Small changes and edits to Worksheet 4.

4_PlottingData.ipynb

@@ -14,17 +14,6 @@
     "## 4. Plotting Data with Matplotlib and Bokeh"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "% matplotlib inline"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -36,7 +25,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "What we have been doing so far has required you to type the data into the programs by hand, which is a bit cruel. For this worksheet, we will be using a larger dataset (still tiny by many standards) and you can download a file containing the data from the [GitHub repository](https://github.com/tobyhodges/ITPP/blob/master/speciesDistribution.txt) where these teaching materials are maintained. Just right-click 'Raw' at the top of the file content and download/save the linked file into the same directory as you are keeping the Python scripts. (_Note: if you already obtained these materials from the repository, you probably downloaded the data file, into the same folder, at the same time._)"
+    "What we have been doing so far has required you to type the data into the programs by hand, which is a bit cruel. For this worksheet, we will be using a larger dataset (still tiny by many standards) and you can download a file containing the data from the [GitHub repository](https://git.embl.de/grp-bio-it/ITPP/blob/master/speciesDistribution.txt) where these teaching materials are maintained. Just right-click 'Raw' at the top of the file content and download/save the linked file into the same directory as you are keeping the Python scripts. (_Note: if you already obtained these materials from the repository, you probably downloaded the data file, into the same folder, at the same time._)"
    ]
   },
   {
@@ -82,11 +71,12 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
    "outputs": [],
    "source": [
-    "lines = f.readlines()"
+    "lines = f.readlines()\n",
+    "lines"
    ]
   },
   {
@@ -711,6 +701,10 @@
    },
    "outputs": [],
    "source": [
+    "% magic inline\n",
+    "# The above line is a 'magic' line for the Jupyter notebook which allows plots to be placed inside of the notebook.\n",
+    "# Make sure to place this line before importing matplotlib/pyplot.\n",
+    "\n",
     "import numpy as np\n",
     "from matplotlib import pyplot as plt"
    ]
@@ -905,7 +899,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
    "outputs": [],
    "source": [
@@ -1152,7 +1146,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The `charts` library also contains several other functions for common types of plot, and `bokeh.io` provides functions to display these plots together. For example, below we will create a scatter plot and display that alongside our bar chart in the output:"
+    "The `charts` library also contains several other functions for common types of plot, and `bokeh.models.layours` provides functions to display these plots together. For example, below we will create a scatter plot and display that alongside our bar chart in the output:"
    ]
   },
   {
@@ -1164,13 +1158,13 @@
    "outputs": [],
    "source": [
     "from bokeh.charts import Scatter\n",
-    "from bokeh.io import hplot\n",
+    "from bokeh.models.layouts import Row\n",
     "data2 = {'X': [0,1,2,3,4,5,6,7,0,1,2,3,4,5,6,7],\n",
     "         'Y': [1,2,1,2,1,2,1,2,3,1,2,3,3,3,2,1],\n",
     "         'S': ['A','A','A','A','A','A','A','A','B','B','B','B','B','B','B','B']}\n",
     "print(data2)\n",
     "mySecondPlot = Scatter(data2, x='X', y='Y', color='S', legend='top_right')\n",
-    "layout = hplot(myFirstPlot, mySecondPlot)\n",
+    "layout = Row(myFirstPlot, mySecondPlot)\n",
     "show(layout)"
    ]
   },
@@ -1256,7 +1250,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.1"
+   "version": "3.6.0"
   }
  },
  "nbformat": 4,