diff --git a/ball-and-stick-1.ipynb b/ball-and-stick-1.ipynb
index 373698b844..bc3aca9d9d 100644
--- a/ball-and-stick-1.ipynb
+++ b/ball-and-stick-1.ipynb
@@ -50,6 +50,22 @@
     "As good practice, we'll load some unit definitions:"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from neuron.units import ms, mV"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We'll load the standard run library to give us high-level simulation control functions (e.g. running a simulation for a given period of time):"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -1207,7 +1223,7 @@
     "        h.continuerun(25)\n",
     "        f.line(t, list(soma_v),\n",
     "               line_width=width,\n",
-    "               legend_label='amp=%g' % amp if my_cell.dend.nseg == 1 else None,\n",
+    "               legend_label='amp={:.3g}'.format(amp) if my_cell.dend.nseg == 1 else '',\n",
     "               color=color)\n",
     "        f.line(t, list(dend_v),\n",
     "               line_width=width,\n",
@@ -1277,7 +1293,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.6"
+   "version": "3.7.7"
   }
  },
  "nbformat": 4,
diff --git a/ball-and-stick-2.ipynb b/ball-and-stick-2.ipynb
index af0c4fce98..b2f176b12a 100644
--- a/ball-and-stick-2.ipynb
+++ b/ball-and-stick-2.ipynb
@@ -182,7 +182,40 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "If you are writing a script to do this, and revising the classes as we make changes, everything should be good. If you are following along in a Jupyter notebook, you will need to rerun the definition of BallAndStick above for the changes to take effect."
+    "If you are writing a script to do this, and revising the classes as we make changes, everything should be good. If you are following along in a Jupyter notebook, you will need to rerun the definition of BallAndStick above for the changes to take effect:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Run only for jupyter\n",
+    "class BallAndStick(Cell):\n",
+    "    name = 'BallAndStick'\n",
+    "    def _setup_morphology(self):\n",
+    "        self.soma = h.Section(name='soma', cell=self)\n",
+    "        self.dend = h.Section(name='dend', cell=self)\n",
+    "        self.dend.connect(self.soma)\n",
+    "        self.soma.L = self.soma.diam = 12.6157\n",
+    "        self.dend.L = 200\n",
+    "        self.dend.diam = 1\n",
+    "    def _setup_biophysics(self):\n",
+    "        for sec in self.all:\n",
+    "            sec.Ra = 100    # Axial resistance in Ohm * cm\n",
+    "            sec.cm = 1      # Membrane capacitance in micro Farads / cm^2\n",
+    "        self.soma.insert('hh')                                          \n",
+    "        for seg in self.soma:\n",
+    "            seg.hh.gnabar = 0.12  # Sodium conductance in S/cm2\n",
+    "            seg.hh.gkbar = 0.036  # Potassium conductance in S/cm2\n",
+    "            seg.hh.gl = 0.0003    # Leak conductance in S/cm2\n",
+    "            seg.hh.el = -54.3     # Reversal potential in mV\n",
+    "        # Insert passive current in the dendrite\n",
+    "        self.dend.insert('pas')                 \n",
+    "        for seg in self.dend:\n",
+    "            seg.pas.g = 0.001  # Passive conductance in S/cm2\n",
+    "            seg.pas.e = -65    # Leak reversal potential mV\n"
    ]
   },
   {
@@ -718,7 +751,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.3"
+   "version": "3.7.7"
   }
  },
  "nbformat": 4,
diff --git a/ball-and-stick-3.ipynb b/ball-and-stick-3.ipynb
index 5c5134b88c..5a49827024 100644
--- a/ball-and-stick-3.ipynb
+++ b/ball-and-stick-3.ipynb
@@ -392,7 +392,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.3"
+   "version": "3.7.7"
   }
  },
  "nbformat": 4,
diff --git a/ball-and-stick-4.ipynb b/ball-and-stick-4.ipynb
index e34e3cb452..b10375f725 100644
--- a/ball-and-stick-4.ipynb
+++ b/ball-and-stick-4.ipynb
@@ -73,16 +73,16 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
    "source": [
+    "```python\n",
     "from neuron import h\n",
     "h.nrnmpi_init()       # initialize MPI\n",
