2. 创建数据集.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2.1 数据集的概念"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "R中有许多用于存储数据的结构，包括标量、向量、数组、数据框和列表\n",
    "\n",
    "R可以处理的数据类型（模式）包括数值型、字符型、逻辑型（TRUE/FALSE）、复数型（虚\n",
    "数）和原生型（字节）。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2.2 数据结构"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![R中的数据结构](./image/R中的数据结构.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![一些定义.jpg](./image/一些定义.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.2.1 向量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Your code contains a unicode char which cannot be displayed in your\n",
      "current locale and R will silently convert it to an escaped form when the\n",
      "R kernel executes this code. This can lead to subtle errors if you use\n",
      "such chars to do comparisons. For more information, please see\n",
      "https://github.com/IRkernel/repr/wiki/Problems-with-unicode-on-windows"
     ]
    }
   ],
   "source": [
    "a <- c(1, 2, 5, 3, 6, -2, 4)  #数值型向量\n",
    "b <- c(\"one\", \"two\", \"three\")  #字符型向量\n",
    "c <- c(TRUE, TRUE, TRUE, FALSE, TRUE, FALSE)  #逻辑型向量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Your code contains a unicode char which cannot be displayed in your\n",
      "current locale and R will silently convert it to an escaped form when the\n",
      "R kernel executes this code. This can lead to subtle errors if you use\n",
      "such chars to do comparisons. For more information, please see\n",
      "https://github.com/IRkernel/repr/wiki/Problems-with-unicode-on-windows"
     ]
    },
    {
     "data": {
      "text/html": [
       "'h'"
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       "'h'"
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      "text/markdown": [
       "'h'"
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      "text/plain": [
       "[1] \"h\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "a <- c(\"k\", \"j\", \"h\", \"a\", \"c\", \"m\")\n",
    "a[3]  #访问第二个元素"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Your code contains a unicode char which cannot be displayed in your\n",
      "current locale and R will silently convert it to an escaped form when the\n",
      "R kernel executes this code. This can lead to subtle errors if you use\n",
      "such chars to do comparisons. For more information, please see\n",
      "https://github.com/IRkernel/repr/wiki/Problems-with-unicode-on-windows"
     ]
    },
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>'k'</li>\n",
       "\t<li>'h'</li>\n",
       "\t<li>'c'</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'k'\n",
       "\\item 'h'\n",
       "\\item 'c'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'k'\n",
       "2. 'h'\n",
       "3. 'c'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] \"k\" \"h\" \"c\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "a[c(1,3,5)]  #访问地二个和第四个元素"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Your code contains a unicode char which cannot be displayed in your\n",
      "current locale and R will silently convert it to an escaped form when the\n",
      "R kernel executes this code. This can lead to subtle errors if you use\n",
      "such chars to do comparisons. For more information, please see\n",
      "https://github.com/IRkernel/repr/wiki/Problems-with-unicode-on-windows"
     ]
    },
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>'j'</li>\n",
       "\t<li>'h'</li>\n",
       "\t<li>'a'</li>\n",
       "\t<li>'c'</li>\n",
       "\t<li>'m'</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'j'\n",
       "\\item 'h'\n",
       "\\item 'a'\n",
       "\\item 'c'\n",
       "\\item 'm'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'j'\n",
       "2. 'h'\n",
       "3. 'a'\n",
       "4. 'c'\n",
       "5. 'm'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] \"j\" \"h\" \"a\" \"c\" \"m\""
      ]
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     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "a[2:6] #访问第二个到第6个元素"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.2.2 矩阵"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "矩阵是一个二维数组，只是每个元素都拥有相同的模式（数值型、字符型或逻辑型）。可通过函数matrix()创建矩阵。一般使用格式为：\n",
    "\n",
    "myymatrix <- matrix(vector, nrow=number_of_rows, ncol=number_of_columns,byrow=logical_value, dimnames=list(char_vector_rownames,char_vector_colnames))\n",
    "\n",
    "vector包含了矩阵的元素，\n",
    "\n",
    "nrow和ncol用以指定行和列的维数，\n",
    "\n",
    "dimnames包含了可选的、以字符型向量表示的行名和列名。\n",
    "\n",
    "选项byrow则表明矩阵应当按行填充（byrow=TRUE）还是按列填充（byrow=FALSE），默认情况下按列填充。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Your code contains a unicode char which cannot be displayed in your\n",
      "current locale and R will silently convert it to an escaped form when the\n",
      "R kernel executes this code. This can lead to subtle errors if you use\n",
      "such chars to do comparisons. For more information, please see\n",
      "https://github.com/IRkernel/repr/wiki/Problems-with-unicode-on-windows"
     ]
    },
    {
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       "<table>\n",
       "<tbody>\n",
       "\t<tr><td>1 </td><td> 6</td><td>11</td><td>16</td></tr>\n",
       "\t<tr><td>2 </td><td> 7</td><td>12</td><td>17</td></tr>\n",
       "\t<tr><td>3 </td><td> 8</td><td>13</td><td>18</td></tr>\n",
       "\t<tr><td>4 </td><td> 9</td><td>14</td><td>19</td></tr>\n",
       "\t<tr><td>5 </td><td>10</td><td>15</td><td>20</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
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       "\\begin{tabular}{llll}\n",
       "\t 1  &  6 & 11 & 16\\\\\n",
       "\t 2  &  7 & 12 & 17\\\\\n",
