Rephrase two steps installing kernel in docs

docs/source/install/kernel_install.rst

@@ -1,75 +1,80 b''
 .. _kernel_install:
 
 Installing the IPython kernel
 =============================
 
 .. seealso::
 
    :ref:`Installing Jupyter <jupyter:install>`
      The IPython kernel is the Python execution backend for Jupyter.
 
 The Jupyter Notebook and other frontends automatically ensure that the IPython kernel is available.
 However, if you want to use a kernel with a different version of Python, or in a virtualenv or conda environment,
 you'll need to install that manually.
 
 Kernels for Python 2 and 3
 --------------------------
 
 If you're running Jupyter on Python 3, you can set up a Python 2 kernel like this::
 
     python2 -m pip install ipykernel
     python2 -m ipykernel install --user
 
 Or using conda, create a Python 2 environment::
 
     conda create -n ipykernel_py2 python=2 ipykernel
     source activate ipykernel_py2    # On Windows, remove the word 'source'
     python -m ipykernel install --user
 
 If you're running Jupyter on Python 2 and want to set up a Python 3 kernel,
 follow the same steps, replacing ``2`` with ``3``.
 
 The last command installs a :ref:`kernel spec <jupyterclient:kernelspecs>` file
 for the current python installation. Kernel spec files are JSON files, which
 can be viewed and changed with a normal text editor.
 
 .. _multiple_kernel_install:
 
 Kernels for different environments
 ----------------------------------
 
 If you want to have multiple IPython kernels for different virtualenvs or conda environments,
 you will need to specify unique names for the kernelspecs.
 
 For example, using conda environments:
 
 .. sourcecode:: bash
 
     source activate myenv
     python -m ipykernel install --user --name myenv --display-name "Python (myenv)"
     source activate other-env
     python -m ipykernel install --user --name other-env --display-name "Python (other-env)"
 
 The ``--name`` value is used by Jupyter internally. These commands will overwrite
 any existing kernel with the same name. ``--display-name`` is what you see in
 the notebook menus.
 
 Using virtualenv or conda envs, you can make your IPython kernel in one env available to Jupyter in a different env. To do so, run ipykernel install from the kernel's env, with --prefix pointing to the Jupyter env:
 
 .. sourcecode:: bash
 
     /path/to/kernel/env/bin/python -m ipykernel install --prefix=/path/to/jupyter/env --name 'python-my-env'
 
 Note that this command will create new configuration for kernel in one of it's prefered location (see ``jupyter --paths`` command for more details):
 
 * system-wide (e.g. /usr/local/share),
 * in Jupyter's env (sys.prefix/share),
 * per-user (~/.local/share or ~/Library/share)
 
-In case where you want to edit generated kernelspec configuration before installing it you can do the same with two steps approach. You can create configuration in temporary location and install it in Jupyter (copy configuration files) with:
+If you want to edit the kernelspec before installing it, you can do so in two steps.
+First, ask IPython to write its spec to a temporary location:
 
 .. sourcecode:: bash
 
     ipython kernel install --prefix /tmp
-    jupyter kernelspec install /tmp/share/jupyter/kernels/python3
 
+edit the files in /tmp/share/jupyter/kernels/python3 to your liking, then when you are ready, tell Jupyter to install it (this will copy the files into a place Jupyter will look):
+
+.. sourcecode:: bash
+
+    jupyter kernelspec install /tmp/share/jupyter/kernels/python3