Add directory structure to README, improves #10

The file structure is an essential part of the provided benefit and should be in the readme file.

README.md

@@ -32,6 +32,57 @@ $ conda install cookiecutter
 [![asciicast](https://asciinema.org/a/9bgl5qh17wlop4xyxu9n9wr02.png)](https://asciinema.org/a/9bgl5qh17wlop4xyxu9n9wr02)
 
 
+### The resulting directory structure
+------------
+
+The directory structure of your new project looks like this: 
+
+```
+├── LICENSE
+├── Makefile           <- Makefile with commands like `make data` or `make train`
+├── README.md          <- The top-level README for developers using this project.
+├── data
+│   ├── external       <- Data from third party sources.
+│   ├── interim        <- Intermediate data that has been transformed.
+│   ├── processed      <- The final, canonical data sets for modeling.
+│   └── raw            <- The original, immutable data dump.
+│
+├── docs               <- A default Sphinx project; see sphinx-doc.org for details
+│
+├── models             <- Trained and serialized models, model predictions, or model summaries
+│
+├── notebooks          <- Jupyter notebooks. Naming convention is a number (for ordering),
+│                         the creator's initials, and a short `-` delimited description, e.g.
+│                         `1.0-jqp-initial-data-exploration`.
+│
+├── references         <- Data dictionaries, manuals, and all other explanatory materials.
+│
+├── reports            <- Generated analysis as HTML, PDF, LaTeX, etc.
+│   └── figures        <- Generated graphics and figures to be used in reporting
+│
+├── requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.
+│                         generated with `pip freeze > requirements.txt`
+│
+├── src                <- Source code for use in this project.
+│   ├── __init__.py    <- Makes src a Python module
+│   │
+│   ├── data           <- Scripts to download or generate data
+│   │   └── make_dataset.py
+│   │
+│   ├── features       <- Scripts to turn raw data into features for modeling
+│   │   └── build_features.py
+│   │
+│   ├── models         <- Scripts to train models and then use trained models to make
+│   │   │                 predictions
+│   │   ├── predict_model.py
+│   │   └── train_model.py
+│   │
+│   └── visualization  <- Scripts to create exploratory and results oriented visualizations
+│       └── visualize.py
+│
+└── tox.ini            <- tox file with settings for running tox; see tox.testrun.org
+```
+
 ## Contributing
 
 We welcome contributions! [See the docs for guidelines](https://drivendata.github.io/cookiecutter-data-science/#contributing).