     "pc = h.ParallelContext()\n",
     "print('I am {} of {}'.format(pc.id(), pc.nhost()))\n",
-    "h.quit()              # necessary to avoid a warning message on parallel exit on some systems"
+    "h.quit()              # necessary to avoid a warning message on parallel exit on some systems\n",
+    "```"
    ]
   },
   {
@@ -96,13 +96,13 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<pre>\n",
+    "```bash\n",
     "numprocs=4\n",
     "I am 1 of 4\n",
     "I am 2 of 4\n",
     "I am 3 of 4\n",
     "I am 0 of 4\n",
-    "</pre>"
+    "```"
    ]
   },
   {
@@ -134,11 +134,10 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
    "source": [
+    "```python\n",
     "from neuron import h\n",
     "from ballandstick import BallAndStick\n",
     "\n",
@@ -200,7 +199,8 @@
     "            nc = pc.gid_connect(source_gid, target.syn)\n",
     "            nc.weight[0] = self._syn_w\n",
     "            nc.delay = self._syn_delay\n",
-    "            target._ncs.append(nc)        "
+    "            target._ncs.append(nc)\n",
+    "```"
    ]
   },
   {
@@ -234,11 +234,10 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
    "source": [
+    "```python\n",
     "from neuron import h\n",
     "from neuron.units import ms, mV\n",
     "import matplotlib.pyplot as plt\n",
@@ -262,7 +261,8 @@
     "\n",
     "pc.barrier()\n",
     "pc.done()\n",
-    "h.quit()"
+    "h.quit()\n",
+    "```"
    ]
   },
   {
@@ -297,7 +297,20 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<tt>python test_ring1.py</tt>"
+    "`python test_ring1.py`"
+   ]
+  },
+  {
+   "attachments": {
+    "test_ring1.png": {
+     "image/png": 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"
+    }
+   },
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You should see:\n",
+    "![test_ring1.png](attachment:test_ring1.png)"
    ]
   },
   {
@@ -311,7 +324,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<tt>mpiexec -n 2 python test_ring1.py</tt>"
+    "`mpiexec -n 2 python test_ring1.py`"
    ]
   },
   {
@@ -336,11 +349,10 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
    "source": [
+    "```python\n",
     "from neuron import h\n",
     "from neuron.units import ms, mV\n",
     "import matplotlib.pyplot as plt\n",
@@ -372,7 +384,8 @@
     "\n",
     "pc.barrier()\n",
     "pc.done()\n",
-    "h.quit()"
+    "h.quit()\n",
+    "```"
    ]
   },
   {
@@ -381,6 +394,26 @@
    "source": [
     "Running this via e.g. `mpiexec -n 2 python test_ring2.py` displays the familiar raster plot. If you are wondering why node 0 was the one chosen to make the plot, it is because that is the only node that is guaranteed to exist (nothing else exists if there is only one process being used for the simulation)."
    ]
+  },
+  {
+   "attachments": {
+    "test_ring2.png": {
+     "image/png": "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"
+    }
+   },
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You should see:\n",
+    "![test_ring2.png](attachment:test_ring2.png)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -399,7 +432,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.3"
+   "version": "3.7.7"
   }
  },
  "nbformat": 4,
diff --git a/pythontutorial.ipynb b/pythontutorial.ipynb
index a47c7d4c43..c955e3cfc5 100644
--- a/pythontutorial.ipynb
+++ b/pythontutorial.ipynb
@@ -178,12 +178,12 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "print(my_name + my_age)"
+    "```python\n",
+    "print(my_name + my_age)\n",
+    "```"
    ]
   },
   {
@@ -938,12 +938,12 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "my_tuple[1] = 2"
+    "```python\n",
+    "my_tuple[1] = 2\n",
+    "```"
    ]
   },
   {
@@ -1598,7 +1598,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.3"
+   "version": "3.7.7"
   }
  },
  "nbformat": 4,
diff --git a/scripting-neuron-basics.ipynb b/scripting-neuron-basics.ipynb
index 3bfb602a66..b01bebd2d9 100644
--- a/scripting-neuron-basics.ipynb
+++ b/scripting-neuron-basics.ipynb
@@ -1285,7 +1285,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.4"
+   "version": "3.7.7"
   }
  },
  "nbformat": 4,