없는 곳에 주로 쓰인다.\n",
    "\n",
    "```python\n",
    "add = lambda a, b: a+b\n",
    "result = add(3, 4)\n",
    "print(result)\n",
    "```\n",
    "* add는 두 개의 인수를 받아 서로 더한 값을 돌려주는 lambda 함수이다. 위 예제는 def를 사용한 다음 함수와 하는 일이 완전히 동일하다."
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "add = lambda a, b: a+b\n",
    "result = add(3, 4)\n",
    "print(result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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