diff --git a/examples/Index.ipynb b/examples/Index.ipynb
index 6dc6921..359dc88 100644
--- a/examples/Index.ipynb
+++ b/examples/Index.ipynb
@@ -1,117 +1,105 @@
 {
- "metadata": {
-  "kernelspec": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "display_name": "IPython (Python 3)",
-   "language": "python",
-   "name": "python3"
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Physical Quantities"
+   ]
   },
-  "name": "",
-  "signature": "sha256:4e42a13d33ae49e4d1b53a3b08cee84e8219c693f9de6b85ed4fda2bc6a661ad"
- },
- "nbformat": 3,
- "nbformat_minor": 0,
- "worksheets": [
   {
-   "cells": [
-    {
-     "cell_type": "heading",
-     "level": 1,
-     "metadata": {},
-     "source": [
-      "Physical Quantities"
-     ]
-    },
-    {
-     "cell_type": "markdown",
-     "metadata": {
-      "variables": {}
-     },
-     "source": [
-      "PhysicalQuantities is a python module that allows calculations to be aware of physical units. Built-in unit conversion ensures that calculations will result in the correct unit.\n",
-      "\n",
-      "The module also contains an extension for IPython. This allows much simplified usage by typing in physical quantities as number and unit:"
-     ]
-    },
-    {
-     "cell_type": "code",
-     "collapsed": false,
-     "input": [
-      "a = 1m ; b = 1s\n",
-      "print(\"a=\", a, \", b=\",b,\", a/b=\", a/b)"
-     ],
-     "language": "python",
-     "metadata": {
-      "run_control": {
-       "breakpoint": false
-      }
-     },
-     "outputs": [
-      {
-       "output_type": "stream",
-       "stream": "stdout",
-       "text": [
-        "a= 1 m , b= 1 s , a/b= 1.0 m/s\n"
-       ]
-      }
-     ],
-     "prompt_number": 1
-    },
-    {
-     "cell_type": "markdown",
-     "metadata": {
-      "variables": {}
-     },
-     "source": [
-      "The Github repository for this module can be found here: https://github.com/juhasch/PhysicalQuantities\n",
-      "\n",
-      "This module is based on the IPython extension by Georg Brandl: https://bitbucket.org/birkenfeld/ipython-physics.\n",
-      "It was converted into a standalone Python module and extended heavily to be as flexible as possible."
-     ]
-    },
-    {
-     "cell_type": "heading",
-     "level": 2,
-     "metadata": {},
-     "source": [
-      "Example Notebooks"
-     ]
-    },
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "PhysicalQuantities is a python module that allows calculations to be aware of physical units. Built-in unit conversion ensures that calculations will result in the correct unit.\n",
+    "\n",
+    "The module also contains an extension for IPython. This allows much simplified usage by typing in physical quantities as number and unit:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": false,
+    "run_control": {
+     "breakpoint": false
+    }
+   },
+   "outputs": [
     {
-     "cell_type": "markdown",
-     "metadata": {
-      "variables": {}
-     },
-     "source": [
-      "* [Basics and Installation](pq-basics.ipynb)\n",
-      "* [Using Physical Quantities in IPython](pq-ipython.ipynb)\n",
-      "* [Output Formatting](pq-formatting.ipynb)\n",
-      "* [Doing dB Calculations](pq-dbquantity.ipynb)\n",
-      "* [Using Numpy Arrays](pq-numpy.ipynb)\n",
-      "* [Autoscaling](pq-autoscale.ipynb)\n",
-      "* [SymPy](pq-sympy.ipynb)\n",
-      "* [Uncertainties](pq-uncertainties.ipynb)\n",
-      "* [Practical Example - Calculate a RC Circuit](pq-example.ipynb)\n"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "a= 1 m , b= 1 s , a/b= 1.0 m/s\n"
      ]
-    },
-    {
-     "cell_type": "code",
-     "collapsed": false,
-     "input": [],
-     "language": "python",
-     "metadata": {
-      "run_control": {
-       "breakpoint": false
-      }
-     },
-     "outputs": [],
-     "prompt_number": 1
     }
    ],
-   "metadata": {}
+   "source": [
+    "a = 1m ; b = 1s\n",
+    "print(\"a=\", a, \", b=\",b,\", a/b=\", a/b)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The Github repository for this module can be found here: https://github.com/juhasch/PhysicalQuantities\n",
+    "\n",
+    "This module is based on the IPython extension by Georg Brandl: https://bitbucket.org/birkenfeld/ipython-physics.\n",
+    "It was converted into a standalone Python module and extended heavily to be as flexible as possible."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Example Notebooks"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "* [Basics and Installation](pq-basics.ipynb)\n",
+    "* [Using Physical Quantities in IPython](pq-ipython.ipynb)\n",
+    "* [Output Formatting](pq-formatting.ipynb)\n",
+    "* [Doing dB Calculations](pq-dbquantity.ipynb)\n",
+    "* [Using Numpy Arrays](pq-numpy.ipynb)\n",
+    "* [Autoscaling](pq-autoscale.ipynb)\n",
+    "* [SymPy](pq-sympy.ipynb)\n",
+    "* [Uncertainties](pq-uncertainties.ipynb)\n",
+    "* [Practical Example - Calculate a RC Circuit](pq-example.ipynb)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
   }
- ]
-}
\ No newline at end of file
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.4.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/examples/pq-autoscale.ipynb b/examples/pq-autoscale.ipynb
index 9a5646a..9ca04ae 100644
--- a/examples/pq-autoscale.ipynb
+++ b/examples/pq-autoscale.ipynb
@@ -23,6 +23,9 @@
    "outputs": [
     {
      "data": {
+      "text/latex": [
+       "1.0 $\\text{mm}$"
+      ],
       "text/markdown": [
        "1.0 $\\text{mm}$"
       ],
@@ -49,6 +52,9 @@
    "outputs": [
     {
      "data": {
+      "text/latex": [
+       "300.0 $\\text{µs}$"
+      ],
       "text/markdown": [
        "300.0 $\\text{µs}$"
       ],
@@ -75,6 +81,9 @@
    "outputs": [
     {
      "data": {
+      "text/latex": [
+       "1.0 $\\text{m}$"
+      ],
       "text/markdown": [
        "1.0 $\\text{m}$"
       ],
@@ -99,8 +108,20 @@
     "collapsed": false
