22 - List ชุดข้อมูลแบบรายการ.ipynb

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    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![list.png](attachment:list.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1) `list` ชุดข้อมูลแบบรายการ"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`list` เป็นชุดข้อมูลที่มีการเก็บข้อมูลด้วยตำแหน่งของข้อมูล ซึ่งสิ่งที่ใช้ระบุข้อมูลจะถูกเรียกว่า `index` โดยตำแหน่งของข้อมูลจะเริ่มที่ 0 เสมอ"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2) สร้าง `list`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "สร้าง `list` ที่ไม่บรรจุ `object` ใดๆ ไว้"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3) ใส่ข้อมูลใน `list`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ใน `list` สามารถใส่ `object` ประเภทใด กี่ `object` ก็ได้โดยให้แต่ละ `object` แบ่งกันด้วย `,`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['strint', 10, 10.0]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "['strint',10,10.0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4) ดึงข้อมูลด้วยตำแหน่ง Indexing\n",
    "เราสามารถเรียกข้อมูลใน `list` ด้วยการใช้ Indexing และ Slicing ใน ลักษณะเดียวกันกับ Strings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[1,2,3][0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5) ดึงข้อมูลเป็นช่วงแบบ slicing\n",
    "เราสามารถเรียกข้อมูลใน `list` ด้วยการใช้ Indexing และ Slicing ใน ลักษณะเดียวกันกับ Strings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[2, 3]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[1,2,3][1:3]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6) การรวม `list` ด้วยการ `+`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3, 4]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[1,2,3] + [4]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7) `list` `methods` คำสั่งที่ใช้บ่อย"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "สร้างตัวแปรเก็บ `list` ตัวอย่าง"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "list1 = [1,2,3]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 8) `.append()` คำสั่งใส่ `input` เข้าไปใน `list`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "list1.append('append me!')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3, 'append me!']"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 9) `.pop()` คำสั่งเอา `object` ออกจาก `list` โดยการระบุ `index` ใน `input`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`.pop()` ให้ `output` เป็น `object` ที่ถูกนำออกจาก `list`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'append me!'"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list1.pop(-1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`.pop()` ยังนำ `object` ออกจาก `list` ด้วย"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ติดต่อเราได้ที่\n",
    "\n",
    "Facebook  : www.facebook.com/ultimatepython\n",
    "\n",
    "Website   : www.ultimatepython.com\n",
    "\n",
    "Messenger : www.m.me/ultimatepython"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
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