Fix some error; Add section number

1_numpy_matplotlib_scipy_sympy/1-numpy_tutorial.ipynb

@@ -33,16 +33,16 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 简介"
+    "## 1. 简介"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "这个`numpy`包(模块)用在几乎所有使用Python的数值计算中。他是一个为Python提供高性能向量，矩阵和高维数据结构的模块。它是用C和Fortran语言实现的，因此当计算被向量化（用向量和矩阵表示）时，性能非常的好。\n",
+    "这个`numpy`包(模块)用在几乎所有使用Python的数值计算中。他是一个为Python提供高性能向量，矩阵和高维数据结构的模块。它是用C和Fortran语言实现的，因此当计算向量化数据（用向量和矩阵表示）时，性能非常的好。\n",
     "\n",
-    "为了使用`numpy`模块，你先要向下面的例子一样导入这个模块："
+    "为了使用`numpy`模块，你先要像下面的例子一样导入这个模块："
    ]
   },
   {
@@ -60,14 +60,15 @@
    "metadata": {},
    "source": [
     "在`numpy`模块中，用于向量，矩阵和高维数据集的术语是*数组*。\n",
-    "\n"
+    "\n",
+    "**建议大家使用第二种导入方法** `import numpy as np`\n"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 创建`numpy`数组"
+    "## 2. 创建`numpy`数组"
    ]
   },
   {
@@ -85,7 +86,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 从列表中"
+    "### 2.1 从列表中"
    ]
   },
   {
@@ -399,7 +400,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 使用数组生成函数"
+    "### 2.2 使用数组生成函数"
    ]
   },
   {
@@ -758,14 +759,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 文件 I/O"
+    "## 3. 文件 I/O"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 逗号分隔值 (CSV)"
+    "### 3.1 逗号分隔值 (CSV)"
    ]
   },
   {
@@ -945,7 +946,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Numpy 的本地文件格式"
+    "### 3.2 numpy 的本地文件格式"
    ]
   },
   {
@@ -1000,7 +1001,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 更多Numpy数组的性质"
+    "## 4. 更多Numpy数组的性质"
    ]
   },
   {
@@ -1066,14 +1067,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 操作数组"
+    "## 5. 操作数组"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 索引"
+    "### 5.1 索引"
    ]
   },
   {
@@ -1299,7 +1300,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 切片索引"
+    "### 5.2 切片索引"
    ]
   },
   {
@@ -1627,7 +1628,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 花式索引"
+    "### 5.3 花式索引"
    ]
   },
   {
@@ -1852,14 +1853,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 用于从数组中提取数据和创建数组的函数"
+    "## 6. 用于从数组中提取数据和创建数组的函数"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### where"
+    "### 6.1 where"
    ]
   },
   {
@@ -1915,7 +1916,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### diag"
+    "### 6.2 diag"
    ]
   },
   {
@@ -1969,7 +1970,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### take"
+    "### 6.3 take"
    ]
   },
   {
@@ -2072,7 +2073,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### choose"
+    "### 6.4 choose"
    ]
   },
   {
@@ -2109,7 +2110,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 线性代数"
+    "## 7. 线性代数"
    ]
   },
   {
@@ -2123,7 +2124,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Scalar-array 操作"
+    "### 7.1 Scalar-array 操作"
    ]
   },
   {
@@ -2214,7 +2215,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 数组间的元素操作"
+    "### 7.2 数组间的元素操作"
    ]
   },
   {
@@ -2319,7 +2320,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 矩阵代数"
+    "### 7.4 矩阵代数"
    ]
   },
   {
@@ -2602,7 +2603,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 数组/矩阵转换"
+    "### 7.5 数组/矩阵转换"
    ]
   },
   {
@@ -2812,7 +2813,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 矩阵计算"
+    "### 7.6 矩阵计算"
    ]
   },
   {
@@ -2915,7 +2916,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 数据处理"
+    "### 7.7 数据处理"
    ]
   },
   {
@@ -3226,7 +3227,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 数组子集的计算"
+    "### 7.8 数组子集的计算"
    ]
   },
   {
@@ -3363,7 +3364,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 高维数据的计算"
+    "### 7.9 高维数据的计算"
    ]
   },
   {
@@ -3472,7 +3473,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 阵列的重塑、调整大小和堆叠"
+    "## 8. 阵列的重塑、调整大小和堆叠"
    ]
   },
   {
@@ -3749,7 +3750,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 添加新的维度：newaxis"
+    "## 9. 添加新的维度：newaxis"
    ]
   },
   {
@@ -3890,7 +3891,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 叠加和重复数组"
+    "## 10. 叠加和重复数组"
    ]
   },
   {
@@ -3904,7 +3905,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### tile and repeat"
+    "### 10.1 tile and repeat"
    ]
   },
   {
@@ -4020,7 +4021,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### concatenate"
+    "### 10.2 concatenate"
    ]
   },
   {
@@ -4079,7 +4080,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### hstack and vstack"
+    "### 10.3 hstack and vstack"
    ]
   },
   {
@@ -4129,7 +4130,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 复制和“深度复制”"
+    "## 11. 复制和“深度复制”"
    ]
   },
   {
@@ -4282,7 +4283,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 遍历数组元素"
+    "## 12. 遍历数组元素"
    ]
   },
   {
@@ -4408,7 +4409,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 向量化功能"
+    "## 13. 向量化功能"
    ]
   },
   {
@@ -4589,7 +4590,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 在条件中使用数组"
+    "## 14. 在条件中使用数组"
    ]
   },
   {
@@ -4685,7 +4686,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 类型转换"
+    "## 15. 类型转换"
    ]
   },
   {
@@ -4881,7 +4882,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.8"
+   "version": "3.6.9"
   }
  },
  "nbformat": 4,