diff --git a/0_python/1_Basics.ipynb b/0_python/1_Basics.ipynb
index e933749..01010da 100644
--- a/0_python/1_Basics.ipynb
+++ b/0_python/1_Basics.ipynb
@@ -11,7 +11,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 1. 导入和Python之禅\n"
+    "## 1. 导入库与Python之禅\n"
    ]
   },
   {
@@ -22,16 +22,24 @@
     {
      "data": {
       "text/plain": [
-       "['1_Basics.ipynb',\n",
+       "['.ipynb_checkpoints',\n",
+       " 'Python.pdf',\n",
+       " '1_Basics_EN.ipynb',\n",
+       " '2_Print_Statement_EN.ipynb',\n",
+       " '4_Data_Structure_2_EN.ipynb',\n",
+       " '5_Control_Flow_EN.ipynb',\n",
+       " '6_Function_EN.ipynb',\n",
+       " 'README.md',\n",
+       " 'README_EN.md',\n",
+       " '1_Basics.ipynb',\n",
        " '2_Print_Statement.ipynb',\n",
        " '3_Data_Structure_1.ipynb',\n",
+       " '3_Data_Structure_1_EN.ipynb',\n",
        " '4_Data_Structure_2.ipynb',\n",
        " '5_Control_Flow.ipynb',\n",
        " '6_Function.ipynb',\n",
        " '7_Class.ipynb',\n",
-       " 'Python.pdf',\n",
-       " 'README.md',\n",
-       " '.ipynb_checkpoints']"
+       " '7_Class_EN.ipynb']"
       ]
      },
      "execution_count": 1,
@@ -47,7 +55,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -86,6 +94,30 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+    "**Python 之禅， by Tim Peters**\n",
+    "```\n",
+    "优美胜于丑陋（Python 以编写优美的代码为目标）\n",
+    "明了胜于晦涩（优美的代码应当是明了的，命名规范，风格相似）\n",
+    "简洁胜于复杂（优美的代码应当是简洁的，不要有复杂的内部实现）\n",
+    "复杂胜于凌乱（如果复杂不可避免，那代码间也不能有难懂的关系，要保持接口简洁）\n",
+    "扁平胜于嵌套（优美的代码应当是扁平的，不能有太多的嵌套）\n",
+    "间隔胜于紧凑（优美的代码有适当的间隔，不要奢望一行代码解决问题）\n",
+    "可读性很重要（优美的代码是可读的）\n",
+    "即便假借特例的实用性之名，也不可违背这些规则（这些规则至高无上）\n",
+    "不要包容所有错误，除非你确定需要这样做（精准地捕获异常，不写except:pass风格的代码）\n",
+    "当存在多种可能，不要尝试去猜测\n",
+    "而是尽量找一种，最好是唯一一种明显的解决方案（如果不确定，就用穷举法）\n",
+    "虽然这并不容易，因为你不是 Python 之父（这里的 Dutch 是指 Guido）\n",
+    "做也许好过不做，但不假思索就动手还不如不做（动手之前要细思量）\n",
+    "如果你无法向人描述你的方案，那肯定不是一个好方案；反之亦然（方案测评标准）\n",
+    "命名空间是一种绝妙的理念，我们应当多加利用（倡导与号召）\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
     "## 2. 变量"
    ]
   },
@@ -98,7 +130,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -109,7 +141,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -133,7 +165,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -142,7 +174,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -188,7 +220,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -197,7 +229,7 @@
        "3"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -275,7 +307,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -284,7 +316,7 @@
        "0.5"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -315,7 +347,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -324,7 +356,7 @@
        "5"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -337,12 +369,12 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "地板除法就是将这样得到的结果转换成最接近的整数。"
+    "地板除法(floor divide)就是将这样得到的结果转换成最接近的整数。"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -351,7 +383,7 @@
        "1.0"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -383,7 +415,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -392,7 +424,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -401,7 +433,7 @@
        "True"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -412,7 +444,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -421,7 +453,7 @@
        "False"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -453,7 +485,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -463,7 +495,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -482,7 +514,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -491,7 +523,7 @@
        "2"
       ]
      },
-     "execution_count": 23,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -513,7 +545,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -522,7 +554,7 @@
        "10"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -560,7 +592,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 4.1 从一个系统到另一个系统的转换"
+    "### 4.1 从一个进制到另一个进制的转换"
    ]
   },
   {
@@ -572,7 +604,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
@@ -581,7 +613,7 @@
        "'0xaa'"
       ]
      },
-     "execution_count": 25,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -592,7 +624,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
@@ -601,7 +633,7 @@
        "170"
       ]
      },
-     "execution_count": 26,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -612,7 +644,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
@@ -621,7 +653,7 @@
        "'0o10'"
       ]
      },
-     "execution_count": 2,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -639,7 +671,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
