2. 넘파이 기본 사용법.ipynb

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   "source": [
    "import numpy as np"
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   "cell_type": "markdown",
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   "source": [
    "## 파이썬의 리스트"
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    "number_1 + number_2"
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   "source": [
    "## 넘파이의 기본 연산"
   ]
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    "np.array(number_1) + np.array(number_2)"
   ]
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.add(number_1, number_2)"
   ]
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
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   "source": [
    "np.subtract(number_1, number_2)"
   ]
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.multiply(number_1, number_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.divide(number_1, number_2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 넘파이를 통한 기술통계"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
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    "number = np.array([[1, 2, 3], \n",
    "                   [4, 5, 6]])\n",
    "number"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 행열의 크기\n",
    "number.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 최솟값\n",
    "np.min(number)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 최댓값\n",
    "np.max(number)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 평균 \n",
    "np.mean(number)"
   ]
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 중앙값\n",
    "np.median(number)"
   ]
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 분산\n",
    "number_var = np.var(number)\n",
    "number_var"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 표준편차 - 분산에 root를 취함\n",
    "np.sqrt(number_var)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 표준편차\n",
    "np.std(number)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 합계\n",
    "np.sum(number)"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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   "cell_type": "code",
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