       "\t 3  &  8 & 13 & 18\\\\\n",
       "\t 4  &  9 & 14 & 19\\\\\n",
       "\t 5  & 10 & 15 & 20\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| 1  |  6 | 11 | 16 |\n",
       "| 2  |  7 | 12 | 17 |\n",
       "| 3  |  8 | 13 | 18 |\n",
       "| 4  |  9 | 14 | 19 |\n",
       "| 5  | 10 | 15 | 20 |\n",
       "\n"
      ],
      "text/plain": [
       "     [,1] [,2] [,3] [,4]\n",
       "[1,] 1     6   11   16  \n",
       "[2,] 2     7   12   17  \n",
       "[3,] 3     8   13   18  \n",
       "[4,] 4     9   14   19  \n",
       "[5,] 5    10   15   20  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y <- matrix(1:20, nrow=5, ncol=4) #创建一个5*4的矩阵\n",
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>C1</th><th scope=col>C2</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>R1</th><td> 1</td><td>26</td></tr>\n",
       "\t<tr><th scope=row>R2</th><td>24</td><td>68</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ll}\n",
       "  & C1 & C2\\\\\n",
       "\\hline\n",
       "\tR1 &  1 & 26\\\\\n",
       "\tR2 & 24 & 68\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| <!--/--> | C1 | C2 |\n",
       "|---|---|---|\n",
       "| R1 |  1 | 26 |\n",
       "| R2 | 24 | 68 |\n",
       "\n"
      ],
      "text/plain": [
       "   C1 C2\n",
       "R1  1 26\n",
       "R2 24 68"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cells <- c(1,26,24,68) \n",
    "rnames <- c(\"R1\", \"R2\")\n",
    "cnames <- c(\"C1\", \"C2\")\n",
    "mymatrix <- matrix(cells, nrow=2, ncol=2, byrow=TRUE,dimnames=list(rnames, cnames)) #按行填充的2*2矩阵\n",
    "mymatrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Your code contains a unicode char which cannot be displayed in your\n",
      "current locale and R will silently convert it to an escaped form when the\n",
      "R kernel executes this code. This can lead to subtle errors if you use\n",
      "such chars to do comparisons. For more information, please see\n",
      "https://github.com/IRkernel/repr/wiki/Problems-with-unicode-on-windows"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>C1</th><th scope=col>C2</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>R1</th><td> 1</td><td>24</td></tr>\n",
       "\t<tr><th scope=row>R2</th><td>26</td><td>68</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ll}\n",
       "  & C1 & C2\\\\\n",
       "\\hline\n",
       "\tR1 &  1 & 24\\\\\n",
       "\tR2 & 26 & 68\\\\\n",
       "\\end{tabular}\n"
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      "text/markdown": [
       "\n",
       "| <!--/--> | C1 | C2 |\n",
       "|---|---|---|\n",
       "| R1 |  1 | 24 |\n",
       "| R2 | 26 | 68 |\n",
       "\n"
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       "   C1 C2\n",
       "R1  1 24\n",
       "R2 26 68"
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     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mymatrix <- matrix(cells, nrow=2, ncol=2, byrow=FALSE,dimnames=list(rnames, cnames)) #按列填充的2*2矩阵\n",
    "mymatrix"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 使用下标和方括号来选择矩阵中的行、列或元素"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<tbody>\n",
       "\t<tr><td>1 </td><td>3 </td><td>5 </td><td>7 </td><td> 9</td></tr>\n",
       "\t<tr><td>2 </td><td>4 </td><td>6 </td><td>8 </td><td>10</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
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      "text/latex": [
       "\\begin{tabular}{lllll}\n",
       "\t 1  & 3  & 5  & 7  &  9\\\\\n",
       "\t 2  & 4  & 6  & 8  & 10\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| 1  | 3  | 5  | 7  |  9 |\n",
       "| 2  | 4  | 6  | 8  | 10 |\n",
       "\n"
      ],
      "text/plain": [
       "     [,1] [,2] [,3] [,4] [,5]\n",
       "[1,] 1    3    5    7     9  \n",
       "[2,] 2    4    6    8    10  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x <- matrix(1:10, nrow=2)\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>2</li>\n",
       "\t<li>4</li>\n",
       "\t<li>6</li>\n",
       "\t<li>8</li>\n",
       "\t<li>10</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 2\n",
       "\\item 4\n",
       "\\item 6\n",
       "\\item 8\n",
       "\\item 10\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 2\n",
       "2. 4\n",
       "3. 6\n",
       "4. 8\n",
       "5. 10\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1]  2  4  6  8 10"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x[2,]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>3</li>\n",
       "\t<li>4</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 3\n",
       "\\item 4\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 3\n",
       "2. 4\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 3 4"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x[,2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "7"
      ],
      "text/latex": [
       "7"
      ],
      "text/markdown": [
       "7"
      ],
      "text/plain": [
       "[1] 7"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x[1,4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>7</li>\n",
       "\t<li>9</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 7\n",
       "\\item 9\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 7\n",
       "2. 9\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 7 9"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x[1, c(4,5)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.2.3 数组"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "数组可通过array函数创建，形式如下：\n",
    "\n",
    "myarray <- array(vector, dimensions, dimnames)\n",
    "\n",
    "vector包含了数组中的数据，\n",
    "\n",
    "dimensions是一个数值型向量，给出了各个维度下标的最大\n",
    "值，\n",
    "\n",
