D05 NumPy 統計函式 Universal Functions (ufunc) 作業題目.ipynb

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    "作業目標<br>\n",
    "計算有缺失值的資料，統計量實作<br>\n",
    "作業重點<br>\n",
    "當遇到缺失值有函式可以處理，不須額外寫程式刪除<br>\n",
    "計算統計量時不能出現缺失值"
   ]
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   "source": [
    "題目:<br>\n",
    "english_score = np.array([55,89,76,65,48,70])<br>\n",
    "math_score = np.array([60,85,60,68,np.nan,60])<br>\n",
    "chinese_score = np.array([65,90,82,72,66,77])<br>\n",
    "上3列共六位同學的英文、數學、國文成績，第一個元素代表第一位同學，舉例第一位同學英文55分、數學60分、國文65分，今天第五位同學因某原因沒來考試，導致數學成績缺值，運用上列數據回答下列問題。<br>\n",
    "1. 請計算各科成績平均、最大值、最小值、標準差，其中數學缺一筆資料可忽略?\n",
    "2. 第五位同學補考數學後成績為55，請計算補考後數學成績平均、最大值、最小值、標準差?\n",
    "3. 用補考後資料找出與國文成績相關係數最高的學科?"
   ]
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   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
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     "text": [
      "[55 89 76 65 48 70]\n",
      "[60. 85. 60. 68. nan 60.]\n",
      "[65 90 82 72 66 77]\n"
     ]
    }
   ],
   "source": [
    "english_score = np.array([55,89,76,65,48,70])\n",
    "math_score = np.array([60,85,60,68,np.nan,60])\n",
    "chinese_score = np.array([65,90,82,72,66,77])\n",
    "\n",
    "print(english_score)\n",
    "print(math_score)\n",
    "print(chinese_score)"
   ]
  },
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     "text": [
      "英文平均: 67.17 英文最大值: 89 英文最小值: 48 英文標準差: 13.43\n"
     ]
    }
   ],
   "source": [
    "#1. 請計算各科成績平均、最大值、最小值、標準差，其中數學缺一筆資料可忽略?\n",
    "print(\"英文平均: %.2f\" % np.mean(english_score),\n",
    "      \"英文最大值: %d\" % np.max(english_score),\n",
    "      \"英文最小值: %d\" % np.min(english_score), \n",
    "      \"英文標準差: %.2f\" % np.std(english_score))"
   ]
  },
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   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "數學平均: 66.60 數學最大值: 85 數學最小值: 60 數學標準差: 9.71\n"
     ]
    }
   ],
   "source": [
    "print(\"數學平均: %.2f\" % np.nanmean(math_score),\n",
    "      \"數學最大值: %d\" % np.nanmax(math_score),\n",
    "      \"數學最小值: %d\" % np.nanmin(math_score), \n",
    "      \"數學標準差: %.2f\" % np.nanstd(math_score))"
   ]
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   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "國文平均: 75.33 國文最大值: 90 國文最小值: 65 國文標準差: 8.83\n"
     ]
    }
   ],
   "source": [
    "print(\"國文平均: %.2f\" % np.mean(chinese_score),\n",
    "      \"國文最大值: %d\" % np.max(chinese_score),\n",
    "      \"國文最小值: %d\" % np.min(chinese_score), \n",
    "      \"國文標準差: %.2f\" % np.std(chinese_score))"
   ]
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   "execution_count": 26,
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     "data": {
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       "array([60., 85., 60., 68., 55., 60.])"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#2. 第五位同學補考數學後成績為55，請計算補考後數學成績平均、最大值、最小值、標準差?\n",
    "math_score[4] = 55\n",
    "math_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "數學平均: 64.67 數學最大值: 85 數學最小值: 55 數學標準差: 9.86\n"
     ]
    }
   ],
   "source": [
    "print(\"數學平均: %.2f\" % np.mean(math_score),\n",
    "      \"數學最大值: %d\" % np.max(math_score),\n",
    "      \"數學最小值: %d\" % np.min(math_score), \n",
    "      \"數學標準差: %.2f\" % np.std(math_score))"
   ]
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   "outputs": [],
   "source": [
    "#3. 用補考後資料找出與國文成績相關係數最高的學科?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
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    {
     "name": "stdout",
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     "text": [
      "[[1.         0.97792828]\n",
      " [0.97792828 1.        ]]\n",
      "[[1.         0.74056803]\n",
      " [0.74056803 1.        ]]\n"
     ]
    }
   ],
   "source": [
    "CE = np.corrcoef(chinese_score, english_score)\n",
    "print(CE)\n",
    "\n",
    "CM = np.corrcoef(chinese_score, math_score)\n",
    "print(CM)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "source": [
    "關係數最高的學科...英文"
   ]
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