@@ -693,7 +725,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
     {
@@ -702,7 +734,7 @@
        "'b'"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -713,7 +745,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [
     {
@@ -722,7 +754,7 @@
        "98"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -747,7 +779,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 26,
    "metadata": {
     "scrolled": false
    },
@@ -775,7 +807,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [
     {
@@ -800,7 +832,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [
     {
@@ -809,7 +841,7 @@
        "(4, 1)"
       ]
      },
-     "execution_count": 36,
+     "execution_count": 28,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -827,7 +859,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [
     {
@@ -946,14 +978,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Type something here and it will be stored in variable abc \tHello world!\n"
+      "Type something here and it will be stored in variable abc \t10\n"
      ]
     }
    ],
@@ -963,7 +995,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [
     {
@@ -972,7 +1004,7 @@
        "str"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 33,
      "metadata": {},
      "output_type": "execute_result"
     }
diff --git a/0_python/2_Print_Statement.ipynb b/0_python/2_Print_Statement.ipynb
index 0b142cb..16c2bfe 100644
--- a/0_python/2_Print_Statement.ipynb
+++ b/0_python/2_Print_Statement.ipynb
@@ -47,19 +47,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Hey\n"
+      "Hey\n",
+      "line1line2\n"
      ]
     }
    ],
    "source": [
-    "print('Hey')"
+    "print('Hey')\n",
+    "a = 'line1\\\n",
+    "line2\\\n",
+    "\\\n",
+    "'\n",
+    "print(a)"
    ]
   },
   {
@@ -92,7 +98,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 7,
    "metadata": {
     "scrolled": true
    },
@@ -243,7 +249,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -255,12 +261,12 @@
     }
    ],
    "source": [
-    "print(\"I want to be printed %s\" %'here')"
+    "print(\"I want to be printed %s\" % 'here')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
@@ -277,7 +283,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -301,7 +307,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -370,7 +376,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# 2. PrecisionWidth和FieldWidth"
+    "# 2. `PrecisionWidth`和`FieldWidth`"
    ]
   },
   {
@@ -384,7 +390,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -393,7 +399,7 @@
        "'3.121312'"
       ]
      },
-     "execution_count": 19,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -411,7 +417,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -420,7 +426,7 @@
        "'3.12131'"
       ]
      },
-     "execution_count": 20,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -438,22 +444,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'  3.12131'"
+       "'-33.12131'"
       ]
      },
-     "execution_count": 21,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "\"%9.5f\" % 3.121312312312"
+    "\"%9.5f\" % -33.121312312312"
    ]
   },
   {
diff --git a/0_python/3_Data_Structure_1.ipynb b/0_python/3_Data_Structure_1.ipynb
index 097bbb6..37b2966 100644
--- a/0_python/3_Data_Structure_1.ipynb
+++ b/0_python/3_Data_Structure_1.ipynb
@@ -4,14 +4,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# 数据结构"
+    "# 数据结构1"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "简单地说，它是特定结构中的数据集合或数据组。"
+    "数据结构是计算机存储、组织数据的方式，简单来说是指相互之间存在一种或多种特定关系的数据元素的集合"
    ]
   },
   {
@@ -27,7 +27,7 @@
    "source": [
     "列表是最常用的数据结构。可以把它看作用方括号括起来的数据序列，数据之间用逗号分隔。这些数据都可以通过调用其索引值来访问。\n",
     "\n",
-    "list的声明只需将变量等同于'[ ]'或list即可。"
+    "`list`的声明只需将变量等同于`[ ]`或`list`即可。"
    ]
   },
   {
@@ -65,7 +65,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [
     {
@@ -92,12 +92,12 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "在python中，索引从0开始。因此，现在包含两个元素的列表x的apple索引值为0,orange索引值为1。"
+    "在Python中，索引从`0`开始。因此，现在包含两个元素的列表`x`的apple索引值为`0`,orange索引值为`1`。"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -106,7 +106,7 @@
        "'apple'"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -119,12 +119,12 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "索引也可以按照相反的顺序进行。这是最后一个可以被首先访问的元素。这里，索引从-1开始。因此，指数-1将是橙色，指数-2将是苹果。"
+    "索引也可以按照相反的顺序进行。这是最后一个可以被首先访问的元素。这里，索引从`-1`开始。因此，索引`-1`对应是橙色，索引`-2`对应的是苹果。"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -133,7 +133,7 @@
