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This repository contains notebook + code for DataCamp community post on groupbys, split-apply-combine and pandas.

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community-groupby

This repository contains notebook + code for DataCamp community post on groupbys, split-apply-combine and pandas.

Getting set up

Clone this repository

git clone https://github.com/datacamp/community-groupby

If you do not already have the Anaconda distribution, go get it (n.b., you can also do this w/out Anaconda using pip to install the required packages, however Anaconda is great for Data Science and I encourage you to use it).

Navigate to the relevant directory community-groupby and install required packages in a new conda environment:

conda env create -f environment.yml

This will create a new environment called group-by-pandas-netflix. To activate the environment, execute

source activate group-by-pandas-netflix

Then open the notebook split-apply-combine-netflix-data.ipynb and execute the code.

Code

The code in this repository is released under the MIT license. Read more at the Open Source Initiative. All text remains the Intellectual Property of DataCamp. If you wish to reuse, adapt or remix, get in touch with me at hugo at datacamp com to request permission.

Data

Data is from data.world and Chase Willden.

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This repository contains notebook + code for DataCamp community post on groupbys, split-apply-combine and pandas.

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  • Jupyter Notebook 100.0%