    "dimnames是可选的、各维度名称标签的列表"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Your code contains a unicode char which cannot be displayed in your\n",
      "current locale and R will silently convert it to an escaped form when the\n",
      "R kernel executes this code. This can lead to subtle errors if you use\n",
      "such chars to do comparisons. For more information, please see\n",
      "https://github.com/IRkernel/repr/wiki/Problems-with-unicode-on-windows"
     ]
    },
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>1</li>\n",
       "\t<li>2</li>\n",
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       "\\begin{enumerate*}\n",
       "\\item 1\n",
       "\\item 2\n",
       "\\item 3\n",
       "\\item 4\n",
       "\\item 5\n",
       "\\item 6\n",
       "\\item 7\n",
       "\\item 8\n",
       "\\item 9\n",
       "\\item 10\n",
       "\\item 11\n",
       "\\item 12\n",
       "\\item 13\n",
       "\\item 14\n",
       "\\item 15\n",
       "\\item 16\n",
       "\\item 17\n",
       "\\item 18\n",
       "\\item 19\n",
       "\\item 20\n",
       "\\item 21\n",
       "\\item 22\n",
       "\\item 23\n",
       "\\item 24\n",
       "\\end{enumerate*}\n"
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      "text/markdown": [
       "1. 1\n",
       "2. 2\n",
       "3. 3\n",
       "4. 4\n",
       "5. 5\n",
       "6. 6\n",
       "7. 7\n",
       "8. 8\n",
       "9. 9\n",
       "10. 10\n",
       "11. 11\n",
       "12. 12\n",
       "13. 13\n",
       "14. 14\n",
       "15. 15\n",
       "16. 16\n",
       "17. 17\n",
       "18. 18\n",
       "19. 19\n",
       "20. 20\n",
       "21. 21\n",
       "22. 22\n",
       "23. 23\n",
       "24. 24\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       ", , C1\n",
       "\n",
       "   B1 B2 B3\n",
       "A1  1  3  5\n",
       "A2  2  4  6\n",
       "\n",
       ", , C2\n",
       "\n",
       "   B1 B2 B3\n",
       "A1  7  9 11\n",
       "A2  8 10 12\n",
       "\n",
       ", , C3\n",
       "\n",
       "   B1 B2 B3\n",
       "A1 13 15 17\n",
       "A2 14 16 18\n",
       "\n",
       ", , C4\n",
       "\n",
       "   B1 B2 B3\n",
       "A1 19 21 23\n",
       "A2 20 22 24\n"
      ]
     },
     "metadata": {},
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   ],
   "source": [
    "#创建一个数组\n",
    "dim1 <- c(\"A1\", \"A2\")\n",
    "dim2 <- c(\"B1\", \"B2\", \"B3\")\n",
    "dim3 <- c(\"C1\", \"C2\", \"C3\", \"C4\")\n",
    "z <- array(1:24, c(2, 3, 4), dimnames=list(dim1, dim2, dim3))\n",
    "z"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "15"
      ],
      "text/latex": [
       "15"
      ],
      "text/markdown": [
       "15"
      ],
      "text/plain": [
       "[1] 15"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "z[1,2,3]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.2.4 数据框"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "数据框可通过函数data.frame()创建：\n",
    "\n",
    "mydata <- data.frame(col1, col2, col3,...)\n",
    "\n",
    "其中的列向量col1、col2、col3等可为任何类型（如字符型、数值型或逻辑型）。每一列的名称可由函数names指定。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Your code contains a unicode char which cannot be displayed in your\n",
      "current locale and R will silently convert it to an escaped form when the\n",
      "R kernel executes this code. This can lead to subtle errors if you use\n",
      "such chars to do comparisons. For more information, please see\n",
      "https://github.com/IRkernel/repr/wiki/Problems-with-unicode-on-windows"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>patientID</th><th scope=col>age</th><th scope=col>diabetes</th><th scope=col>status</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>1        </td><td>25       </td><td>Type1    </td><td>Poor     </td></tr>\n",
       "\t<tr><td>2        </td><td>34       </td><td>Type2    </td><td>Improved </td></tr>\n",
       "\t<tr><td>3        </td><td>28       </td><td>Type1    </td><td>Excellent</td></tr>\n",
       "\t<tr><td>4        </td><td>52       </td><td>Type1    </td><td>Poor     </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llll}\n",
       " patientID & age & diabetes & status\\\\\n",
       "\\hline\n",
       "\t 1         & 25        & Type1     & Poor     \\\\\n",
       "\t 2         & 34        & Type2     & Improved \\\\\n",
       "\t 3         & 28        & Type1     & Excellent\\\\\n",
       "\t 4         & 52        & Type1     & Poor     \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| patientID | age | diabetes | status |\n",
       "|---|---|---|---|\n",
       "| 1         | 25        | Type1     | Poor      |\n",
       "| 2         | 34        | Type2     | Improved  |\n",
       "| 3         | 28        | Type1     | Excellent |\n",
       "| 4         | 52        | Type1     | Poor      |\n",
       "\n"
      ],
      "text/plain": [
       "  patientID age diabetes status   \n",
       "1 1         25  Type1    Poor     \n",
       "2 2         34  Type2    Improved \n",
       "3 3         28  Type1    Excellent\n",
       "4 4         52  Type1    Poor     "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#创建一个数据框\n",
    "patientID <- c(1, 2, 3, 4)\n",
    "age <- c(25, 34, 28, 52)\n",
    "diabetes <- c(\"Type1\", \"Type2\", \"Type1\", \"Type1\")\n",
    "status <- c(\"Poor\", \"Improved\", \"Excellent\", \"Poor\")\n",
    "patientdata <- data.frame(patientID, age, diabetes, status)\n",
    "patientdata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Your code contains a unicode char which cannot be displayed in your\n",
      "current locale and R will silently convert it to an escaped form when the\n",
      "R kernel executes this code. This can lead to subtle errors if you use\n",
      "such chars to do comparisons. For more information, please see\n",