        "'peach'"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -151,7 +151,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -162,12 +162,12 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "在这里我们已经声明过两个列表x和y每一个包含自己的数据。现在，这两个列表可以再一次被放入另一个也具有自己的数据的列表z中。列表中的这个列表被称为嵌套列表，这就是数组的声明方式，我们将在后面看到。"
+    "在这里我们已经声明过两个列表`x`和`y`每一个包含自己的数据。现在，这两个列表可以再一次被放入另一个也具有自己的数据的列表`z`中。列表中的这个列表被称为`嵌套列表`，这就是数组的声明方式，我们将在后面看到。**这是和很多其他计算机语言不同的地方，不要求列表的元素是相同类型，因此编程的时候会非常方便，这也是为什么Python对人类比较友好**"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -207,10 +207,10 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "如果您不了解在python中索引是如何工作的，那么在嵌套列表中索引可能会非常令人困惑。所以让我们把它分解一下，然后得出一个结论。\n",
+    "如果您不了解在Python中索引是如何工作的，那么在嵌套列表中索引可能会非常令人困惑。所以让我们把它分解一下，然后得出一个结论。\n",
     "\n",
     "让我们在上述嵌套列表中获得数据'apple'。\n",
-    "首先在索引为0处，有一个列表['apple','orange'] 而在索引为1处有另外一个列表['carrot','potato'] 。因此z[0] 应该给我们第一个包含'apple'的列表。"
+    "首先在索引为0处，有一个列表`['apple','orange']` 而在索引为1处有另外一个列表`['carrot','potato']` 。因此z[0] 应该给我们第一个包含'apple'的列表。"
    ]
   },
   {
@@ -310,36 +310,36 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[0, 1, 2, 3]\n",
-      "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]\n",
-      "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]\n"
+      "[3, 2, 3]\n",
+      "[2, 3, 2, 3, 4, 5, 6, 7, 8, 9]\n",
+      "[2, 3, 2, 3, 4, 5, 6, 7, 8, 9]\n"
      ]
     }
    ],
    "source": [
-    "num = [0,1,2,3,4,5,6,7,8,9]\n",
-    "print(num[0:4])\n",
+    "num = [2,3,2,3,4,5,6,7,8,9]\n",
+    "print(num[1:4])\n",
     "print(num[0:])\n",
     "print(num[:])"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[0, 1, 2, 3]\n",
+      "[2, 3, 2, 3]\n",
       "[4, 5, 6, 7, 8, 9]\n"
      ]
     }
@@ -358,16 +358,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[0, 3, 6]"
+       "[2, 3, 6]"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -380,7 +380,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 1.3 构造列表函数"
+    "### 1.3 列表的内置函数"
    ]
   },
   {
@@ -493,7 +493,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -596,7 +596,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -605,7 +605,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
@@ -631,7 +631,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -640,7 +640,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
@@ -673,7 +673,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
@@ -681,11 +681,12 @@
      "output_type": "stream",
      "text": [
       "Earth\n",
-      "Air\n"
+      "Jet\n"
      ]
     }
    ],
    "source": [
+    "names = ['Earth','Jet', 'Air','Fire','Water']\n",
     "print(max(names, key=len))\n",
     "print(min(names, key=len))"
    ]
@@ -703,7 +704,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
     {
@@ -712,7 +713,7 @@
        "['h', 'e', 'l', 'l', 'o']"
       ]
      },
-     "execution_count": 26,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -730,7 +731,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -739,7 +740,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 45,
    "metadata": {},
    "outputs": [
     {
@@ -764,7 +765,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 46,
    "metadata": {},
    "outputs": [
     {
@@ -773,7 +774,7 @@
        "3"
       ]
      },
-     "execution_count": 29,
+     "execution_count": 46,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -791,7 +792,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 47,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -800,7 +801,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 48,
    "metadata": {},
    "outputs": [
     {
@@ -825,7 +826,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 49,
    "metadata": {},
    "outputs": [
     {
@@ -850,7 +851,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 50,
    "metadata": {},
    "outputs": [
     {
@@ -859,7 +860,7 @@
        "0"
       ]
      },
-     "execution_count": 33,
+     "execution_count": 50,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -870,7 +871,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 51,
    "metadata": {},
    "outputs": [
     {
@@ -880,7 +881,7 @@
      "traceback": [
       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
       "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-34-344da5bcf759>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlst\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m999\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[0;32m<ipython-input-51-344da5bcf759>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlst\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m999\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
       "\u001b[0;31mValueError\u001b[0m: 999 is not in list"
      ]
     }
@@ -898,18 +899,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 52,
    "metadata": {},
