googleanalytics

Running the code

1. Clone this repo

git clone git@github.com:MichiganDataScienceTeam/googleanalytics.git

If you don't have an SSH key set up on Github, the above will not work. As a temporary solution, use the command below.

git clone https://github.com/MichiganDataScienceTeam/googleanalytics.git

2. Download the data from Google Drive and place it in ./data

3. Unzip the data and make sure they have read permissions

cd data
unzip train.csv.zip
unzip test.csv.zip
unzip sample_submission.csv.zip
chmod +r train.csv test.csv sample_submission.csv
cd ..

4. Create a virtualenv named env so that you can prevent version conflicts (this will likely solve any package installation issues you have.)

sudo pip install virtualenv
python -m virtualenv env

5. Activate/go into the virtualenv

source env/bin/activate

6. Install the required packages.

pip install -r requirements.txt

7. Process the train/val split.

python split_train_valid.py

8. Make sure the dataset is in the correct place and run the exploration code. Note: removing the --debug flag will cause the full dataset to be loaded, which may take a long time on your machine.

python dataset.py --debug
python explore.py --debug

Contributing

1. Create an account on Github and add an SSH key to your account
2. Ask @stroud on slack to join the MDST Organization
3. Assign yourself to an issue
4. Create a branch and write your code
5. Submit a pull request when you are done!