FAQ: How to use tsfresh with windows (blue-yonder#191)

* Added FAQ - how to use tsfresh with windows.

* Some reformatting.

* Some more reformatting.

* Some more reformatting.

* Typos.

docs/text/faq.rst

@@ -3,16 +3,31 @@ FAQ
 
 
     1. **Does tsfresh support different time series lengths?**
+
        Yes, it supports different time series lengths. However, some feature calculators can demand a minimal length
        of the time series. If a shorter time series is passed to the calculator, a NaN is returned for those
        features.
 
 
 
     2. **Is it possible to extract features from rolling/shifted time series?**
+
        Yes, the :func:`tsfresh.dataframe_functions.roll_time_series` function allows to conviniently create a rolled
        time series datframe from your data. You just have to transform your data into one of the supported tsfresh
        :ref:`data-formats-label`.
        Then, the :func:`tsfresh.dataframe_functions.roll_time_series` give you a DataFrame with the rolled time series,
        that you can pass to tsfresh.
        On the following page you can find a detailed description: :ref:`rolling-label`.
+
+
+    3. **How can I use tsfresh with windows?**
+
+       We recommend to use `Anaconda <https://www.continuum.io/downloads#windows>`_. After installing, open the
+       Anaconda Prompt, create an environment and set up tsfresh:
+       ::
+           conda create -n ENV_NAME python=VERSION
+           conda install -n ENV_NAME pip requests numpy pandas scipy statsmodels patsy scikit-learn future six tqdm
+           activate ENV_NAME
+           pip install tsfresh
+
+       Please be aware that we're using multiprocessing, which can be `problematic <http://stackoverflow.com/questions/18204782/runtimeerror-on-windows-trying-python-multiprocessing>`_.