    },
    "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "s 4\n",
+      "A 2\n",
+      "m 2\n"
+     ]
+    },
     {
      "data": {
+      "text/latex": [
+       "3.00 $\\text{nF}$"
+      ],
       "text/markdown": [
        "3.00 $\\text{nF}$"
       ],
@@ -145,9 +166,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.4.3"
+   "version": "3.4.4"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/examples/pq-basics.ipynb b/examples/pq-basics.ipynb
index d11c49e..048a568 100644
--- a/examples/pq-basics.ipynb
+++ b/examples/pq-basics.ipynb
@@ -48,6 +48,13 @@
     "import PhysicalQuantities as pq"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Basic Usage"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -61,16 +68,34 @@
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "1.1 $\\text{m}$"
+      ],
+      "text/markdown": [
+       "1.1 $\\text{m}$"
+      ],
+      "text/plain": [
+       "1.1 m"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "g = pq.PhysicalQuantity(1.1, 'm')"
+    "a = pq.PhysicalQuantity(1.1, 'm')\n",
+    "a"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "or as the shortcut `Q()`:"
+    "or using the shortcut `q`:"
    ]
   },
   {
@@ -79,16 +104,30 @@
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(1 mm, 2 mm)"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "g = pq.Q(1.1, 'm')"
+    "from PhysicalQuantities import q\n",
+    "a = 1 * q.mm\n",
+    "b = 2 * q['mm']\n",
+    "a, b"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "This creates a new `PhysicalQuantity` object:"
+    "Calling `\"a = 1 * q.mm\"` creates a new `PhysicalQuantity` object:"
    ]
   },
   {
@@ -102,14 +141,14 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "object: 1.1 m\n",
+      "object: 1 mm\n",
       "object type : <class 'PhysicalQuantities.Quantity.PhysicalQuantity'>\n"
      ]
     }
    ],
    "source": [
-    "print(\"object: %s\" % g)\n",
-    "print(\"object type : %s\" % type(g))"
+    "print(\"object: %s\" % a)\n",
+    "print(\"object type : %s\" % type(a))"
    ]
   },
   {
@@ -130,18 +169,18 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "value: 1.1\n",
-      "value type: <class 'float'>\n",
-      "unit: m\n",
+      "value: 1\n",
+      "value type: <class 'int'>\n",
+      "unit: mm\n",
       "unit type: <class 'PhysicalQuantities.Unit.PhysicalUnit'>\n"
      ]
     }
    ],
    "source": [
-    "print(\"value: %s\" % g.value)\n",
-    "print(\"value type: %s\" % type(g.value))\n",
-    "print(\"unit: %s\" % g.unit)\n",
-    "print(\"unit type: %s\" % type(g.unit))"
+    "print(\"value: %s\" % a.value)\n",
+    "print(\"value type: %s\" % type(a.value))\n",
+    "print(\"unit: %s\" % a.unit)\n",
+    "print(\"unit type: %s\" % type(a.unit))"
    ]
   },
   {
@@ -164,10 +203,10 @@
      "text": [
       "g = 1.1 m\n",
       "g in mm = 1100.0 mm\n",
-      "x = 2 m*kg/s^2\n",
+      "x = 2 kg*m/s^2\n",
       "x in N = 2.0 N\n",
       "u = 1 V\n",
-      "u in base units = 1.0 m^2*kg/s^3/A\n"
+      "u in base units = 1.0 kg*m^2/s^3/A\n"
      ]
     }
    ],
@@ -255,6 +294,35 @@
     "print(g.km_)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "It is also possible to remove the unit without implicit scaling, however this might be **dangerous**:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1.1"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "g._"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -273,7 +341,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {
     "collapsed": false
    },
@@ -284,7 +352,7 @@
        "[1, 2, 3]"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -309,7 +377,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {
     "collapsed": false
    },
@@ -326,7 +394,7 @@
        "<PhysicalUnit s**3*m**2/kg/A**2>"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -337,7 +405,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {
     "collapsed": false,
     "run_control": {
@@ -351,7 +419,7 @@
        "PhysicalQuantities.Unit.PhysicalUnit"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -366,13 +434,13 @@
    "source": [
     "The unit is stored in a `PhysicalUnit` class. This class has a number of attributes:\n",
     " * `factor` - scaling factor from base units\n",
-    " * `powers` - list of base units contained in unit\n",
+    " * `powers` - list of SI base units contained in unit. All other units can be reduced to these base units.\n",
     " * `prefixed` - unit is a scaled version of a base unit"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {
     "collapsed": false
    },
@@ -383,7 +451,7 @@
        "(0.001, True)"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -394,7 +462,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {
     "collapsed": false,
     "run_control": {
@@ -407,26 +475,59 @@
      "output_type": "stream",
      "text": [
       "['m', 'kg', 's', 'A', 'K', 'mol', 'cd', 'rad', 'sr']\n",
-      "[2, -1, 3, -2, 0, 0, 0, 0, 0]\n",
-      "s^3*m^2/kg/A^2\n"
+      "[1, 0, 0, 0, 0, 0, 0, 0, 0]\n",
+      "m\n"
      ]
     }
    ],
    "source": [
-    "print(pq.base_names) # list of base units\n",
+    "from PhysicalQuantities.Unit import base_names\n",
+    "print(base_names) # list containing names of base units\n",
+    "a = q.m\n",
     "print(a.unit.powers)\n",
-    "print(a.unit)"
+    "print(a.unit.baseunit)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A more complex example:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "metadata": {
     "collapsed": false,
     "run_control": {
      "breakpoint": false
     }
    },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['m', 'kg', 's', 'A', 'K', 'mol', 'cd', 'rad', 'sr']\n",
+      "[2, -1, 3, -2, 0, 0, 0, 0, 0]\n",
+      "s^3*m^2/kg/A^2\n"
+     ]
+    }
+   ],
+   "source": [
+    "a = pq.Q([1,2,3], 'm**2*s**3/A**2/kg')\n",
+    "print(base_names)\n",