      "https://github.com/IRkernel/repr/wiki/Problems-with-unicode-on-windows"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>patientID</th><th scope=col>age</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>1 </td><td>25</td></tr>\n",
       "\t<tr><td>2 </td><td>34</td></tr>\n",
       "\t<tr><td>3 </td><td>28</td></tr>\n",
       "\t<tr><td>4 </td><td>52</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ll}\n",
       " patientID & age\\\\\n",
       "\\hline\n",
       "\t 1  & 25\\\\\n",
       "\t 2  & 34\\\\\n",
       "\t 3  & 28\\\\\n",
       "\t 4  & 52\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| patientID | age |\n",
       "|---|---|\n",
       "| 1  | 25 |\n",
       "| 2  | 34 |\n",
       "| 3  | 28 |\n",
       "| 4  | 52 |\n",
       "\n"
      ],
      "text/plain": [
       "  patientID age\n",
       "1 1         25 \n",
       "2 2         34 \n",
       "3 3         28 \n",
       "4 4         52 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#选取数据框中的元素\n",
    "patientdata[1:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>diabetes</th><th scope=col>status</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>Type1    </td><td>Poor     </td></tr>\n",
       "\t<tr><td>Type2    </td><td>Improved </td></tr>\n",
       "\t<tr><td>Type1    </td><td>Excellent</td></tr>\n",
       "\t<tr><td>Type1    </td><td>Poor     </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ll}\n",
       " diabetes & status\\\\\n",
       "\\hline\n",
       "\t Type1     & Poor     \\\\\n",
       "\t Type2     & Improved \\\\\n",
       "\t Type1     & Excellent\\\\\n",
       "\t Type1     & Poor     \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| diabetes | status |\n",
       "|---|---|\n",
       "| Type1     | Poor      |\n",
       "| Type2     | Improved  |\n",
       "| Type1     | Excellent |\n",
       "| Type1     | Poor      |\n",
       "\n"
      ],
      "text/plain": [
       "  diabetes status   \n",
       "1 Type1    Poor     \n",
       "2 Type2    Improved \n",
       "3 Type1    Excellent\n",
       "4 Type1    Poor     "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "patientdata[c(\"diabetes\", \"status\")]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>25</li>\n",
       "\t<li>34</li>\n",
       "\t<li>28</li>\n",
       "\t<li>52</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 25\n",
       "\\item 34\n",
       "\\item 28\n",
       "\\item 52\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 25\n",
       "2. 34\n",
       "3. 28\n",
       "4. 52\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 25 34 28 52"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "patientdata$age  #表示patientdata数据框中的变量age"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Your code contains a unicode char which cannot be displayed in your\n",
      "current locale and R will silently convert it to an escaped form when the\n",
      "R kernel executes this code. This can lead to subtle errors if you use\n",
      "such chars to do comparisons. For more information, please see\n",
      "https://github.com/IRkernel/repr/wiki/Problems-with-unicode-on-windows"
     ]
    },
    {
     "data": {
      "text/plain": [
       "       \n",
       "        Excellent Improved Poor\n",
       "  Type1         1        0    2\n",
       "  Type2         0        1    0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "table(patientdata$diabetes, patientdata$status) #生成糖尿病类型变量diabetes和patientdata的列联表"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 在每个变量名前都键入一次patientdata$可能会让人生厌，所以不妨走一些捷径。可以联合使用函数attach()和detach()或单独使用函数with()来简化代码"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. attach()、detach()和with()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Your code contains a unicode char which cannot be displayed in your\n",
      "current locale and R will silently convert it to an escaped form when the\n",
      "R kernel executes this code. This can lead to subtle errors if you use\n",
      "such chars to do comparisons. For more information, please see\n",
      "https://github.com/IRkernel/repr/wiki/Problems-with-unicode-on-windows"
     ]
    },
    {
     "data": {
      "text/plain": [
       "   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. \n",
       "  10.40   15.43   19.20   20.09   22.80   33.90 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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QAAQqjuUWxedDqdRqOJjIxUOghQjJQo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\nFStWREZG3rp1q0qVKp6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qZNmzIzM/Uu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\n",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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dgBAABIgrADAACQBGEH6Epubq7SIwAA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\nV640adJE/1Oh+MvMzNy7d6+Hh4fmSSsFDB06VK1W79q1S9dj9O3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uhB0AaFNycvLFixe7du1qZmZWePeDDz4QQhw5ckTvcwEoEQg7ANCm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\nIiHYAQBEQrADAIiEYAcAEAnBDgAgEv8BfK6sWg9FotIAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#summary(mtcars$mpg)\n",
    "#plot(mtcars$mpg, mtcars$disp)\n",
    "#plot(mtcars$mpg, mtcars$wt)\n",
    "#写成下面的代码：\n",
    "attach(mtcars) #将数据框添加到R的搜索路径中\n",
    "  summary(mpg)\n",
    "  plot(mpg, disp)\n",
    "  plot(mpg, wt)\n",
    "detach(mtcars)  #将数据框从搜索路径中移除"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Your code contains a unicode char which cannot be displayed in your\n",
      "current locale and R will silently convert it to an escaped form when the\n",
