<commit_before># Help
Chat with us via the orange icon on [beta.quiltdata.com](https://beta.quiltdata.com/).

# Overview
[Quilt](https://beta.quiltdata.com/) is a data package manager.
You can use data packages from the community, or publish packages for others to use.

`quilt` is the command-line client that builds, retrieves, and stores
packages. `quilt` works in conjunction with a server-side registry,
not covered in this document. `quilt` currently pushes to and pulls from
the registry at [beta.quiltdata.com](https://beta.quiltdata.com/). In the near
future users will be able to browse packages in the registry.

## Benefits
* Access data frames [5X to 20X faster](http://wesmckinney.com/blog/pandas-and-apache-arrow/).
Quilt stores data frames in high-efficiency, memory-mapped binary formats like HDF5.
* Version your data. Pull packages by version number or tag (incomplete feature).
* Publish data packages for the benefit of the community.
* Satisfy your data dependencies with one command, `quilt install dependency`.

# Known Issues
- `Python 3.6` - Install fails due to missing HDF5 dependencies. Try Python 3.5. For example if you're using Anaconda, create a 3.5 environment: `conda create -n ENV python=3.5`.

# Quick Start
1. Open Terminal
1. `$ pip install git+https://github.com/quiltdata/quilt.git` (install quilt)
1. `$ quilt install akarve/wine` (install a sample package)
1. `python` (fire up python)
1. You've got data frames
```
>>> from quilt.data.akarve import wine
>>> wine.quality.red # this is a pandas.DataFrame
```

# Tutorial

## Install `quilt`<commit_msg>pickle problems<commit_after># Help
Chat with us via the orange icon on [beta.quiltdata.com](https://beta.quiltdata.com/).

# Overview
[Quilt](https://beta.quiltdata.com/) is a data package manager.
You can use data packages from the community, or publish packages for others to use.

`quilt` is the command-line client that builds, retrieves, and stores
packages. `quilt` works in conjunction with a server-side registry,
not covered in this document. `quilt` currently pushes to and pulls from
the registry at [beta.quiltdata.com](https://beta.quiltdata.com/). In the near
future users will be able to browse packages in the registry.

## Benefits
* Access data frames [5X to 20X faster](http://wesmckinney.com/blog/pandas-and-apache-arrow/).
Quilt stores data frames in high-efficiency, memory-mapped binary formats like HDF5.
* Version your data. Pull packages by version number or tag (incomplete feature).
* Publish data packages for the benefit of the community.
* Satisfy your data dependencies with one command, `quilt install dependency`.

# Known Issues
- `Python 3.6` - Install fails due to missing HDF5 dependencies. Try Python 3.5. For example if you're using Anaconda, create a 3.5 environment: `conda create -n ENV python=3.5`.
-  `quilt/test/build.yml` relies on pickle and is therefore not compatible between Python 2 and Python 3.

# Quick Start
1. Open Terminal
1. `$ pip install git+https://github.com/quiltdata/quilt.git` (install quilt)
1. `$ quilt install akarve/wine` (install a sample package)
1. `python` (fire up python)
1. You've got data frames
```
>>> from quilt.data.akarve import wine
>>> wine.quality.red # this is a pandas.DataFrame
```

# Tutorial

## Install `quilt`
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