Merge pull request drvinceknight#1 from Nikoleta-v3/niks_sugg

Minor corrections.

Author: drvinceknight

nbs/00 - Studying Mathematics with Python.ipynb

@@ -16,7 +16,7 @@
     "2. [Numpy](02 - Linear algebra with Numpy.ipynb) for dealing with large numeric arrays: perfect for linear algebra;\n",
     "3. [Pandas](03 - Data analysis with Pandas.ipynb) a brilliant tool for data analysis.\n",
     "\n",
-    "**Python and the above libraries are all free to use (and potentially change if you needed to!).** The recommended distribution of Python that includes a number of libraries for scientific work is Anaconda. If you have not yet installed Python on your machine go here: https://www.continuum.io/downloads and follow the download instructions.\n",
+    "**Python and the above libraries are all free to use (and potentially change if you needed to!).** The recommended distribution of Python that includes a number of libraries for scientific work is Anaconda. If you have not yet installed Python on your machine go to the following link: https://www.continuum.io/downloads and follow the download instructions.\n",
     "\n",
     "**Note** that there is a choice between python 3 and python 2. **Python 3 is recommended and assumed in this handbook.**\n",
     "\n",
@@ -177,7 +177,7 @@
     }
    ],
    "source": [
-    "# Anything after a `#` will be ignored\n",
+    "# Anything after a `#` will be ignored. This is what we call a 'comment'\n",
     "a = 20  # Assigning a value to a\n",
     "b = 21  # Assigning a value to b\n",
     "a * b  # Calculating the product of a and b"
@@ -484,7 +484,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.2"
+   "version": "3.6.0"
   }
  },
  "nbformat": 4,

nbs/01 - Symbolic mathematics with Sympy.ipynb

@@ -64,7 +64,7 @@
     }
    ],
    "source": [
-    "x + x"
+    "x - x"
    ]
   },
   {
@@ -162,7 +162,7 @@
     }
    ],
    "source": [
-    "expr = (a + b) ** 2\n",
+    "expr = (a + b) ** 2 \n",
     "expr"
    ]
   },
@@ -704,7 +704,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.2"
+   "version": "3.6.0"
   }
  },
  "nbformat": 4,

nbs/02 - Linear algebra with Numpy.ipynb

@@ -535,7 +535,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.2"
+   "version": "3.6.0"
   }
  },
  "nbformat": 4,

nbs/03 - Data analysis with Pandas.ipynb

@@ -917,7 +917,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.2"
+   "version": "3.6.0"
   }
  },
  "nbformat": 4,

nbs/A1 - Appendix creating Goldbach data.ipynb

@@ -74,9 +74,9 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [default]",
+   "display_name": "Python [conda env:pymathws]",
    "language": "python",
-   "name": "python3"
+   "name": "conda-env-pymathws-py"
   },
   "language_info": {
    "codemirror_mode": {
@@ -88,7 +88,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.2"
+   "version": "3.6.0"
   }
  },
  "nbformat": 4,