    "outputs": [
     {
-     "ename": "NameError",
-     "evalue": "name 'lst' is not defined",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-1-c109f115d7f9>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlst\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minsert\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'name'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlst\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mNameError\u001b[0m: name 'lst' is not defined"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[1, 1, 4, 8, 7, 'name', 1, [5, 4, 2, 8], 5, 4, 2, 8]\n"
      ]
     }
    ],
@@ -927,7 +924,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 53,
    "metadata": {},
    "outputs": [
     {
@@ -952,16 +949,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 54,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[1, 1, 4, 8, 7, 'name', 1, [5, 4, 2, 8], 5, 4]"
+       "[1, 1, 4, 8, 7, 'Python', 1, [5, 4, 2, 8], 5, 4, 2]"
       ]
      },
-     "execution_count": 37,
+     "execution_count": 54,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -980,7 +977,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 55,
    "metadata": {},
    "outputs": [
     {
@@ -989,7 +986,7 @@
        "4"
       ]
      },
-     "execution_count": 38,
+     "execution_count": 55,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1000,14 +997,42 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[1, 1, 8, 7, 'Python', 1, [5, 4, 2, 8], 5, 4, 2]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "4"
+      ]
+     },
+     "execution_count": 57,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "print(lst)\n",
+    "lst.pop(-2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[1, 1, 8, 7, 'name', 1, [5, 4, 2, 8], 5, 4]\n"
+      "[1, 1, 8, 7, 'Python', 1, [5, 4, 2, 8], 5, 2]\n"
      ]
     }
    ],
@@ -1024,19 +1049,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 60,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[1, 1, 8, 7, 1, [5, 4, 2, 8], 5, 4]\n"
+      "[1, 1, 8, 7, 1, [5, 4, 2, 8], 5, 2]\n"
      ]
     }
    ],
    "source": [
-    "lst.remove('name')\n",
+    "lst.remove('Python')\n",
     "print(lst)"
    ]
   },
@@ -1049,15 +1074,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 61,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[1, 4, 7, 1, [5, 4, 2, 8], 5, 4, 2]\n",
-      "[1, 7, 1, [5, 4, 2, 8], 5, 4, 2]\n"
+      "[1, 1, 8, 7, 1, [5, 4, 2, 8], 5, 2]\n",
+      "[1, 8, 7, 1, [5, 4, 2, 8], 5, 2]\n"
      ]
     }
    ],
@@ -1076,14 +1101,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 62,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[4, 5, [5, 4, 2, 8], 1, 7, 8, 1, 1]\n"
+      "[2, 5, [5, 4, 2, 8], 1, 7, 8, 1]\n"
      ]
     }
    ],
@@ -1103,7 +1128,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 63,
    "metadata": {},
    "outputs": [
     {
@@ -1129,7 +1154,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 64,
    "metadata": {},
    "outputs": [
     {
@@ -1154,7 +1179,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 65,
    "metadata": {},
    "outputs": [
     {
@@ -1213,12 +1238,12 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "大多数新的python程序员都会犯这个错误，即对象的赋值和拷贝的差异。考虑以下的例子："
+    "大多数新的python程序员都会犯这个错误，即**对象的赋值和拷贝的差异**。考虑以下的例子："
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 66,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1227,7 +1252,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 67,
    "metadata": {},
    "outputs": [
     {
@@ -1239,7 +1264,7 @@
     }
    ],
    "source": [
-    "listb = lista\n",
+    "listb = lista # 对象赋值\n",
     "print(listb)"
    ]
   },
@@ -1252,7 +1277,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 68,
    "metadata": {},
    "outputs": [
     {
@@ -1273,7 +1298,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 69,
    "metadata": {},
    "outputs": [
     {
@@ -1299,7 +1324,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 71,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1308,7 +1333,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 72,
    "metadata": {},
    "outputs": [
     {
@@ -1326,7 +1351,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 73,
    "metadata": {},
    "outputs": [
     {
@@ -1347,7 +1372,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 74,
    "metadata": {},
    "outputs": [
     {
@@ -1419,7 +1444,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 75,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1436,7 +1461,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": 76,
    "metadata": {},
    "outputs": [
     {
@@ -1445,7 +1470,7 @@
        "(27,)"
