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https://github.com/datacamp/community-hierarchical-indices

This repository contains notebook + code for DataCamp community post on hierarchical indices, groupby, split-apply-combine and pandas.
https://github.com/datacamp/community-hierarchical-indices

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

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# community-hierarchical-indices
This repository contains notebook + code for DataCamp community post on hierarchical indices, groupby, split-apply-combine and pandas.

## Getting set up

Clone this repository

```
git clone https://github.com/datacamp/community-hierarchical-indices
```

If you do not already have the [Anaconda distribution](https://www.anaconda.com/download/), 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-hierarchical-indices` and install required packages in a new conda environment:

```
conda env create -f environment.yml
```

This will create a new environment called hierarchical-indices-pandas. To activate the environment, execute

```
source activate hierarchical-indices
```

Then open the notebook `hierarchical_indices_multiple_groupbys_and_pandas.ipynb` and execute the code.

### Code
The code in this repository is released under the [MIT license](LICENSE). Read more at the [Open Source Initiative](https://opensource.org/licenses/MIT). 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.