      "R kernel executes this code. This can lead to subtle errors if you use\n",
      "such chars to do comparisons. For more information, please see\n",
      "https://github.com/IRkernel/repr/wiki/Problems-with-unicode-on-windowsThe following object is masked _by_ .GlobalEnv:\n",
      "\n",
      "    mpg\n",
      "\n"
     ]
    },
    {
     "ename": "ERROR",
     "evalue": "Error in xy.coords(x, y, xlabel, ylabel, log): 'x' and 'y' lengths differ\n",
     "output_type": "error",
     "traceback": [
      "Error in xy.coords(x, y, xlabel, ylabel, log): 'x' and 'y' lengths differ\nTraceback:\n",
      "1. plot(mpg, wt)",
      "2. plot.default(mpg, wt)",
      "3. xy.coords(x, y, xlabel, ylabel, log)",
      "4. stop(\"'x' and 'y' lengths differ\")"
     ]
    }
   ],
   "source": [
    "mpg <- c(25, 36, 47)\n",
    "attach(mtcars)  #当名称相同的对象不止一个时，这种方法很局限。\n",
    "plot(mpg,wt)\n",
    "mpg  #，在数据框mtcars被绑定（attach）之前，你们的环境中已经有了一个名为mpg的对象。在这种情况下，原始对象将取得优先权，这与你们想要的结果有所出入。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Your code contains a unicode char which cannot be displayed in your\n",
      "current locale and R will silently convert it to an escaped form when the\n",
      "R kernel executes this code. This can lead to subtle errors if you use\n",
      "such chars to do comparisons. For more information, please see\n",
      "https://github.com/IRkernel/repr/wiki/Problems-with-unicode-on-windows"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. \n",
      "  10.40   15.43   19.20   20.09   22.80   33.90 \n"
     ]
    },
    {
     "data": {
      "image/png": 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QAAQqjuUWxedDqdRqOJjIxUOghQjJQo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\nFStWREZG3rp1q0qVKp6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qZNmzIzM/Uu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\n",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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dgBAABIgrADAACQBGEH6Epubq7SIwAA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\nV640adJE/1Oh+MvMzNy7d6+Hh4fmSSsFDB06VK1W79q1S9dj9O3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uhB0AaFNycvLFixe7du1qZmZWePeDDz4QQhw5ckTvcwEoEQg7ANCm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\nIiHYAQBEQrADAIiEYAcAEAnBDgAgEv8BfK6sWg9FotIAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#使用with()重写上面的例子\n",
    "with(mtcars, {\n",
    "print(summary(mpg))\n",
    "plot(mpg, disp)\n",
    "plot(mpg, wt)\n",
    "})\n",
    "#函数with()的局限性在于，赋值仅在此函数的括号内生效"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 如果你需要创建在with()结构以外存在的对象，使用特殊赋值符<<-替代标准赋值符（<-）即可，它可将对象保存到with()之外的全局环境中"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "with(mtcars, {\n",
    "nokeepstats <- summary(mpg)\n",
    "keepstats <<- summary(mpg)\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "ename": "ERROR",
     "evalue": "Error in eval(expr, envir, enclos): object 'nokeepstats' not found\n",
     "output_type": "error",
     "traceback": [
      "Error in eval(expr, envir, enclos): object 'nokeepstats' not found\nTraceback:\n"
     ]
    }
   ],
   "source": [
    "nokeepstats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. \n",
       "  10.40   15.43   19.20   20.09   22.80   33.90 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "keepstats"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. 实例标识符"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Your code contains a unicode char which cannot be displayed in your\n",
      "current locale and R will silently convert it to an escaped form when the\n",
      "R kernel executes this code. This can lead to subtle errors if you use\n",
      "such chars to do comparisons. For more information, please see\n",
      "https://github.com/IRkernel/repr/wiki/Problems-with-unicode-on-windows"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>patientID</th><th scope=col>age</th><th scope=col>diabetes</th><th scope=col>status</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>1        </td><td>25       </td><td>Type1    </td><td>Poor     </td></tr>\n",
       "\t<tr><td>2        </td><td>34       </td><td>Type2    </td><td>Improved </td></tr>\n",
       "\t<tr><td>3        </td><td>28       </td><td>Type1    </td><td>Excellent</td></tr>\n",
       "\t<tr><td>4        </td><td>52       </td><td>Type1    </td><td>Poor     </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llll}\n",
       " patientID & age & diabetes & status\\\\\n",
       "\\hline\n",
       "\t 1         & 25        & Type1     & Poor     \\\\\n",
       "\t 2         & 34        & Type2     & Improved \\\\\n",
       "\t 3         & 28        & Type1     & Excellent\\\\\n",
       "\t 4         & 52        & Type1     & Poor     \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| patientID | age | diabetes | status |\n",
       "|---|---|---|---|\n",
       "| 1         | 25        | Type1     | Poor      |\n",
       "| 2         | 34        | Type2     | Improved  |\n",
       "| 3         | 28        | Type1     | Excellent |\n",
       "| 4         | 52        | Type1     | Poor      |\n",
       "\n"
      ],
      "text/plain": [
       "  patientID age diabetes status   \n",
       "1 1         25  Type1    Poor     \n",
       "2 2         34  Type2    Improved \n",
       "3 3         28  Type1    Excellent\n",
       "4 4         52  Type1    Poor     "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#在R中，实例标识符（case identifier）可通过数据框操作函数中的rowname选项指定。\n",
    "patientdata <- data.frame(patientID, age, diabetes,status, row.names=patientID)\n",
    "patientdata"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.2.5 因子"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "类别（名义型）变量和有序类别（有序型）变量在R中称为因子（factor）。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Your code contains a unicode char which cannot be displayed in your\n",