       ]
      },
-     "execution_count": 53,
+     "execution_count": 76,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1463,7 +1488,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 54,
+   "execution_count": 79,
    "metadata": {},
    "outputs": [
     {
@@ -1472,7 +1497,7 @@
        "(27, 27)"
       ]
      },
-     "execution_count": 54,
+     "execution_count": 79,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1490,7 +1515,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 80,
    "metadata": {
     "scrolled": true
    },
@@ -1520,7 +1545,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
+   "execution_count": 81,
    "metadata": {},
    "outputs": [
     {
@@ -1547,7 +1572,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
+   "execution_count": 82,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1593,7 +1618,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 2.2 内置元组函数"
+    "### 2.2 元组内置函数"
    ]
   },
   {
@@ -1668,7 +1693,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": 83,
    "metadata": {},
    "outputs": [
     {
@@ -1686,7 +1711,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 62,
+   "execution_count": 84,
    "metadata": {},
    "outputs": [
     {
@@ -1703,6 +1728,24 @@
    ]
   },
   {
+   "cell_type": "code",
+   "execution_count": 86,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{1, 2, 3, 4}\n"
+     ]
+    }
+   ],
+   "source": [
+    "set1 = set((1,2,2,3,3,4))\n",
+    "print(set1)"
+   ]
+  },
+  {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -1718,7 +1761,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": 87,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1727,7 +1770,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 88,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1743,7 +1786,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
+   "execution_count": 89,
    "metadata": {},
    "outputs": [
     {
@@ -1752,7 +1795,7 @@
        "{1, 2, 3, 4, 5}"
       ]
      },
-     "execution_count": 65,
+     "execution_count": 89,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1770,7 +1813,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 90,
    "metadata": {},
    "outputs": [
     {
@@ -1786,7 +1829,7 @@
        "{0, 1, 2, 3}"
       ]
      },
-     "execution_count": 66,
+     "execution_count": 90,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1806,7 +1849,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 67,
+   "execution_count": 91,
    "metadata": {},
    "outputs": [
     {
@@ -1815,7 +1858,7 @@
        "{2, 3}"
       ]
      },
-     "execution_count": 67,
+     "execution_count": 91,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1833,21 +1876,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 68,
+   "execution_count": 93,
    "metadata": {},
    "outputs": [
     {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{0, 1, 2, 3}\n",
+      "{2, 3, 4, 5}\n"
+     ]
+    },
+    {
      "data": {
       "text/plain": [
        "{0, 1}"
       ]
      },
-     "execution_count": 68,
+     "execution_count": 93,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
+    "print(set1)\n",
+    "print(set2)\n",
     "set1.difference(set2)"
    ]
   },
@@ -1860,7 +1913,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 94,
    "metadata": {},
    "outputs": [
     {
@@ -1869,7 +1922,7 @@
        "{0, 1, 4, 5}"
       ]
      },
-     "execution_count": 59,
+     "execution_count": 94,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1887,7 +1940,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": 95,
    "metadata": {},
    "outputs": [
     {
@@ -1896,7 +1949,7 @@
        "False"
       ]
      },
-     "execution_count": 60,
+     "execution_count": 95,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1907,18 +1960,40 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 96,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "False"
+      ]
+     },
+     "execution_count": 96,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "set2.isdisjoint(set1)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 97,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "False"
+      ]
+     },
+     "execution_count": 97,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "set2.issuperset(set1)"
    ]
@@ -1932,9 +2007,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 98,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{1, 2, 3}\n"
+     ]
+    }
+   ],
    "source": [
     "set1.pop()\n",
     "print(set1)"
@@ -1949,9 +2032,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 99,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{1, 3}"
