Improve numpy & matplotlib description

1_numpy_matplotlib_scipy_sympy/1-numpy_tutorial.ipynb

@@ -11,9 +11,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "最新的[IPython notebook](http://ipython.org/notebook.html)课程可以在[http://github.com/jrjohansson/scientific-python-lectures](http://github.com/jrjohansson/scientific-python-lectures) 找到.\n",
-    "\n",
-    "其他有关这个课程的参考书在这里标注出[http://jrjohansson.github.io](http://jrjohansson.github.io).\n"
+    "NumPy是Python中科学计算的基本软件包。它是一个Python库，提供多维数组对象、各种派生类(如掩码数组和矩阵)和各种例程，用于对数组进行快速操作，包括数学、逻辑、形状操作、排序、选择、I/O、离散傅立叶变换、基本线性代数、基本统计操作、随机模拟等等。Numpy作为Python数据计算的基础广泛应用到数据处理、信号处理、机器学习等领域。"
    ]
   },
   {
@@ -2050,146 +2048,6 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 6.3 take"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "`take` 函数和上面描述的花式索引类似"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 92,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([-3, -2, -1,  0,  1,  2])"
-      ]
-     },
-     "execution_count": 92,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "v2 = np.arange(-3,3)\n",
-    "v2"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 93,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([-2,  0,  2])"
-      ]
-     },
-     "execution_count": 93,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "row_indices = [1, 3, 5]\n",
-    "v2[row_indices] # 花式索引"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 38,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([-2,  0,  2])"
-      ]
-     },
-     "execution_count": 38,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "v2.take(row_indices)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "但是`take`也作用在列表和其他的物体上："
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 94,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([-2,  0,  2])"
-      ]
-     },
-     "execution_count": 94,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.take([-3, -2, -1,  0,  1,  2], row_indices)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### 6.4 choose"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "通过从几个数组中选择元素来构造一个数组:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 95,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([ 5, -2,  5, -2])"
-      ]
-     },
-     "execution_count": 95,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "which = [1, 0, 1, 0]\n",
-    "choices = [[-2,-2,-2,-2], [5,5,5,5]]\n",
-    "\n",
-    "np.choose(which, choices)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
     "## 7. 线性代数"
    ]
   },
@@ -4984,7 +4842,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.9"
+   "version": "3.7.9"
   }
  },
  "nbformat": 4,

1_numpy_matplotlib_scipy_sympy/2-matplotlib_tutorial.ipynb

@@ -446,7 +446,7 @@
     "* [Image tutorial](https://matplotlib.org/users/image_tutorial.html)\n",
     "* [手把手教你用Python做数据可视化](https://mp.weixin.qq.com/s/3Gwdjw8trwTR5uyr4G7EOg)\n",
     "* matplotlib Gallery\n",
-    "    - https://matplotlib.org/gallery.html\n",
+    "    - https://www.matplotlib.org.cn/gallery/\n",
     "    - https://github.com/rasbt/matplotlib-gallery"
    ]
   }
@@ -467,7 +467,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.9"
+   "version": "3.7.9"
   }
  },
  "nbformat": 4,