01_tools.ipynb: Add iGraph to the list of tools

iGraph is a library collection for creating and manipulating graphs and
analyzing networks. It is written in C and also exists as Python and
R packages.

Mentioned as one of possibilities in the Dmitry Zinoviev's talk titled
"Complex networks and their analysis in Python", filmed during the codebar
Literary Festival in collaboration with The Pragmatic Bookshelf
on Wednesday 23rd June 2021:
  https://www.youtube.com/watch?v=4SdYpv57fxQ

Author: jnareb

01_tools.ipynb

@@ -107,6 +107,30 @@
     "    - numpy and scipy for numerical and scientific computing"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<!-- ![igraph-logo](https://igraph.org/img/igraph_logo_black.svg) -->\n",
+    "<img src=\"https://igraph.org/img/igraph_logo_black.svg\" width=\"20%\" />\n",
+    "\n",
+    "- [iGraph](https://igraph.org/) is a collection of network analysis tools with the emphasis on **efficiency**, **portability** and ease of use.\n",
+    "  - [open source](https://github.com/igraph) and free\n",
+    "  - the source code of igraph packages is written in C\n",
+    "  - can be programmed in \n",
+    "    [Python](https://igraph.org/python),\n",
+    "    [R](https://igraph.org/r),\n",
+    "    [Mathematica](http://szhorvat.net/mathematica/IGraphM),\n",
+    "    and [C/C++](https://igraph.org/c)\n",
+    "  - python-igraph documentation:\n",
+    "    [User's Manual with Tutorial](https://igraph.org/python/doc/tutorial/),\n",
+    "    [API reference](https://igraph.org/python/doc/api/index.html)\n",
+    "    - supports inline plots within a Jupyter notebook via both the Cairo and matplotlib backend\n",
+    "    - you can generate graph from edges stored in a _pandas.DataFrame_\n",
+    "  - capable of handling large networks efficiently\n",
+    "  - interactive and non-interactive usage are both supported"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},