+      ]
+     },
+     "execution_count": 99,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "set1.remove(2)\n",
     "set1"
@@ -1966,7 +2060,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": 100,
    "metadata": {},
    "outputs": [
     {
@@ -1975,7 +2069,7 @@
        "set()"
       ]
      },
-     "execution_count": 61,
+     "execution_count": 100,
      "metadata": {},
      "output_type": "execute_result"
     }
diff --git a/0_python/4_Data_Structure_2.ipynb b/0_python/4_Data_Structure_2.ipynb
index 659bfba..62bd8e8 100644
--- a/0_python/4_Data_Structure_2.ipynb
+++ b/0_python/4_Data_Structure_2.ipynb
@@ -4,6 +4,8 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+    "# 数据结构2\n",
+    "\n",
     "## 1. 字符串"
    ]
   },
@@ -16,17 +18,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 1,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "10\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "String0 = 'Taj Mahal is beautiful'\n",
     "String1 = \"Taj Mahal is beautiful\"\n",
@@ -37,7 +31,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -67,7 +61,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -100,19 +94,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "Taj Mahal is beautiful\n",
       "7\n",
       "-1\n"
      ]
     }
    ],
    "source": [
+    "print(String0)\n",
     "print(String0.find('al'))\n",
     "print(String0.find('am'))"
    ]
@@ -126,7 +122,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -150,7 +146,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -176,7 +172,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -201,7 +197,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -210,7 +206,7 @@
        "'                        Taj Mahal is beautiful                        '"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -228,7 +224,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -237,7 +233,7 @@
        "'------------------------Taj Mahal is beautiful------------------------'"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -255,7 +251,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -264,7 +260,7 @@
        "'00000000Taj Mahal is beautiful'"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -282,7 +278,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -313,7 +309,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
@@ -331,7 +327,7 @@
      "traceback": [
       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
       "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-14-a7d6b97b4839>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mString0\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Taj'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mString0\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Mahal'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mString0\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Mahal'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m20\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[0;32m<ipython-input-15-a7d6b97b4839>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mString0\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Taj'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mString0\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Mahal'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mString0\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Mahal'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m20\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
       "\u001b[0;31mValueError\u001b[0m: substring not found"
      ]
     }
@@ -351,7 +347,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -375,7 +371,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -401,7 +397,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -427,7 +423,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -436,7 +432,7 @@
        "'*a_a-'"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -447,7 +443,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
@@ -456,7 +452,7 @@
        "'1\\n2'"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -481,7 +477,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
@@ -509,7 +505,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
@@ -534,7 +530,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
@@ -666,7 +662,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -682,7 +678,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [
     {
@@ -691,7 +687,7 @@
        "'hello'"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -709,7 +705,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -718,7 +714,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [
