Provides instant access to many datasets right from Python (in pandas DataFrame structure).

The idea is simple. There are various datasets available out there, but they are scattered in different places over the web. Is there a quick way (in Python) to access them instantly without going through the hassle of searching, downloading, and reading ... etc? PyDataset tries to address that question :)

Start with importing data():

from pydataset import data

• To load a dataset:

titanic = data('titanic')

• To display the documentation of a dataset:

data('titanic', show_doc=True)

• To see the available datasets:

data()

That's it. See more examples.

In R, there is a very easy and immediate way to access multiple statistical datasets, in almost no effort. All it takes is one line > data(dataset_name). This makes the life easier for quick prototyping and testing. Well, I am jealous that Python does not have a similar functionality. Thus, the aim of pydataset is to fill that gap.

Currently, pydataset has about 757 (mostly numerical-based) datasets, that are based on RDatasets. In the future, I plan to scale it to include a larger set of datasets. For example,

1. include textual data for NLP-related tasks, and
2. allow adding a new dataset to the in-module repository.

$ pip install pydataset

• $ pip uninstall pydataset
• $ rm -rf $HOME/.pydataset

0.2.0

• Add search dataset by name similarity.
• Example:

>>> data('heat')
Did you mean:
Wheat, heart, Heating, Yeast, eidat, badhealth, deaths, agefat, hla, heptathlon, azt

0.1.1

• Fix: add support to Windows and fix filepaths, issue #1

• pandas

• Tested on OSX and Linux (debian).
• Supports both Python 2 (2.7.11) and Python 3 (3.5.1).

• add textual datasets (e.g. NLTK stuff).
• add samples generators.

• RDatasets: R's datasets collection.