Fix NumPy tutorial notebook typos and examples

matpltlib/10_subplots.ipynb

@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<h1 align=\"center\", style=\"color:green\">Matplotlib Tutorial: Subplots</h1>"
+    "<h1 align=\"center\" style=\"color:green\">Matplotlib Tutorial: Subplots</h1>"
    ]
   },
   {
@@ -53,12 +53,14 @@
     "expense=[2800,3000,2800,3400]\n",
     "\n",
     "plt.subplot(2,1,1)\n",
-    "# income.set_title('Income')\n",
     "plt.bar(year,income)\n",
+    "plt.title('Income')\n",
     "\n",
+    "plt.subplot(2,1,2)\n",
+    "plt.bar(year,expense,color='green')\n",
+    "plt.title('Expense')\n",
     "\n",
-    "# plt.subplot(2,1,2)\n",
-    "# plt.bar(year,expense,color='green')"
+    "plt.tight_layout()\n"
    ]
   }
  ],

matpltlib/4_bar_chart/4_bar_chart.ipynb

@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<h1 align=\"center\", style=\"color:green\">Matplotlib Tutorial: Bar Chart</h1>"
+    "<h1 align=\"center\" style=\"color:green\">Matplotlib Tutorial: Bar Chart</h1>"
    ]
   },
   {
@@ -155,7 +155,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<h3>Horizontal bar chart using barh function<h3>"
+    "<h3>Horizontal bar chart using barh function</h3>"
    ]
   },
   {
@@ -189,7 +189,7 @@
     "\n",
     "plt.yticks(xpos,company)\n",
     "plt.ylabel(\"Revenue(Bln)\")\n",
-    "plt.title('US Technolog Stocks')\n",
+    "plt.title('US Technology Stocks')\n",
     "plt.legend()"
    ]
   }

matpltlib/5_histogram/5_histogram.ipynb

@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<h1 align=\"center\", style=\"color:green\">Matplotlib Tutorial: Histogram</h1>"
+    "<h1 align=\"center\" style=\"color:green\">Matplotlib Tutorial: Histogram</h1>"
    ]
   },
   {
@@ -122,7 +122,7 @@
     "<ul style=\"color:brown;font-weight: bold;\">\n",
     "    <li>80-100: Normal</li>\n",
     "    <li>100-125: Pre-diabetic</li>\n",
-    "    <li>80-100: Diabetic</li>\n",
+    "    <li>125-150: Diabetic</li>\n",
     "</ul>"
    ]
   },

matpltlib/6_pie_chart/6_pie_chart.ipynb

@@ -6,7 +6,7 @@
     "collapsed": true
    },
    "source": [
-    "<h1 align=\"center\", style=\"color:green\">Matplotlib Tutorial: Pie Charts</h1>"
+    "<h1 align=\"center\" style=\"color:green\">Matplotlib Tutorial: Pie Charts</h1>"
    ]
   },
   {

numpy/nditer.ipynb

@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<h1 style=\"color:green\" align='center'>Numpy tutorial: iterate numpy array using nditer</h1>"
+    "<h1 style=\"color:green\" align=\"center\">Numpy tutorial: iterate numpy array using nditer</h1>"
    ]
   },
   {
@@ -38,10 +38,7 @@
      "output_type": "execute_result"
     }
    ],
-   "source": [
-    "a = np.arange(12).reshape(3,4)\n",
-    "a"
-   ]
+   "source": "a = np.arange(12).reshape(3, 4)\na"
   },
   {
    "cell_type": "markdown",
@@ -167,7 +164,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<h2 style=\"color:purple\">Fortan style ordering</h2>"
+    "<h2 style=\"color:purple\">Fortran style ordering</h2>"
    ]
   },
   {
@@ -226,10 +223,7 @@
      ]
     }
    ],
-   "source": [
-    "for x in np.nditer(a, flags=['external_loop'],order='F'):\n",
-    "    print(x)"
-   ]
+   "source": "for x in np.nditer(a, flags=['external_loop'], order='F'):\n    print(x)"
   },
   {
    "cell_type": "markdown",
@@ -299,10 +293,7 @@
      "output_type": "execute_result"
     }
    ],
-   "source": [
-    "b = np.arange(3, 15, 4).reshape(3,1)\n",
-    "b"
-   ]
+   "source": "b = np.arange(3, 15, 4).reshape(3, 1)\nb"
   },
   {
    "cell_type": "code",
@@ -328,10 +319,7 @@
      ]
     }
    ],
-   "source": [
-    "for x, y in np.nditer([a,b]):\n",
-    "    print (x,y)"
-   ]
+   "source": "for x, y in np.nditer([a, b]):\n    print(x, y)"
   }
  ],
  "metadata": {
@@ -355,4 +343,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 2
-}
+}

numpy/numpy_tutorial.py

@@ -1,19 +1,16 @@
 import numpy as np
 import time
-import sys
 SIZE = 1000000
 l1 = range(SIZE)
 l2 = range(SIZE)
-a1=np.arange(SIZE)
-a2=np.arange(SIZE)
+a1 = np.arange(SIZE)
+a2 = np.arange(SIZE)
 
 # python list
 start = time.time()
-result = [(x+y) for x,y in zip(l1,l2)]
-print("python list took: ",(time.time()-start)*1000)
+result = [(x + y) for x, y in zip(l1, l2)]
+print("python list took: ", (time.time() - start) * 1000)
 # numpy array
-start= time.time()
+start = time.time()
 result = a1 + a2
-print("numpy took: ", (time.time()-start)*1000)
-
-
+print("numpy took: ", (time.time() - start) * 1000)

numpy/numpy_tutorial_2.py

@@ -0,0 +1,3 @@
+import numpy as np
+
+a = np.array([[1, 2, 3], [4, 5, 6]])