+    "print(a.unit.powers)\n",
+    "print(a.unit.baseunit)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": []
   }
@@ -447,9 +548,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.4.3"
+   "version": "3.4.4"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/examples/pq-dbquantity.ipynb b/examples/pq-dbquantity.ipynb
index f75e1cc..7af4926 100644
--- a/examples/pq-dbquantity.ipynb
+++ b/examples/pq-dbquantity.ipynb
@@ -2,9 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "metadata": {
-    "variables": {}
-   },
+   "metadata": {},
    "source": [
     "Back to [Index](index.ipynb)"
    ]
@@ -20,7 +18,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The IPython extension for dB units is loaded using:"
+    "dB calculations can also be performed using the `dBQuantity` class:"
    ]
   },
   {
@@ -29,16 +27,29 @@
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1 dBm"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "%reload_ext PhysicalQuantities.dBQuantity_ipython"
+    "from PhysicalQuantities.dBQuantity import dBQuantity\n",
+    "a = dBQuantity(1, 'dBm')\n",
+    "a"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "It provides an easy way to do dB calculations:"
+    "The IPython extension provides an easy way to do dB calculations:"
    ]
   },
   {
@@ -49,20 +60,28 @@
    },
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0 dBm\n",
-      "-30.0 dBW\n",
-      "0.001 W\n"
-     ]
+     "data": {
+      "text/plain": [
+       "10 dBm"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
     "p = 0 dBm\n",
-    "print(p)\n",
-    "print(p.dBW)\n",
-    "print(p.W)"
+    "g = 20 dB\n",
+    "a = 10 dB\n",
+    "p + g - a"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The list of supported dBUnits is small:"
    ]
   },
   {
@@ -73,37 +92,71 @@
    },
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "3 dBm\n"
-     ]
+     "data": {
+      "text/plain": [
+       "['dBnV',\n",
+       " 'dB',\n",
+       " 'dBV',\n",
+       " 'dBi',\n",
+       " 'dBnA',\n",
+       " 'dBuA',\n",
+       " 'dBc',\n",
+       " 'dBA',\n",
+       " 'dBW',\n",
+       " 'dBuV',\n",
+       " 'dBd',\n",
+       " 'dBm',\n",
+       " 'dBmA',\n",
+       " 'dBsm',\n",
+       " 'dBmV']"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
-    "g = 3 dB\n",
-    "print (p+g)"
+    "from PhysicalQuantities.dBQuantity import dB_unit_table\n",
+    "list(dB_unit_table.keys())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Converting to other units is easy:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 4,
    "metadata": {
-    "collapsed": false
+    "collapsed": false,
+    "scrolled": true
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "0 dBm\n",
       "-30.0 dBW\n",
-      "-30.0\n"
+      "0.001 W\n"
      ]
     }
    ],
    "source": [
+    "print(p)\n",
     "print(p.dBW)\n",
-    "print(p.dBW_)"
+    "print(p.W)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Absolute values (`dBm` or `dBW`) are handled differently compared to unitless `dB`:"
    ]
   },
   {
@@ -112,9 +165,21 @@
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3.0102999566398121 dBW"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "from PhysicalQuantities.dBQuantity import dBQuantity"
+    "p = 0 dBW\n",
+    "p+p"
    ]
   },
   {
@@ -123,23 +188,101 @@
    "metadata": {
     "collapsed": false
    },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0 dBW"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "g = 0 dB\n",
+    "p+g"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The `_` attribute to remove units is available too:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0.1 dBm\n"
+      "-30.0 dBW\n",
+      "-30.0\n",
+      "0\n"
      ]
     }
    ],
+   "source": [
+    "p = 0 dBm\n",
+    "print(p.dBW)\n",
+    "print(p.dBW_)\n",
+    "print(p._)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Internal representation"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Calling the `dBQuantity()` constructor creates the desired object:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.1 dBm"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "a = dBQuantity(0.1,'dBm', islog=True)\n",
-    "print(a)"
+    "a"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The information is stored in two attributes:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 13,
    "metadata": {
     "collapsed": false
    },
@@ -150,61 +293,100 @@
        "(0.1, 'dBm')"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "a.value, a.unit"
+    "a.value, a.unitname"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The unit itself is represented as `dBUnit` object:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 17,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "u = a.unit"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The unit contains the name, the conversion factor (10 or 20), the reference impedance and the underlying PhysicalUnit:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
-      "text/markdown": [
-       "0.0010232929922807542 $\\text{W}$"
-      ],
       "text/plain": [
-       "0.0010232929922807542 W"
+       "('dBm', 10, 0, 50 Ohm, <PhysicalUnit mW>)"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "a.W"
+    "u.name, u.factor, u.offset, u.z0, u.physicalunit"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "For relative dB values, offset and physicalunit are unknown:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 23,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
-      "text/markdown": [
-       "1.02 $\\text{mW}$"
-      ],
       "text/plain": [
-       "1.02 mW"
+       "('dB', 0, 0, 50 Ohm, None)"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 23,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
+   "source": [
+    "a = 0dB\n",
+    "u = a.unit\n",