     {
@@ -727,7 +723,7 @@
        "'   ***----hello---*******     '"
       ]
      },
-     "execution_count": 21,
+     "execution_count": 27,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -799,7 +795,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "字典更像数据库，因为在这里你可以用用户定义的字符串索引特定的序列。"
+    "词典更像数据库，因为在这里你可以用用户定义的字符串索引特定的序列。"
    ]
   },
   {
@@ -811,7 +807,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [
     {
@@ -837,14 +833,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "{'OneTwo': 12, 'One': 1}\n"
+      "{'One': 1, 'OneTwo': 12}\n"
      ]
     }
    ],
@@ -856,14 +852,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "{'key2': [1, 2, 4], 'key1': 1, 3: (1, 4, 6)}\n"
+      "{'key1': 1, 'key2': [1, 2, 4], 3: (1, 4, 6)}\n"
      ]
     }
    ],
@@ -881,7 +877,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [
     {
@@ -905,7 +901,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -922,14 +918,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "{'One': 1, 'Four': 4, 'Three': 3, 'Five': 5, 'Two': 2}\n"
+      "{'One': 1, 'Two': 2, 'Three': 3, 'Four': 4, 'Five': 5}\n"
      ]
     }
    ],
@@ -983,14 +979,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{}\n"
+     "ename": "NameError",
+     "evalue": "name 'a1' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-34-ea21b6f6055b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0ma1\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclear\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mNameError\u001b[0m: name 'a1' is not defined"
      ]
     }
    ],
@@ -1008,14 +1008,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "{'One': 1, 'Four': 4, 'Three': 3, 'Five': 5, 'Two': 2}\n"
+      "{'One': 1, 'Two': 2, 'Three': 3, 'Four': 4, 'Five': 5}\n"
      ]
     }
    ],
@@ -1052,16 +1052,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "dict_values([1, 4, 3, 5, 2])"
+       "dict_values([1, 2, 3, 4, 5])"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 36,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1079,16 +1079,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "dict_keys(['One', 'Four', 'Three', 'Five', 'Two'])"
+       "dict_keys(['One', 'Two', 'Three', 'Four', 'Five'])"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 37,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1106,7 +1106,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [
     {
@@ -1114,10 +1114,10 @@
      "output_type": "stream",
      "text": [
       "[   One] 1\n",
-      "[  Four] 4\n",
+      "[   Two] 2\n",
       "[ Three] 3\n",
-      "[  Five] 5\n",
-      "[   Two] 2\n"
+      "[  Four] 4\n",
+      "[  Five] 5\n"
      ]
     }
    ],
@@ -1137,15 +1137,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 41,
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{'One': 1, 'Three': 3, 'Five': 5, 'Two': 2}\n",
-      "4\n"
+     "ename": "KeyError",
+     "evalue": "'Four'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-41-807ce32acb5c>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0ma2\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0ma1\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Four'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mKeyError\u001b[0m: 'Four'"
      ]
     }
    ],
diff --git a/0_python/5_Control_Flow.ipynb b/0_python/5_Control_Flow.ipynb
index ddfcb6e..4d44307 100644
--- a/0_python/5_Control_Flow.ipynb
+++ b/0_python/5_Control_Flow.ipynb
@@ -180,7 +180,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 4.1 For"
+    "### 4.1 for"
    ]
   },
   {
@@ -307,7 +307,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 4.2 While"
+    "### 4.2 while"
    ]
   },
   {
@@ -363,7 +363,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 5. Break"
+    "## 5. break"
    ]
   },
   {
@@ -404,7 +404,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 6. Continue"
+    "## 6. continue"
    ]
   },
   {
@@ -449,14 +449,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 7. List Comprehensions"
+    "## 7. 列表推导（List Comprehensions）"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Python使用列表理解式，用一行代码就可以很容易地生成所需的列表。例如，如果我需要生成27的倍数，我用For loop写代码，"
+    "Python可以使用列表推导模式，用一行代码就可以很容易地生成所需的列表。例如，如果我需要生成27的倍数，用`for`循环缩写的代码如下："
    ]
   },
   {
@@ -484,7 +484,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "由于你需要生成另一个列表，所以列表理解是解决这个问题的更有效的方法。"
+    "由于你需要生成另一个列表，所以列表推导是解决这个问题的更有效的方法（建议大家使用这样的方式）"
    ]
   },
   {
diff --git a/0_python/README.md b/0_python/README.md
index a91dcad..78e3308 100644
--- a/0_python/README.md
+++ b/0_python/README.md
@@ -1,7 +1,7 @@
 
