Data Structure Overview.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "________________________________________________________________________________________________________________________\n",
    "\n",
    "\n",
    "* Yuvraj Sutar \n",
    "* yuvrajsutar009@gmail.com\n",
    "_ _________________________________________________________________________________________________________________________\n",
    "_  _________________________________________________________________________________________________________________________"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Structure Overview:\n",
    "    "
   ]
  },
  {
   "attachments": {
    "datatype1.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![datatype1.png](attachment:datatype1.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 1-List: It is similar to array the data elements can be of different data types.\n",
    "    \n",
    "- 2-Tuple: similar to lists but they are immutable which means the values in a tuple cannot be modified they can only be read.\n",
    "    \n",
    "- 3-Dictionary: The dictionary contains Key-value pairs as its data elements.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Key Points to Remember\n",
    "\n",
    "- Mutable-can change or update after declaration e.g. list, mutable set, dictionary\n",
    "- Immutable-can't change or update after declaration e.g. number,string,tuple\n",
    "- Ordered Sequences-Indexes starting from 0 e.g. string,list,tuple\n",
    "- unordered dequences-Indexes does't start with 0 e.g set & dictionary\n",
    "- Hashable-Can access values from their indices\n",
    "- Unhashable-Can't access values from their indices e.g. Numbers,sets"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "________________________________________________________________________________________________________________________\n",
    "\n",
    "\n",
    "* Yuvraj Sutar \n",
    "* yuvrajsutar009@gmail.com\n",
    "_ _________________________________________________________________________________________________________________________\n",
    "_  _________________________________________________________________________________________________________________________"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}