Merge pull request #2507 from nikhartman/nik/as_xarray

docs/examples/15_minutes_to_QCoDeS.ipynb

@@ -25,7 +25,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "An experimental setup comprises of many instruments. We call an experimental setup as \"station\". A station is connected to many instruments or devices. QCoDeS provides a way to interact with all these instruments to help users ",
+    "An experimental setup comprises of many instruments. We call an experimental setup as \"station\". A station is connected to many instruments or devices. QCoDeS provides a way to interact with all these instruments to help users \n",
     "the measurements and store the data in a database. To interact (read, write, trigger, etc) with the instruments, we have created a [library of drivers](http://qcodes.github.io/Qcodes/api/generated/qcodes.instrument_drivers.html) for commonly used ones. These drivers implement the most needed functionalities of the instruments. \n",
     "\n",
     "An \"Instrument\" can perform many functions. For example, on an oscilloscope instrument, we first set a correct trigger level and other parameters and then obtain a trace. In QCoDeS lingo, we call \"trigger_level\" and \"trace\" as `parameter` of this `instrument`. An instrument at any moment will have many such parameters which together define the state of the instrument, hence a parameter can be thought of as a state variable of the instrument. QCoDeS provides a method to set values of these parameters (set trigger level) and get the values from them (obtain a trace). By this way, we can interact with all the needed parameters of an instrument and are ready to set up a measurement. \n",
@@ -1243,6 +1243,30 @@
     "df.head()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Export data to xarray"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "It's also possible to export data stored within a QCoDeS database to an `xarray.DataArray`. This can be achieved via:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "xarray = dataset.to_xarray_dataarray_dict()['dmm_v1']\r\n",
+    "xarray.head()"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -1358,7 +1382,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.9"
+   "version": "3.7.9-final"
   },
   "toc": {
    "base_numbering": 1,

environment.yml

@@ -22,6 +22,7 @@ dependencies:
  - scipy
  - gitpython
  - pandas
+ - xarray
  - testpath>=0.4.4
  - tqdm
  - tabulate