      "current locale and R will silently convert it to an escaped form when the\n",
      "R kernel executes this code. This can lead to subtle errors if you use\n",
      "such chars to do comparisons. For more information, please see\n",
      "https://github.com/IRkernel/repr/wiki/Problems-with-unicode-on-windows"
     ]
    }
   ],
   "source": [
    "# 以向量形式输入数据\n",
    "patientID <- c(1, 2, 3, 4)  \n",
    "age <- c(25, 34, 28, 52)\n",
    "diabetes <- c(\"Type1\", \"Type2\", \"Type1\", \"Type1\")\n",
    "status <- c(\"Poor\", \"Improved\", \"Excellent\", \"Poor\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Your code contains a unicode char which cannot be displayed in your\n",
      "current locale and R will silently convert it to an escaped form when the\n",
      "R kernel executes this code. This can lead to subtle errors if you use\n",
      "such chars to do comparisons. For more information, please see\n",
      "https://github.com/IRkernel/repr/wiki/Problems-with-unicode-on-windows"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'data.frame':\t4 obs. of  4 variables:\n",
      " $ patientID: num  1 2 3 4\n",
      " $ age      : num  25 34 28 52\n",
      " $ diabetes : Factor w/ 2 levels \"Type1\",\"Type2\": 1 2 1 1\n",
      " $ status   : Ord.factor w/ 3 levels \"Excellent\"<\"Improved\"<..: 3 2 1 3\n"
     ]
    }
   ],
   "source": [
    "diabetes <- factor(diabetes)\n",
    "status <- factor(status, order=TRUE)\n",
    "patientdata <- data.frame(patientID, age, diabetes, status)\n",
    "str(patientdata)  #显示对象的结构"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Your code contains a unicode char which cannot be displayed in your\n",
      "current locale and R will silently convert it to an escaped form when the\n",
      "R kernel executes this code. This can lead to subtle errors if you use\n",
      "such chars to do comparisons. For more information, please see\n",
      "https://github.com/IRkernel/repr/wiki/Problems-with-unicode-on-windows"
     ]
    },
    {
     "data": {
      "text/plain": [
       "   patientID         age         diabetes       status \n",
       " Min.   :1.00   Min.   :25.00   Type1:3   Excellent:1  \n",
       " 1st Qu.:1.75   1st Qu.:27.25   Type2:1   Improved :1  \n",
       " Median :2.50   Median :31.00             Poor     :2  \n",
       " Mean   :2.50   Mean   :34.75                          \n",
       " 3rd Qu.:3.25   3rd Qu.:38.50                          \n",
       " Max.   :4.00   Max.   :52.00                          "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#显示对象的统计概要\n",
    "summary(patientdata)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.2.6 列表"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "列表（list）是R的数据类型中最为复杂的一种。一般来说，列表就是一些对象（或成分，component）的有序集合。列表允许你整合若干（可能无关的）对象到单个对象名下。例如，某个列表中可能是若干向量、矩阵、数据框，甚至其他列表的组合。可以使用函数list()创\n",
    "建列表：\n",
    "\n",
    "mylist <- list(object1, object2, ...)\n",
    "\n",
    "其中的对象可以是目前为止讲到的任何结构。你还可以为列表中的对象命名：\n",
    "\n",
    "mylist <- list(name1=object1, name2=object2, ...)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Your code contains a unicode char which cannot be displayed in your\n",
      "current locale and R will silently convert it to an escaped form when the\n",
      "R kernel executes this code. This can lead to subtle errors if you use\n",
      "such chars to do comparisons. For more information, please see\n",
      "https://github.com/IRkernel/repr/wiki/Problems-with-unicode-on-windows"
     ]
    },
    {
     "data": {
      "text/html": [
       "<dl>\n",
       "\t<dt>$title</dt>\n",
       "\t\t<dd>'My First List'</dd>\n",
       "\t<dt>$ages</dt>\n",
       "\t\t<dd><ol class=list-inline>\n",
       "\t<li>25</li>\n",
       "\t<li>26</li>\n",
       "\t<li>18</li>\n",
       "\t<li>39</li>\n",
       "</ol>\n",
       "</dd>\n",
       "\t<dt>[[3]]</dt>\n",
       "\t\t<dd><table>\n",
       "<tbody>\n",
       "\t<tr><td>1 </td><td> 6</td></tr>\n",
       "\t<tr><td>2 </td><td> 7</td></tr>\n",
       "\t<tr><td>3 </td><td> 8</td></tr>\n",
       "\t<tr><td>4 </td><td> 9</td></tr>\n",
       "\t<tr><td>5 </td><td>10</td></tr>\n",
       "</tbody>\n",
       "</table>\n",
       "</dd>\n",
       "\t<dt>[[4]]</dt>\n",
       "\t\t<dd><ol class=list-inline>\n",
       "\t<li>'one'</li>\n",
       "\t<li>'two'</li>\n",
       "\t<li>'three'</li>\n",
       "</ol>\n",
       "</dd>\n",
       "</dl>\n"
      ],
      "text/latex": [
       "\\begin{description}\n",
       "\\item[\\$title] 'My First List'\n",
       "\\item[\\$ages] \\begin{enumerate*}\n",
       "\\item 25\n",
       "\\item 26\n",
       "\\item 18\n",
       "\\item 39\n",
       "\\end{enumerate*}\n",
       "\n",
       "\\item[{[[3]]}] \\begin{tabular}{ll}\n",
       "\t 1  &  6\\\\\n",
       "\t 2  &  7\\\\\n",
       "\t 3  &  8\\\\\n",
       "\t 4  &  9\\\\\n",
       "\t 5  & 10\\\\\n",
       "\\end{tabular}\n",
       "\n",
       "\\item[{[[4]]}] \\begin{enumerate*}\n",
       "\\item 'one'\n",
       "\\item 'two'\n",
       "\\item 'three'\n",
       "\\end{enumerate*}\n",
       "\n",
       "\\end{description}\n"
      ],
      "text/markdown": [
       "$title\n",
       ":   'My First List'\n",
       "$ages\n",
       ":   1. 25\n",
       "2. 26\n",
       "3. 18\n",
       "4. 39\n",
       "\n",
       "\n",
       "\n",
       "[[3]]\n",
       ":   \n",
       "| 1  |  6 |\n",
       "| 2  |  7 |\n",
       "| 3  |  8 |\n",
       "| 4  |  9 |\n",
       "| 5  | 10 |\n",
       "\n",
       "\n",
       "[[4]]\n",
       ":   1. 'one'\n",
       "2. 'two'\n",
