Merge branch 'master' into connected-scatter

Author: holtzy

.DS_Store

@@ -28,7 +28,7 @@
     "gatsby-plugin-sharp": "^3.11.0",
     "gatsby-source-filesystem": "^3.11.0",
     "gatsby-transformer-sharp": "^3.11.0",
-    "prismjs": "^1.24.1",
+    "prismjs": "^1.25.0",
     "react": "^17.0.2",
     "react-bootstrap": "^1.6.1",
     "react-dom": "^17.0.2",

package-lock.json

@@ -2,29 +2,16 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "metadata": {},
    "source": [
-    "In the following example, **title**, **x label** and **y label** are added to the [barplot](http://python-graph-gallery.com/barplot/) using `title()`, `xlabel()`, and `ylabel()` functions of [matplotlib](http://python-graph-gallery.com/matplotlib/) library. The functions applied on a barplot in the example, but the same method works for other chart types."
-   ]
+    "In the following example, **title**, **x label** and **y label** are added to the [barplot](http://python-graph-gallery.com/barplot/) using the `title()`, `xlabel()`, and `ylabel()` functions of the [matplotlib](http://python-graph-gallery.com/matplotlib/) library. \n",
+    "\n",
+    "Those functions are applied to a barplot in the example, but the same method would work for other chart types."
+   ],
+   "metadata": {}
   },
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
    "source": [
     "# libraries\n",
     "import numpy as np\n",
@@ -48,12 +35,34 @@
     " \n",
     "# Show graph\n",
     "plt.show()"
-   ]
+   ],
+   "outputs": [
+    {
+     "output_type": "display_data",
+     "data": {
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ],
+      "image/png": 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"
+     },
+     "metadata": {
+      "needs_background": "light"
+     }
+    }
+   ],
+   "metadata": {}
+  },
+  {
+   "cell_type": "markdown",
+   "source": [
+    ">Note: the [matplotlib section](https://www.python-graph-gallery.com/matplotlib/) provides a lot of tips and tricks on how to customize a matplotlib chart!"
+   ],
+   "metadata": {}
   }
  ],
  "metadata": {
   "chartType": "barplot",
-  "description": "In this post, you will see how to add a <b>title</b> and <b>axis labels</b> to your python charts using <a href='https://python-graph-gallery.com/matplotlib/'>matplotlib</a>.",
+  "description": "In this post, you will see how to add a <b>title</b> and <b>axis labels</b> to your python charts using <a href='https://python-graph-gallery.com/matplotlib/'>matplotlib</a>. If you're new to python and want to get the basics of <code>matplotlib</code>, this <a target='_blank' href='https://datacamp.pxf.io/YgNDbR'>online course</a> can be interesting.",
   "family": "ranking",
   "kernelspec": {
    "display_name": "Python 3",
@@ -79,4 +88,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 4
-}
+}