+    "u.name, u.factor, u.offset, u.z0, u.physicalunit"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
    "source": [
     "%precision 2\n",
     "a.mW"
@@ -214,12 +396,42 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Helper function to generate dB values from a linear value:"
+    "Calling with `islog=False` converts the value to log:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "a = dBQuantity(0.1,'dBm', islog=False)\n",
+    "a"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Conversion from and to dB"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "from PhysicalQuantities.dBQuantity import dB10, dB20"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 28,
    "metadata": {
     "collapsed": false
    },
@@ -227,22 +439,21 @@
     {
      "data": {
       "text/plain": [
-       "0.00 dBm"
+       "10.0 dB"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 28,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "from PhysicalQuantities.dBQuantity import dB, dB10, dB20\n",
-    "dB(1 mW)"
+    "dB10(10)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 29,
    "metadata": {
     "collapsed": false
    },
@@ -250,21 +461,21 @@
     {
      "data": {
       "text/plain": [
-       "10.00 dB"
+       "20.0 dB"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 29,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "dB10(10)"
+    "dB20(10)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 31,
    "metadata": {
     "collapsed": false
    },
@@ -272,16 +483,97 @@
     {
      "data": {
       "text/plain": [
-       "20.00 dB"
+       "0.0 dBm"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 31,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "dB20(10)"
+    "p = (1mW).dB\n",
+    "p"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "1.0 $\\text{mW}$"
+      ],
+      "text/markdown": [
+       "1.0 $\\text{mW}$"
+      ],
+      "text/plain": [
+       "1.0 mW"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "p.lin"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "For relative dB values, the conversion factor to linear has to be specified, either $10^{(value/10)}$ or $10^{(value/20)}$. This can be simplified by using the properties `lin10` or `lin20`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "10.0"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "a = 10 dB\n",
+    "a.lin10"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3.1622776601683795"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "a.lin20"
    ]
   },
   {
@@ -310,9 +602,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.4.3"
+   "version": "3.4.4"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/examples/pq-example.ipynb b/examples/pq-example.ipynb
index 5da9dc2..7c009de 100644
--- a/examples/pq-example.ipynb
+++ b/examples/pq-example.ipynb
@@ -9,7 +9,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 25,
    "metadata": {
     "code_folding": [],
     "collapsed": false,
@@ -25,24 +25,17 @@
       "The PhysicalQuantities.ipython extension is already loaded. To reload it, use:\n",
       "  %reload_ext PhysicalQuantities.ipython\n"
      ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "'%.2f'"
-      ]
-     },
-     "execution_count": 1,
-     "metadata": {},
-     "output_type": "execute_result"
     }
    ],
    "source": [
     "# Imports\n",
+    "%precision 2\n",
     "import PhysicalQuantities as pq\n",
+    "import PhysicalQuantities.numpywrapper as nw\n",
     "%load_ext PhysicalQuantities.ipython\n",
     "from PhysicalQuantities.constants import eps0\n",
-    "%precision 2"
+    "def disp(s):\n",
+    "    display(HTML(s))\n"
    ]
   },
   {
@@ -54,76 +47,77 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "variables": {}
-   },
+   "metadata": {},
    "source": [
-    "<img  src=\"/notebooks/PhysicalQuantities/images/rc.png\"/>"
+    "![image1](images/rc.png)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "variables": {}
-   },
+   "metadata": {},
    "source": [
     "Let's start with calculating the capacitance of a simple parallel plate capacitor:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 26,
    "metadata": {
     "collapsed": false,
+    "hide_input": false,
     "run_control": {
-     "breakpoint": false
+     "breakpoint": false,
+     "marked": true
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "Capacitor value $C$ = 26.56 pF"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "A = 1 mm * 1 mm # Plate area\n",
     "d = 1 um        # Plate distance\n",
     "eps_r = 3       # Permittivity of dielectric material\n",
-    "C  = (eps0*eps_r*A) / d"
+    "C  = (eps0*eps_r*A) / d\n",
+    "disp(\"Capacitor value $C$ = %s\" % C.pF)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "variables": {
-     " C.pF ": "26.56 $\\text{pF}$"
-    }
-   },
-   "source": [
-    "The capacitor value is $C$ = {{ C.pF }}"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "variables": {}
-   },
+   "metadata": {},
    "source": [
     "The resistor is a thick film resistor:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 27,
    "metadata": {
     "collapsed": false,
+    "hide_input": false,
     "run_control": {
-     "breakpoint": false
+     "breakpoint": false,
+     "marked": true
     }
    },
    "outputs": [
     {
      "data": {
-      "text/latex": [
+      "text/html": [
        "Resistor value $R$ = 15.00 kOhm"
       ],
       "text/plain": [
-       "<IPython.core.display.Latex object>"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -131,11 +125,11 @@
     }
    ],
    "source": [
-    "rho = 10 Ohm * 1 mm # Material resistivity\n",
+    "ρ = 10 Ohm * 1 mm # Material resistivity\n",
     "t = 10 um           # Sheet thickness\n",
     "L = 150 um          # Structure length\n",
     "W = 10 um           # Structure width\n",
-    "Rs = rho / t \n",
+    "Rs = ρ / t \n",
     "R = Rs * L / W\n",
     "disp(\"Resistor value $R$ = %s\" % R.kOhm)"