       "3. 'three'\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "$title\n",
       "[1] \"My First List\"\n",
       "\n",
       "$ages\n",
       "[1] 25 26 18 39\n",
       "\n",
       "[[3]]\n",
       "     [,1] [,2]\n",
       "[1,]    1    6\n",
       "[2,]    2    7\n",
       "[3,]    3    8\n",
       "[4,]    4    9\n",
       "[5,]    5   10\n",
       "\n",
       "[[4]]\n",
       "[1] \"one\"   \"two\"   \"three\"\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#创建一个列表\n",
    "g <- \"My First List\"\n",
    "h <- c(25, 26, 18, 39)\n",
    "j <- matrix(1:10, nrow=5)\n",
    "k <- c(\"one\", \"two\", \"three\")\n",
    "mylist <- list(title=g, ages=h, j, k)\n",
    "mylist  #创建的列表，包含四个成分：：一个字符串、一个数值型向量、一个矩阵以及一个字符型向量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>25</li>\n",
       "\t<li>26</li>\n",
       "\t<li>18</li>\n",
       "\t<li>39</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 25\n",
       "\\item 26\n",
       "\\item 18\n",
       "\\item 39\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 25\n",
       "2. 26\n",
       "3. 18\n",
       "4. 39\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 25 26 18 39"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mylist[[2]] #输出地二个成分 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>25</li>\n",
       "\t<li>26</li>\n",
       "\t<li>18</li>\n",
       "\t<li>39</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 25\n",
       "\\item 26\n",
       "\\item 18\n",
       "\\item 39\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 25\n",
       "2. 26\n",
       "3. 18\n",
       "4. 39\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 25 26 18 39"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mylist[['ages']] #输出地二个成分"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![提醒程序员注意的一些事项](./image/提醒程序员注意的一些事项.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2.3 数据的输入"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![可供R导入的数据源.jpg](./image/可供R导入的数据源.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.3.1 使用键盘输入数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "R中的函数edit()会自动调用一个允许手动输入数据的文本编辑器\n",
    "\n",
    "(1) 创建一个空数据框（或矩阵），其中变量名和变量的模式需与理想中的最终数据集一致；\n",
    "\n",
    "(2) 针对这个数据对象调用文本编辑器，输入你的数据，并将结果保存回此数据对象中。"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "mydata <- data.frame(age=numeric(0),\n",
    "gender=character(0), weight=numeric(0))\n",
    "mydata <- edit(mydata)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.3.2 从带分隔符的文本文件导入数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "使用read.table()从带分隔符的文本文件中导入数据。此函数可读入一个表格格式的文件并将其保存为一个数据框。表格的每一行分别出现在文件中每一行。其语法如下：\n",
    "\n",
    "mydataframe <- read.table(file, options)\n",
    "\n",
    "file是一个带分隔符的ASCII文本文件，options是控制如何处理数据的选项。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![函数readtable的选项.jpg](./image/函数readtable的选项.jpg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in read.table(\"studentgrades.csv\", header = TRUE, row.names = \"StudentID\", :\n",
      "\"incomplete final line found by readTableHeader on 'studentgrades.csv'\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>First</th><th scope=col>Last</th><th scope=col>Math</th><th scope=col>Science</th><th scope=col>Social.Studies</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>11</th><td>Bob          </td><td>Smith        </td><td>90           </td><td>80           </td><td>67           </td></tr>\n",
       "\t<tr><th scope=row>12</th><td>Jane         </td><td>Weary        </td><td>75           </td><td>NA           </td><td>80           </td></tr>\n",
       "\t<tr><th scope=row>10</th><td>Dan          </td><td>Thornton, III</td><td>65           </td><td>75           </td><td>70           </td></tr>\n",
       "\t<tr><th scope=row>40</th><td>Mary         </td><td>O'Leary      </td><td>90           </td><td>95           </td><td>92           </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllll}\n",
       "  & First & Last & Math & Science & Social.Studies\\\\\n",
       "\\hline\n",
       "\t11 & Bob           & Smith         & 90            & 80            & 67           \\\\\n",
       "\t12 & Jane          & Weary         & 75            & NA            & 80           \\\\\n",
       "\t10 & Dan           & Thornton, III & 65            & 75            & 70           \\\\\n",
       "\t40 & Mary          & O'Leary       & 90            & 95            & 92           \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| <!--/--> | First | Last | Math | Science | Social.Studies |\n",
       "|---|---|---|---|---|---|\n",
       "| 11 | Bob           | Smith         | 90            | 80            | 67            |\n",
       "| 12 | Jane          | Weary         | 75            | NA            | 80            |\n",
       "| 10 | Dan           | Thornton, III | 65            | 75            | 70            |\n",
       "| 40 | Mary          | O'Leary       | 90            | 95            | 92            |\n",
       "\n"
      ],
      "text/plain": [
       "   First Last          Math Science Social.Studies\n",
       "11 Bob   Smith         90   80      67            \n",
       "12 Jane  Weary         75   NA      80            \n",
       "10 Dan   Thornton, III 65   75      70            \n",
       "40 Mary  O'Leary       90   95      92            "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "grades <- read.table(\"studentgrades.csv\", header=TRUE,row.names=\"StudentID\", sep=\",\")\n",
    "grades"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'data.frame':\t4 obs. of  5 variables:\n",
      " $ First         : Factor w/ 4 levels \"Bob\",\"Dan\",\"Jane\",..: 1 3 2 4\n",
      " $ Last          : Factor w/ 4 levels \"O'Leary\",\"Smith\",..: 2 4 3 1\n",
