w102060018w / cb-data-science-workshops

Material for datascience workshops at Cardinalblue

cb-data-science-workshops

Material for datascience workshops at Cardinalblue

Requirements

• install Anaconda from their website
• create a new environment, following their documentation

conda create --name py3env python=3
source activate py3env

• install required packages with conda: numpy, pandas, matplotlib, seaborn, xgboost

conda install numpy pandas matplotlib seaborn ipykernel scikit-learn
conda install -c conda-forge xgboost

• install ggplot package as follows (there is a currently conflict with pandas)

pip install git+git://github.com/yhat/ggpy.git@9d00182343eccca6486beabd256e8c89fb0c59e8 --no-cache

• download the data either from Kaggle or directly from our Drive folder, and put it in ./kaggle-zillow/input/
• add your Python environment to the list of Jupyter kernels

python -m ipykernel install --user

• go to the notebook folder, and launch the notebook!

cd kaggle-zillow/notebooks/
jupyter notebook

Sources:

• This Kaggle kernel, this one, Pandas documentation