    ]
@@ -149,37 +143,41 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 28,
    "metadata": {
     "collapsed": false,
+    "hide_input": false,
     "run_control": {
-     "breakpoint": false
+     "breakpoint": false,
+     "marked": true
     }
    },
    "outputs": [],
    "source": [
     "u0 = 1. V\n",
-    "tau = 1/(R*C)\n",
-    "t = pq.linspace(0,4/tau,100).us"
+    "τ = 1/(R*C)\n",
+    "t = nw.linspace(0, 4/τ.base, 100).us"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 29,
    "metadata": {
     "collapsed": false,
+    "hide_input": false,
     "run_control": {
-     "breakpoint": false
+     "breakpoint": false,
+     "marked": true
     }
    },
    "outputs": [
     {
      "data": {
-      "text/latex": [
+      "text/html": [
        "Initial current is $i_0$ = 66.67 uA"
       ],
       "text/plain": [
-       "<IPython.core.display.Latex object>"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -188,7 +186,7 @@
    ],
    "source": [
     "i0 = u0/R\n",
-    "i = (i0*e**(-t*tau)).uA\n",
+    "i = (i0*e**(-t*τ)).uA\n",
     "disp(\"Initial current is $i_0$ = %s\" % i0.uA)"
    ]
   },
@@ -201,7 +199,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 23,
    "metadata": {
     "collapsed": false,
     "run_control": {
@@ -211,9 +209,10 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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ii2WTStoexNIQT0IcXWI+b8/b8/a6s72G7Uzljd9/95C+E8c3b6eTqZI7+ftI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\nl3jzcObrBmcskwtMuXph/G5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KZW5kb2JqCjI4IDAgb2JqCjw8IC9MZW5ndGggMzAwIC9GaWx0ZXIgL0ZsYXRl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\nCnN0YXJ0eHJlZgoxNDg3NQolJUVPRgo=\n",
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fBPtsBFwJ7AasBV4CTlfVFWGOXVf06OGmkj76aNhtNzctgTHGlFqoYqOqj4tI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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x64ad668>"
+       "<matplotlib.figure.Figure at 0x11084cdd8>"
       ]
      },
      "metadata": {},
@@ -221,16 +220,16 @@
     }
    ],
    "source": [
-    "plot(t.us_,i.uA_)\n",
+    "plot(t._,i._)\n",
     "grid()\n",
     "title('Circuit Current')\n",
-    "xlabel('Time in %s' % t.unit._repr_latex_())\n",
-    "ylabel('Current in %s' %  i.unit._repr_latex_());"
+    "xlabel('Time in %s' % t.unit)\n",
+    "ylabel('Current in %s' % i.unit);"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 24,
    "metadata": {
     "collapsed": false,
     "run_control": {
@@ -240,9 +239,10 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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I0wakYvMe8CCpc+Cr8/yxCD4oKVQrmQuQmfVbbu68ArARsGGeVgOmAg+ReqP/vzx/rNUe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\nr5Ja09XT4cDlrVp8ADr9Fw6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7PrtpXauGe6hUxMJTOBMhxAywgSMxPR1agxmiA3vD1T1tiWuBwm+VmLtqwdOR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\n",
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ySp5GQG/gFRF5BCgCWgNvAX9T1R9zyGOSzJzp9nhOOAGuuSbuNMaYQpRTLzgR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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7bbf780>"
+       "<matplotlib.figure.Figure at 0x110953978>"
       ]
      },
      "metadata": {},
@@ -251,18 +251,18 @@
    ],
    "source": [
     "uc = u0 - i*R\n",
-    "plot(uc.V_)\n",
+    "plot(t._, uc._)\n",
     "title('Capacitor Voltage')\n",
     "grid()\n",
-    "xlabel('Time in $\\mu s$')\n",
-    "ylabel('Voltage in $V$');"
+    "xlabel('Time in %s' % t.unit)\n",
+    "ylabel('Voltage in %s' % uc.unit);"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "collapsed": false
+    "collapsed": true
    },
    "outputs": [],
    "source": []
@@ -284,9 +284,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.4.3"
+   "version": "3.4.4"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/examples/pq-formatting.ipynb b/examples/pq-formatting.ipynb
index e689233..33d2e33 100644
--- a/examples/pq-formatting.ipynb
+++ b/examples/pq-formatting.ipynb
@@ -26,6 +26,9 @@
       "text/latex": [
        "2.3333333333333335 $\\frac{1}{\\text{m}}$"
       ],
+      "text/markdown": [
+       "2.3333333333333335 $\\frac{1}{\\text{m}}$"
+      ],
       "text/plain": [
        "2.3333333333333335 1/m"
       ]
@@ -66,6 +69,9 @@
       "text/latex": [
        "2.3 $\\frac{1}{\\text{m}}$"
       ],
+      "text/markdown": [
+       "2.3 $\\frac{1}{\\text{m}}$"
+      ],
       "text/plain": [
        "2.3 1/m"
       ]
@@ -162,7 +168,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 5,
    "metadata": {
     "collapsed": false,
     "run_control": {
@@ -173,13 +179,16 @@
     {
      "data": {
       "text/latex": [
-       "1.235 $\\text{mm}$"
+       "2.333 $\\frac{1}{\\text{m}}$"
+      ],
+      "text/markdown": [
+       "2.333 $\\frac{1}{\\text{m}}$"
       ],
       "text/plain": [
-       "1.235 mm"
+       "2.333 1/m"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -198,7 +207,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 6,
    "metadata": {
     "collapsed": false,
     "run_control": {
@@ -236,7 +245,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 7,
    "metadata": {
     "collapsed": false,
     "run_control": {
@@ -317,9 +326,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.4.3"
+   "version": "3.4.4"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/examples/pq-ipython.ipynb b/examples/pq-ipython.ipynb
index fd5bbd4..46f15c4 100644
--- a/examples/pq-ipython.ipynb
+++ b/examples/pq-ipython.ipynb
@@ -150,7 +150,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "1 N*m\n",
+      "1 m*N\n",
       "1.0 J\n"
      ]
     }
@@ -201,13 +201,6 @@
     "print(\"u = %s\" %u)"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "There is limited support for the `uncertainties` module. This should improve in the future."