      " $ Math          : int  90 75 65 90\n",
      " $ Science       : int  80 NA 75 95\n",
      " $ Social.Studies: int  67 80 70 92\n"
     ]
    }
   ],
   "source": [
    "str(grades)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![用连接来导入数据.jpg](./image/用连接来导入数据.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.3.3 导入Excel 数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "读取一个Excel文件的最好方式，就是在Excel中将其导出为一个逗号分隔文件（csv），并使\n",
    "用前文描述的方式将其导入R中。此外，你可以用xlsx包直接地导入Excel工作表。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Installing package into 'C:/Users/acer/Documents/R/win-library/3.5'\n",
      "(as 'lib' is unspecified)\n",
      "also installing the dependencies 'rJava', 'xlsxjars'\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "package 'rJava' successfully unpacked and MD5 sums checked\n",
      "package 'xlsxjars' successfully unpacked and MD5 sums checked\n",
      "package 'xlsx' successfully unpacked and MD5 sums checked\n",
      "\n",
      "The downloaded binary packages are in\n",
      "\tC:\\Users\\acer\\AppData\\Local\\Temp\\Rtmp63GrBU\\downloaded_packages\n"
     ]
    }
   ],
   "source": [
    "install.packages(\"xlsx\")"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "#xlsx包可以用来对Excel文件进行读取、写入和格式转换。\n",
    "library(xlsx)\n",
    "workbook <- \"c:/myworkbook.xlsx\"\n",
    "mydataframe <- read.xlsx(workbook, 1) #表示插入文件workbook.xlsx的第一个工作表格"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.3.4 导入XML数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.3.5 从网页抓取数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.3.6 导入SPSS 数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "IBM SPSS数据集可以通过foreign包中的函数read.spss()导入到R中，\n",
    "\n",
    "也可以使用Hmisc包中的spss.get()函数。函数spss.get()是对read.spss()的一个封装，它可以为你自动设置后者的许多参数，让整个转换过程更加简单一致，最后得到数据分析人员所期望的结果。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Installing package into 'C:/Users/acer/Documents/R/win-library/3.5'\n",
      "(as 'lib' is unspecified)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "package 'Hmisc' successfully unpacked and MD5 sums checked\n",
      "\n",
      "The downloaded binary packages are in\n",
      "\tC:\\Users\\acer\\AppData\\Local\\Temp\\Rtmp63GrBU\\downloaded_packages\n"
     ]
    }
   ],
   "source": [
    "install.packages(\"Hmisc\")"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "library(Hmisc)\n",
    "mydataframe <- spss.get(\"mydata.sav\", use.value.labels=TRUE) #，use.value.labels=TRUE表示让函数将带有值标签的变量导入为R中水平对应相同的因子"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.3.7 导入SAS 数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "R中设计了若干用来导入SAS数据集的函数，包括\n",
    "\n",
    "foreign包中的read.ssd()，\n",
    "\n",
    "Hmisc包中的sas.get()，\n",
    "\n",
    "sas7bdat包中的 read.sas7bdat()。\n",
    "\n",
    "SAS包中sas.get()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.3.8 导入Stata 数据"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "library(foreign)\n",
    "mydataframe <- read.dta(\"mydata.dta\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.3.9 导入NetCDF 数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "NetCDF格式通常用来存储地球物理数据。ncdf包和ncdf4包为NetCDF文件提供了高层的R接口。"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "library(ncdf)\n",
    "nc <- nc_open(\"mynetCDFfile\")\n",
    "myarray <- get.var.ncdf(nc, myvar)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.3.10 导入HDF5 数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "HDF5（Hierarchical Data Format，分层数据格式）是一套用于管理超大型和结构极端复杂数\n",
    "据集的软件技术方案。rhdf5包为R提供了一个HDF5的接口。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.3.11 访问数据库管理系统"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "R中有多种面向关系型数据库管理系统（DBMS）的接口，包括Microsoft SQL Server、Microsoft\n",
    "Access、MySQL、Oracle、PostgreSQL、DB2、Sybase、Teradata以及SQLite。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1. ODBC接口"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Installing package into 'C:/Users/acer/Documents/R/win-library/3.5'\n",
      "(as 'lib' is unspecified)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "package 'RODBC' successfully unpacked and MD5 sums checked\n",
      "\n",
      "The downloaded binary packages are in\n",
      "\tC:\\Users\\acer\\AppData\\Local\\Temp\\Rtmp63GrBU\\downloaded_packages\n"
     ]
    }
   ],
   "source": [
    "install.packages(\"RODBC\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![RODBC中的函数.jpg](./image/RODBC中的函数.jpg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "\"package 'RODBC' was built under R version 3.5.2\"Warning message in RODBC::odbcDriverConnect(\"DSN=mydsn;UID=Rob;PWD=aardvark\"):\n",
      "\"[RODBC] ERROR: state IM002, code 0, message [Microsoft][ODBC Çý¶¯³ÌÐò¹ÜÀíÆ÷] Î´·¢ÏÖÊý¾ÝÔ´Ãû³Æ²¢ÇÒÎ´Ö¸¶¨Ä¬ÈÏÇý¶¯³ÌÐò\"Warning message in RODBC::odbcDriverConnect(\"DSN=mydsn;UID=Rob;PWD=aardvark\"):\n",
      "\"ODBC connection failed\""
     ]
    },
    {
     "ename": "ERROR",
     "evalue": "Error in sqlFetch(myconn, Crime): first argument is not an open RODBC channel\n",
     "output_type": "error",
     "traceback": [
      "Error in sqlFetch(myconn, Crime): first argument is not an open RODBC channel\nTraceback:\n",
      "1. sqlFetch(myconn, Crime)",
      "2. stop(\"first argument is not an open RODBC channel\")"
     ]
    }
   ],
   "source": [
    "library(RODBC)\n",
    "myconn <-odbcConnect(\"mydsn\", uid=\"Rob\", pwd=\"aardvark\")\n",
    "crimedat <- sqlFetch(myconn, Crime)\n",
    "pundat <- sqlQuery(myconn, \"select * from Punishment\")\n",
    "close(myconn)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![RODBC中的函数.jpg](./image/RODBC中的函数.jpg)\n",
    "![处理数据对象的使用函数2.jpg](./image/处理数据对象的使用函数2.jpg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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