Python Basics 101 - Functions.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "a9534f3a",
   "metadata": {},
   "source": [
    "# Functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1bb8a257",
   "metadata": {},
   "outputs": [],
   "source": [
    "def first_func():\n",
    "    print('We did it!')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5f75cf9f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We did it!\n"
     ]
    }
   ],
   "source": [
    "first_func()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "375847c2",
   "metadata": {},
   "outputs": [],
   "source": [
    "def number_squared(number):\n",
    "    print(number**2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "98255c7b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "25\n"
     ]
    }
   ],
   "source": [
    "number_squared(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f23de228",
   "metadata": {},
   "outputs": [],
   "source": [
    "def number_squared_cust(number,power):\n",
    "    print(number**power)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "d956bb39",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "125\n"
     ]
    }
   ],
   "source": [
    "number_squared_cust(5,3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ad75e5e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "args_tuple = (5,6,1,2,8)\n",
    "\n",
    "def number_args(*number):\n",
    "    print(number[0]*number[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "8c6f83d0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "30\n"
     ]
    }
   ],
   "source": [
    "number_args(*args_tuple)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "7bb8dc07",
   "metadata": {},
   "outputs": [],
   "source": [
    "def number_squared_cust(number,power):\n",
    "    print(number**power)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "de070529",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "243\n"
     ]
    }
   ],
   "source": [
    "number_squared_cust(power = 5,number = 3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "af5b85a9",
   "metadata": {},
   "outputs": [],
   "source": [
    "def number_kwarg(**number):\n",
    "    print('My number is: ' + number['integer'] + 'My other number: ' + number['integer2'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "7d2bc5e8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "My number is: 2309My other number: 349\n"
     ]
    }
   ],
   "source": [
    "number_kwarg(integer = '2309', integer2 = '349')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "41126532",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "11b65aea",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c28bdd56",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f81e1140",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "attachments": {
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"
    }
   },
   "cell_type": "markdown",
   "id": "619887d5",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}