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 7,
@@ -219,54 +212,75 @@
    },
    "outputs": [
     {
-     "ename": "ImportError",
-     "evalue": "No module named 'uncertainties'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mImportError\u001b[0m                               Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-7-caf4a16ea7e8>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0muncertainties\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mufloat\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[0;31mImportError\u001b[0m: No module named 'uncertainties'"
-     ]
+     "data": {
+      "text/latex": [
+       "[1, 2, 3] $\\text{V}$"
+      ],
+      "text/markdown": [
+       "[1, 2, 3] $\\text{V}$"
+      ],
+      "text/plain": [
+       "[1, 2, 3] V"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
-    "from uncertainties import ufloat"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "x = ufloat(2, 0.25) * 1 m\n",
-    "x"
+    "a = [1, 2, 3] * 1V\n",
+    "a"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[1, 2, 3]"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "square = x**2  # Transparent calculations\n",
-    "square"
+    "a.value"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/latex": [
+       "[1, 2, 3, 1, 2, 3] $\\text{V}$"
+      ],
+      "text/markdown": [
+       "[1, 2, 3, 1, 2, 3] $\\text{V}$"
+      ],
+      "text/plain": [
+       "[1, 2, 3, 1, 2, 3] V"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "square - x*x"
+    "2*a"
    ]
   },
   {
@@ -287,24 +301,35 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<table><tr><th>Name</th><th>Base Unit</th><th>Quantity</th></tr><tr><td>Wb</td><td>1.0 $\\frac{\\text{m}^{2}\\cdot \\text{kg}}{\\text{A}\\cdot \\text{s}^2}$</td><td><a href=\"https://en.wikipedia.org/wiki/Weber_(unit)\" target=\"_blank\">Weber</a></td></tr><tr><td>s</td><td>1.0 $\\text{s}$</td><td><a href=\"https://en.wikipedia.org/wiki/Second\" target=\"_blank\">Second</a></td></tr><tr><td>h</td><td>3600.0 $\\text{s}$</td><td><a href=\"https://en.wikipedia.org/wiki/Hour\" target=\"_blank\">Hour</a></td></tr><tr><td>lx</td><td>1.0 $\\frac{\\text{cd}\\cdot \\text{sr}}{\\text{m}^2}$</td><td><a href=\"https://en.wikipedia.org/wiki/Lux\" target=\"_blank\">Lux</a></td></tr><tr><td>sr</td><td>1.0 $\\text{sr}$</td><td><a href=\"https://en.wikipedia.org/wiki/Steradian\" target=\"_blank\">Streradian</a></td></tr><tr><td>min</td><td>60.0 $\\text{s}$</td><td><a href=\"https://en.wikipedia.org/wiki/Hour\" target=\"_blank\">Minute</a></td></tr><tr><td>J</td><td>1.0 $\\frac{\\text{m}^{2}\\cdot \\text{kg}}{\\text{s}^2}$</td><td><a href=\"https://en.wikipedia.org/wiki/Joule\" target=\"_blank\">Joule</a></td></tr><tr><td>Pa</td><td>1.0 $\\frac{\\text{kg}}{\\text{m}\\cdot \\text{s}^2}$</td><td><a href=\"https://en.wikipedia.org/wiki/Pascal_(unit)\" target=\"_blank\">Pascal</a></td></tr><tr><td>arcsec</td><td>4.84813681109536e-06 $\\text{rad}$</td><td><a href=\"\" target=\"_blank\">seconds of arc</a></td></tr><tr><td>cd</td><td>1.0 $\\text{cd}$</td><td><a href=\"https://en.wikipedia.org/wiki/Candela\" target=\"_blank\">Candela</a></td></tr><tr><td>lm</td><td>1.0 $\\text{cd}\\cdot \\text{sr}$</td><td><a href=\"https://en.wikipedia.org/wiki/Lumen_(unit)\" target=\"_blank\">Lumen</a></td></tr><tr><td>H</td><td>1.0 $\\frac{\\text{m}^{2}\\cdot \\text{kg}}{\\text{A}^2\\cdot \\text{s}^2}$</td><td><a href=\"https://en.wikipedia.org/wiki/Henry_(unit)\" target=\"_blank\">Henry</a></td></tr><tr><td>m</td><td>1.0 $\\text{m}$</td><td><a href=\"https://en.wikipedia.org/wiki/Metre\" target=\"_blank\">Metre</a></td></tr><tr><td>T</td><td>1.0 $\\frac{\\text{kg}}{\\text{A}\\cdot \\text{s}^2}$</td><td><a href=\"https://en.wikipedia.org/wiki/Tesla_(unit)\" target=\"_blank\">Tesla</a></td></tr><tr><td>S</td><td>1.0 $\\frac{\\text{A}^{2}\\cdot \\text{s}^{3}}{\\text{m}^2\\cdot \\text{kg}}$</td><td><a href=\"https://en.wikipedia.org/wiki/Siemens_(unit)\" target=\"_blank\">Siemens</a></td></tr><tr><td>C</td><td>1.0 $\\text{A}\\cdot \\text{s}$</td><td><a href=\"https://en.wikipedia.org/wiki/Coulomb\" target=\"_blank\">Coulomb</a></td></tr><tr><td>deg</td><td>0.017453292519943295 $\\text{rad}$</td><td><a href=\"http://en.wikipedia.org/wiki/Degree_%28angle%29\" target=\"_blank\">Degree</a></td></tr><tr><td>K</td><td>1.0 $\\text{K}$</td><td><a href=\"https://en.wikipedia.org/wiki/Kelvin\" target=\"_blank\">Kelvin</a></td></tr><tr><td>g</td><td>0.001 $\\text{kg}$</td><td><a href=\"https://en.wikipedia.org/wiki/Kilogram\" target=\"_blank\">Gram</a></td></tr><tr><td>kg</td><td>1 $\\text{kg}$</td><td><a href=\"https://en.wikipedia.org/wiki/Kilogram\" target=\"_blank\">Kilogram</a></td></tr><tr><td>F</td><td>1.0 $\\frac{\\text{A}^{2}\\cdot \\text{s}^{4}}{\\text{m}^2\\cdot \\text{kg}}$</td><td><a href=\"https://en.wikipedia.org/wiki/Farad\" target=\"_blank\">Farad</a></td></tr><tr><td>W</td><td>1.0 $\\frac{\\text{m}^{2}\\cdot \\text{kg}}{\\text{s}^3}$</td><td><a href=\"https://en.wikipedia.org/wiki/Watt\" target=\"_blank\">Watt</a></td></tr><tr><td>arcmin</td><td>0.0002908882086657216 $\\text{rad}$</td><td><a href=\"\" target=\"_blank\">minutes of arc</a></td></tr><tr><td>Hz</td><td>1.0 $\\frac{1}{\\text{s}}$</td><td><a href=\"https://en.wikipedia.org/wiki/Hertz\" target=\"_blank\">Hertz</a></td></tr><tr><td>A</td><td>1.0 $\\text{A}$</td><td><a href=\"https://en.wikipedia.org/wiki/Ampere\" target=\"_blank\">Ampere</a></td></tr><tr><td>Ohm</td><td>1.0 $\\frac{\\text{m}^{2}\\cdot \\text{kg}}{\\text{A}^2\\cdot \\text{s}^3}$</td><td><a href=\"https://en.wikipedia.org/wiki/Ohm_(unit)\" target=\"_blank\">Ohm</a></td></tr><tr><td>N</td><td>1.0 $\\frac{\\text{m}\\cdot \\text{kg}}{\\text{s}^2}$</td><td><a href=\"https://en.wikipedia.org/wiki/Newton_(unit)\" target=\"_blank\">Newton</a></td></tr><tr><td>V</td><td>1.0 $\\frac{\\text{m}^{2}\\cdot \\text{kg}}{\\text{A}\\cdot \\text{s}^3}$</td><td><a href=\"https://en.wikipedia.org/wiki/Volt\" target=\"_blank\">Volt</a></td></tr><tr><td>rad</td><td>1.0 $\\text{rad}$</td><td><a href=\"https://en.wikipedia.org/wiki/Radian\" target=\"_blank\">Radian</a></td></tr><tr><td>mol</td><td>1.0 $\\text{mol}$</td><td><a href=\"https://en.wikipedia.org/wiki/Mole_(unit)\" target=\"_blank\">Mol</a></td></tr></table>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "import PhysicalQuantities as pq\n",
-    "pq.units_html_list()"
+    "from PhysicalQuantities import units_html_list\n",
+    "units_html_list()"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "collapsed": false,
-    "run_control": {
-     "breakpoint": false
-    }
+    "collapsed": true
    },
    "outputs": [],
    "source": []
@@ -313,6 +338,7 @@
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
+   "language": "python",
    "name": "python3"
   },
   "language_info": {
@@ -325,9 +351,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.4.2"
+   "version": "3.4.4"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/examples/pq-numpy.ipynb b/examples/pq-numpy.ipynb
index b70d18f..2e5bf9a 100644
--- a/examples/pq-numpy.ipynb
+++ b/examples/pq-numpy.ipynb
@@ -11,12 +11,23 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Units can be mixed with numpy arrays:"
+    "Units can be mixed with numpy arrays. There is a helper module for this called `numpywrapper`:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 1,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "import PhysicalQuantities.numpywrapper as nw"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
    "metadata": {
     "collapsed": false
    },
@@ -43,7 +54,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 3,
    "metadata": {
     "collapsed": false
    },
@@ -53,10 +64,10 @@
      "output_type": "stream",
      "text": [
       "[1 2 3] s\n",
-      "[[ 0.39  0.16  0.19  0.65]\n",
-      " [ 0.39  0.47  0.21  0.16]\n",
-      " [ 0.35  0.34  0.18  0.28]] m\n",
-      "0.28352011318205039 m\n"
+      "[[ 0.59994977  0.65224855  0.7659288   0.72208264]\n",
+      " [ 0.39490532  0.05471093  0.96338392  0.15117082]\n",
+      " [ 0.67440078  0.02391973  0.0248514   0.45410086]] m\n",
+      "0.45410086453921439 m\n"
      ]
     }
    ],
@@ -76,7 +87,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {
     "collapsed": false
    },
@@ -91,7 +102,7 @@
     }
    ],
    "source": [
-    "a = np.linspace(0,10,10) * 1m\n",