 # 简明Python教程 （90分钟学会Python）
 
-Python 是一门上手简单、功能强大、通用型的脚本编程语言。Python 类库极其丰富，这使得 Python 几乎无所不能，网站开发、软件开发、大数据分析、网络爬虫、机器学习等都不在话下。Python最主要的优点是使用人类的思考方式来完成大部分的工作，大多数时候使用封装好的库快速完成给定的任务，虽然可能执行的效率不一定很高，但是极大的缩短了程序设计、编写、调试的时间，因此非常适合快速试错。
+Python 是一门上手简单、功能强大、通用型的脚本编程语言。Python 类库极其丰富，这使得 Python 几乎无所不能，网站开发、软件开发、大数据分析、网络爬虫、机器学习等都不在话下。Python最主要的优点是使用人类的思考方式来编写程序，大多数情况下使用封装好的库能够快速完成给定的任务，虽然执行的效率不一定很高，但是极大的缩短了程序设计、编写、调试的时间，因此非常适合快速尝试、试错。
 
 本教程来自[IPython Notebooks to learn Python](https://github.com/rajathkmp/Python-Lectures)，将其中部分示例代码转化成Python3。关于Python的按照可以自行去网络上查找相关的资料，或者参考[安装Python环境](../tips/InstallPython.md)。
 
diff --git a/2_knn/knn_classification.ipynb b/2_knn/knn_classification.ipynb
index 56890f5..ec88e27 100644
--- a/2_knn/knn_classification.ipynb
+++ b/2_knn/knn_classification.ipynb
@@ -7,39 +7,40 @@
     "# kNN Classification\n",
     "\n",
     "\n",
-    "K最近邻(k-Nearest Neighbor，kNN)分类算法，是一个理论上比较成熟的方法，也是最简单的机器学习算法之一。该方法的思路是：***如果一个样本在特征空间中的k个最相似(即特征空间中最邻近)的样本中的大多数属于某一个类别，则该样本也属于这个类别***。KNN方法虽然从原理上也依赖于极限定理，但在类别决策时，只与极少量的相邻样本有关。由于KNN方法主要靠周围有限的邻近的样本，而不是靠判别类域的方法来确定所属类别的，因此对于类域的交叉或重叠较多的待分样本集来说，KNN方法较其他方法更为适合。\n",
+    "K最近邻(k-Nearest Neighbor，kNN)分类算法，是一个理论上比较成熟的方法，也是最简单的机器学习算法之一。该方法的思路是：***如果一个样本在特征空间中的k个最相似（即特征空间中最邻近）的样本中的大多数属于某一个类别，则该样本也属于这个类别***。kNN方法虽然从原理上也依赖于极限定理，但在类别决策时，只与极少量的相邻样本有关。由于kNN方法主要靠周围有限的邻近的样本，而不是靠判别类域的方法来确定所属类别的，因此对于类域的交叉或重叠较多的待分样本集来说，kNN方法较其他方法更为适合。\n",
     "\n",
-    "kNN算法不仅可以用于分类，还可以用于回归。通过找出一个样本的k个最近邻居，将这些邻居的属性的平均值赋给该样本，就可以得到该样本的属性。更有用的方法是将不同距离的邻居对该样本产生的影响给予不同的权值(weight)，如权值与距离成正比（组合函数）。\n",
+    "kNN算法不仅可以用于分类，还可以用于回归。通过找出一个样本的`k`个最近邻居，将这些邻居的属性的平均值赋给该样本，就可以得到该样本的属性。更有用的方法是将不同距离的邻居对该样本产生的影响给予不同的权值(weight)，如权值与距离成正比（组合函数）。\n",
     "\n",
-    "该算法在分类时有个主要的不足是，当样本不平衡时，如一个类的样本容量很大，而其他类样本容量很小时，有可能导致当输入一个新样本时，该样本的K个邻居中大容量类的样本占多数。在这种情况下可能会产生误判的结果。因此我们需要减少数量对运行结果的影响。可以采用权值的方法（和该样本距离小的邻居权值大）来改进。该方法的另一个不足之处是计算量较大，因为对每一个待分类的文本都要计算它到全体已知样本的距离，才能求得它的K个最近邻点。目前常用的解决方法是事先对已知样本点进行剪辑，事先去除对分类作用不大的样本。该算法比较适用于样本容量比较大的类域的自动分类，而那些样本容量较小的类域采用这种算法比较容易产生误分。\n",
+    "该算法存在的问题：\n",
+    "1. 当样本不平衡时，如一个类的样本容量很大，而其他类样本容量很小时，有可能导致当输入一个新样本时，该样本的K个邻居中大容量类的样本占多数。在这种情况下可能会产生误判的结果。因此我们需要减少数量对运行结果的影响。可以采用权值的方法（和该样本距离小的邻居权值大）来改进。\n",
+    "2. 计算量较大，因为对每一个待分类的数据都要计算它到全体已知样本的距离，才能求得它的K个最近邻点。目前常用的解决方法是事先对已知样本点进行剪辑，事先去除对分类作用不大的样本。该算法比较适用于样本容量比较大的类域的自动分类，而那些样本容量较小的类域采用这种算法比较容易产生误分。\n",
     "\n",
-    "k-NN可以说是一种最直接的用来分类未知数据的方法。基本通过下面这张图跟文字说明就可以明白K-NN是干什么的\n",
+    "kNN可以说是一种最直接的用来分类未知数据的方法。基本通过下面这张图跟文字说明就可以明白kNN是干什么的\n",
     "![knn](images/knn.png)\n",
     "\n",
-    "简单来说，k-NN可以看成：**有那么一堆你已经知道分类的数据，然后当一个新数据进入的时候，就开始跟训练数据里的每个点求距离，然后挑离这个训练数据最近的K个点看看这几个点属于什么类型，然后用少数服从多数的原则，给新数据归类**。\n"
+    "简单来说，kNN可以看成：**有那么一堆你已经知道分类的数据，然后当一个新数据进入的时候，就开始跟训练数据里的每个点求距离，然后挑选这个训练数据最近的K个点，看看这几个点属于什么类型，然后用少数服从多数的原则，给新数据归类**。\n"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 算法步骤：(FIXME: 把流程再细化一下，循环需要体现的更好)\n",
+    "## 1. 算法步骤：\n",
     "\n",
-    "* step.1---导入训练样本\n",
-    "* step.2---将样本的特征转化为数据\n",
-    "* step.3---计算未知样本和训练样本的距离dist\n",
-    "* step.4---记录位置样本和训练样本得距离及其所属于得分类\n",
-    "* step.5---重复步骤2、3，直到未知样本和所有训练样本的距离都算完\n",
-    "* step.6---将训练样本按照与未知样本的距离进行排序，找出其中K个最近的样本\n",
-    "* step.7---统计K-最近邻样本中每个类标号出现的次数\n",
-    "* step.8---选择出现频率最大的类标号作为未知样本的类标号"
+    "1. 准备数据，对数据进行预处理;\n",
+    "2. 计算测试数据与各个训练数据之间的**距离**；\n",
+    "3. 按照距离的递增关系进行排序；\n",
+    "4. 选取距离最小的`k`个点；\n",
+    "5. 确定前`k`个点所在类别的出现频率；\n",
+    "6. 返回前`k`个点中出现频率最高的类别作为测试数据的预测分类。\n",
+    "\n"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 生成数据"
+    "## 2. 生成数据"
    ]
   },
   {
@@ -119,7 +120,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Program"
+    "## 3. Program"
    ]
   },
   {
@@ -208,7 +209,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## sklearn program"
+    "## 4. sklearn program"
    ]
   },
   {
@@ -312,6 +313,19 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+    "## 5. 深入思考\n",
+    "\n",
+    "* 如果输入的数据非常多，怎么快速进行距离计算？\n",
+    "    - kd-tree\n",
+    "    - Fast Library for Approximate Nearest Neighbors （FLANN）\n",
+    "* 如何选择最好的`k`？\n",
+    "    - https://zhuanlan.zhihu.com/p/143092725"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
     "## References\n",
     "* [Digits Classification Exercise](http://scikit-learn.org/stable/auto_examples/exercises/plot_digits_classification_exercise.html)\n",
     "* [knn算法的原理与实现](https://zhuanlan.zhihu.com/p/36549000)"
@@ -334,7 +348,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.8"
+   "version": "3.6.9"
   }
  },
  "nbformat": 4,
diff --git a/3_kmeans/1-k-means.ipynb b/3_kmeans/1-k-means.ipynb
index 6de3fda..27c5cbf 100644
--- a/3_kmeans/1-k-means.ipynb
+++ b/3_kmeans/1-k-means.ipynb
@@ -955,7 +955,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.8"
+   "version": "3.6.9"
   }
  },
  "nbformat": 4,