單元1 Python 資料分析主流環境 Jupyter.ipynb

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    "# 單元1. Python 資料分析主流環境 Jupyter"
   ]
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    "## 1-1 魔術指令\n",
    "\n",
    "在 Jupyter 中有許多「魔術指令」, 讓我們更方便的用 Python! 每個魔術指令就是用百分比符號開始, 我們介紹第一個非常有用的\n",
    "\n",
    "    %cd 資料夾路徑\n",
    "    \n",
    "熟悉指令列的就知道這就會進入指定資料夾。\n",
    "\n",
    "接著我們把標準資料分析主要套件讀進來, 唯一要說明的大概是\n",
    "\n",
    "    %matplotlib inline\n",
    "\n",
    "這是說之後畫出的圖, 直接在我們 Jupyter Notebook 的網頁中呈現出來!"
   ]
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    "這裡的\n",
    "\n",
    "* `numpy` 是數值計算的標準套件\n",
    "* `matplotlib.pyplot` 是用來畫圖的\n",
    "* `pandas` 可以說像是 Python 中的 Excel\n",
    "\n",
    "更重要的是, 雖然沒有規定, 但我們引用法都是「標準」引用法。這樣引用會讓人覺得你果然是行家。"
   ]
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   "source": [
    "### 【技巧】\n",
    "\n",
    "比 `%` 更炫 (更危險) 的是 `!`, 這可以直接執行系統命令列指令!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 【技巧】\n",
    "\n",
    "善用 Tab 鍵補完!"
   ]
  },
  {
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   "metadata": {},
   "source": [
    "## 1-2 自由方便的試驗場"
   ]
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   "source": [
    "還可以取好高級的亂數, 從平均數 0, 標準差 1 的常態分佈中取出 n 個數字。\n",
    "\n",
    "    randn(n)"
   ]
  },
  {
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   "source": [
    "當然可以直接畫出來。"
   ]
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    "`plot` 標準用法就是把 \n",
    "\n",
    "$$(x_1, y_1), (x_2, y_2), \\ldots (x_n, y_n)$$\n",
    "\n",
    "幾個點點上, 用線段連起來 (也就是折線圖)。指令的下法是把 x, y 座標分別收集起來:\n",
    "\n",
    "$$x = [x_1, x_2, \\ldots, x_n]$$\n",
    "\n",
    "$$y = [y_1, y_2, \\ldots, y_n]$$\n",
    "\n",
    "然後用\n",
    "\n",
    "    plot(x,y)\n",
    "    \n",
    "畫出來。"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "例如, 我們要畫出 (-2, 3), (1, -5), (2.7, 6), (3.3, 0) 幾個點連成的折線圖。"
   ]
  },
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   "source": [
    "### 【技巧】 `zip` 和 `upzip`\n",
    "\n",
    "有時我們這種\n",
    "\n",
    "$$x = [x_1, x_2, \\ldots, x_n]$$\n",
    "\n",
    "$$y = [y_1, y_2, \\ldots, y_n]$$\n",
    "\n",
    "表示的資料, 想換成\n",
    "\n",
    "$$(x_1, y_1), (x_2, y_2), \\ldots (x_n, y_n)$$\n",
    "\n",
    "這要怎麼做呢?"
   ]
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    "是不是很簡單? 再來如果我們本來是上面這種形式的資料, 怎麼把 x, y 座標分開呢? 非常神的居然還是 `zip`!"
   ]
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   "source": [
    "所以..."
   ]
  },
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    "## 1-3 親切的輔助系統\n",
    "\n",
    "* Tab 補完神鍵\n",
    "* 函數打完不知怎麼用, 可以按\n",
    "\n",
    "![Shift-Tab](images/shift_tab.png)"
   ]
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   "source": [
    "## 1-4 用 Markdown 做筆記\n",
    "\n",
    "Cell 可以選 `Markdown` 模式, 就可以用 `Markdown` 語法做筆記。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 【重點】標題\n",
    "\n",
    "`# 最大標題`\n",
    "# 最大標題\n",
    "\n",
    "`## 副標題`\n",
    "## 副標題\n",
    "\n",
    "..."
   ]
  },
  {
   "cell_type": "code",
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    "collapsed": true
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   "source": [
    "### 【重點】分點說明\n",
    "\n",
    "我們要學以下幾個套件:\n",
    "\n",
    "* `matplotlib`\n",
    "* `numpy`\n",
    "* `pandas`\n",
    "* `scikit-learn`"
   ]
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   "source": [
    "### 【重點】程式碼\n",
    "\n",
    "顯示程式碼有幾種方式。\n",
    "\n",
    "#### [1] 前面有若干空白\n",
    "\n",
    "    for i in range(10):\n",
    "        print(i)\n",
    "        \n",
    "#### [2] 內文可以用斜引號\n",
    "\n",
    "    `matplotlib`\n",
    "    \n",
    "#### [3] 還可以用 3 個引號外加語言\n",
    "\n",
    "    ```python\n",
    "    for i in range(10):\n",
    "        print(i)\n",
    "    ```\n",
    "\n",
    "```python\n",
    "for i in range(10):\n",
    "    print(i)\n",
    "```"
   ]
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   "source": [
    "### 【重點】插入網頁\n",
    "\n",
    "格式如下\n",
    "\n",
    "    [網頁名稱](URL)\n",
    "    \n",
    "例如\n",
    "\n",
    "    [炎龍老師的網頁](http://yenlung.km.nccu.edu.tw)\n",
    "    \n",
    "結果: [炎龍老師的網頁](http://yenlung.km.nccu.edu.tw)"
   ]
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 【重點】插入圖片\n",
    "\n",
    "    ![圖片名稱](圖片路徑)\n",
    "    \n",
    "例如\n",
    "\n",
    "    ![Happy Python](images/happy_python.png)\n",
    "    \n",
    "![Happy Python](images/happy_python.png)"
   ]
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  {
   "cell_type": "code",
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  {
   "cell_type": "markdown",
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   "source": [
    "### 【重點】輸入數學符號\n",
    "\n",
    "支援 LaTeX 指令。\n",
    "\n",
    "#### 隨文模式\n",
    "\n",
    "例如\n",
    "\n",
    "    設我們有函數 $f(x) = x^3 - 2x + 5$。\n",
    "    \n",
    "[結果] 設我們有函數 $f(x) = x^3 - 2x + 5$。\n",
    "\n",
    "#### 展式模式\n",
    "\n",
    "例如\n",
    "\n",
    "    $$\\int_a^b f(x) \\, dx$$\n",
    "\n",
    "$$\\int_a^b f(x) \\, dx$$"
   ]
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   "source": [
    "## 1-5 超炫的互動\n",
    "\n",
    "Jupyter Notebook 的互動模式, 提供非常好的科學計算 GUI 實驗場!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 定義一個函數, 就能互動!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
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  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 【範例】數值滑桿"
   ]
  },
  {
   "cell_type": "code",
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   "source": [
    "也可以是浮點數。"
   ]
  },
  {
   "cell_type": "code",
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "還可以設範圍。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   },
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  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 【範例】文字框"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
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  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 【範例】下拉式選單之一"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 【範例】下拉式選單之二"
   ]
  },
  {
   "cell_type": "code",
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   "cell_type": "markdown",
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   "source": [
    "### 【例子】會跑的蟲\n",
    "\n",
    "順便示範怎麼樣設預設值。"
   ]
  },
  {
   "cell_type": "code",
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 【例子】視覺化的互動\n",
    "\n",
    "記得要加 `plt.show()`, 畫圖指令之後會學。"
   ]
  },
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