+    "a = nw.linspace(0, 10m, 10)\n",
     "a[0] = 3 m\n",
     "print(a)"
    ]
@@ -105,7 +116,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {
     "collapsed": false,
     "run_control": {
@@ -135,7 +146,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {
     "collapsed": false
    },
@@ -163,7 +174,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 7,
    "metadata": {
     "collapsed": false
    },
@@ -176,13 +187,13 @@
        "   -8.66e-01  -9.85e-01  -6.43e-01   6.43e-16] V)"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "t = linspace(0,10, 10) * 1 ms\n",
+    "t = nw.linspace(0, 10ms, 10)\n",
     "f = 100 Hz\n",
     "u = np.sin(2*np.pi*f*t) * 1 V\n",
     "t,u"
@@ -190,16 +201,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 10,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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r46XTrQcRPAHcRpoYatb22r5wkLYNvTuC+3MHsUobC2wmsVDuIGa5tXXhkFgE+BFubVjf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\nCjAFOCJ3kKoq5rz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wMDcwNDUgMDAwMDAgbiAKMDAwMDAwNjgyNSAwMDAwMCBuIAowMDAwMDA2ODU3\nIDAwMDAwIG4gCjAwMDAwMDY5NTYgMDAwMDAgbiAKMDAwMDAwNjk3NyAwMDAwMCBuIAowMDAwMDA2\nOTk4IDAwMDAwIG4gCjAwMDAwMDAwNjUgMDAwMDAgbiAKMDAwMDAwMDQwMCAwMDAwMCBuIAowMDAw\nMDAwMjA4IDAwMDAwIG4gCjAwMDAwMDExNzggMDAwMDAgbiAKMDAwMDAwNTY0NSAwMDAwMCBuIAow\nMDAwMDA1NDQ2IDAwMDAwIG4gCjAwMDAwMDUwOTYgMDAwMDAgbiAKMDAwMDAwNjY5OSAwMDAwMCBu\nIAowMDAwMDAxMTk4IDAwMDAwIG4gCjAwMDAwMDEzNjcgMDAwMDAgbiAKMDAwMDAwMTg5OCAwMDAw\nMCBuIAowMDAwMDAyNzUzIDAwMDAwIG4gCjAwMDAwMDI5NTEgMDAwMDAgbiAKMDAwMDAwMzIyNyAw\nMDAwMCBuIAowMDAwMDAzODEzIDAwMDAwIG4gCjAwMDAwMDQzNDIgMDAwMDAgbiAKMDAwMDAwNDUx\nMSAwMDAwMCBuIAowMDAwMDA3MTA1IDAwMDAwIG4gCnRyYWlsZXIKPDwgL1Jvb3QgMSAwIFIgL1Np\nemUgMjYgL0luZm8gMjUgMCBSID4+CnN0YXJ0eHJlZgo3MjUzCiUlRU9GCg==\n",
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KVqwInSa57r3XL/N+7LGhk0i2qBiJ5NkJJ0C7dnDjjaGTJFcqBSUlviBJYVAx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\nSUVORK5CYII=\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x10964ceb8>"
+       "<matplotlib.figure.Figure at 0x110493c50>"
       ]
      },
      "metadata": {},
@@ -207,41 +219,44 @@
     }
    ],
    "source": [
-    "plot(t.ms_,u.V_);"
+    "plot(t.us_,u.V_);"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "A helper function `PhysicalQuantities.linspace` simplifies specifying ranges:"
+    "Or simply using the current unit prefix:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 9,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
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9zWynxOar8EJzQ4mnvg18bWaNE3/+EKgLXAD/LURFQGPgkjREF8lajRv78OIr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\nAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x106b509e8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     }
    ],
    "source": [
-    "t = pq.linspace(0, 10ms, 11)\n",
-    "print(t)"
+    "plot(t._,u._);"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": null,
    "metadata": {
-    "collapsed": false
+    "collapsed": true
    },
    "outputs": [],
    "source": []
@@ -263,9 +278,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.4.3"
+   "version": "3.4.4"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }
diff --git a/examples/pq-sympy.ipynb b/examples/pq-sympy.ipynb
index d3082f8..5757d90 100644
--- a/examples/pq-sympy.ipynb
+++ b/examples/pq-sympy.ipynb
@@ -185,14 +185,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 9,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAF0AAAAxCAYAAAC4R6XiAAAABHNCSVQICAgIfAhkiAAABO9JREFU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\nSkpl8B/sEgahRtMp+gAAAABJRU5ErkJggg==\n",
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAFYAAAA0BAMAAADiRNKVAAAAMFBMVEX///8AAAAAAAAAAAAAAAAA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\n",
       "text/latex": [
        "$$\\int \\sqrt{\\frac{1}{x}}\\, dx$$"
       ],
@@ -205,7 +205,7 @@
        "⌡           "
       ]
      },
-     "execution_count": 16,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -240,9 +240,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.4.3"
+   "version": "3.4.4"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }