opendatasets 0.1.14

A curated collection of datasets for data analysis & machine learning, downloadable with a single Python command

opendatasets

opendatasets is a Python library for downloading datasets from online sources like Kaggle and Google Drive using a simple Python command.

Installation

Install the library using pip:

pip install opendatasets --upgrade

Usage - Downloading a dataset

Datasets can be downloaded within a Jupyter notebook or Python script using the opendatasets.download helper function. Here's some sample code for downloading the US Elections Dataset:

import opendatasets as od
dataset_url = 'https://www.kaggle.com/tunguz/us-elections-dataset'
od.download('https://www.kaggle.com/tunguz/us-elections-dataset')

Kaggle Credentials

opendatasets uses the Kaggle Official API for donwloading dataset from Kaggle. Follow these steps to find your API credentials:

1. Sign in to https://kaggle.com/, then click on your profile picture on the top right and select "My Account" from the menu.

2. Scroll down to the "API" section and click "Create New API Token". This will download a file kaggle.json with the following contents:

{"username":"YOUR_KAGGLE_USERNAME","key":"YOUR_KAGGLE_KEY"}

3. When you run opendatsets.download, you will be asked to enter your username & Kaggle API, which you can get from the file downloaded in step 2.

Note that you need to download the kaggle.json file only once.

Some interesting datasets

You can find interesting datasets on Kaggle: https://www.kaggle.com/datasets

You can also create a new dataset on Kaggle by uploading a CSV file here: https://www.kaggle.com/datasets?new=true (make sure to keep your dataset public, otherwise it will not be downloadable)

• Video Games sales: https://www.kaggle.com/gregorut/videogamesales
• World University Rankings: https://www.kaggle.com/mylesoneill/world-university-rankings
• Netflix Tv shows and Movies: https://www.kaggle.com/shivamb/netflix-shows/notebooks
• StackOverflow Developer Survey: https://www.kaggle.com/stackoverflow/stack-overflow-2018-developer-survey
• Google Play Store Android Apps Data: https://www.kaggle.com/lava18/google-play-store-apps
• Indian Stock Market Data: https://www.kaggle.com/rohanrao/nifty50-stock-market-data
• Indian Air Quality: https://www.kaggle.com/rohanrao/air-quality-data-in-india
• Worldwide Covid-19 Cases: https://www.kaggle.com/imdevskp/corona-virus-report
• USA Covid-19 Cases: https://www.kaggle.com/sudalairajkumar/covid19-in-usa
• US Election Results (2012): https://www.kaggle.com/tunguz/us-elections-dataset
• US Stock Market: https://www.kaggle.com/borismarjanovic/price-volume-data-for-all-us-stocks-etfs/
• Crop production in India: https://www.kaggle.com/srinivas1/agricuture-crops-production-in-india
• Agricultural raw material prices: https://www.kaggle.com/kianwee/agricultural-raw-material-prices-19902020
• Agricultural land values: https://www.kaggle.com/jmullan/agricultural-land-values-19972017
• Digital payments in India: https://www.kaggle.com/lazycipher/upi-usage-statistics-aug16-to-feb20
• US Unemployment Rate Data: https://www.kaggle.com/jayrav13/unemployment-by-county-us
• India Road accident Data: https://community.data.gov.in/statistics-of-road-accidents-in-india/
• Data Science Jobs Data:
  • https://www.kaggle.com/sl6149/data-scientist-job-market-in-the-us
  • https://www.kaggle.com/jonatancr/data-science-jobs-around-the-world
  • https://www.kaggle.com/rkb0023/glassdoor-data-science-jobs
• Youtube Trending Videos: https://www.kaggle.com/datasnaek/youtube-new
• Asteroid Dataset: https://www.kaggle.com/sakhawat18/asteroid-dataset
• Solar flares Data: https://www.kaggle.com/khsamaha/solar-flares-rhessi
• F-1 Race Data: https://www.kaggle.com/cjgdev/formula-1-race-data-19502017
• Automobile Insurance: https://www.kaggle.com/aashishjhamtani/automobile-insurance
• PUBG video game matches: https://www.kaggle.com/skihikingkevin/pubg-match-deaths
• CounterStrike GO (video game)
  • https://www.kaggle.com/mateusdmachado/csgo-professional-matches
  • https://www.kaggle.com/skihikingkevin/csgo-matchmaking-damage
• Dota 2 (video game): https://www.kaggle.com/devinanzelmo/dota-2-matches
• Cricket One-Day Internationals Data: https://www.kaggle.com/jaykay12/odi-cricket-matches-19712017
• Cricket Indian Premier League Data: https://www.kaggle.com/nowke9/ipldata
• Basketball (NCAA): https://www.kaggle.com/ncaa/ncaa-basketball
• Basketball NBA Players Stats: https://www.kaggle.com/ncaa/ncaa-basketball
• Football datasets:
  • https://www.kaggle.com/martj42/international-football-results-from-1872-to-2017
  • https://www.kaggle.com/abecklas/fifa-world-cup
  • https://www.kaggle.com/egadharmawan/uefa-champion-league-final-all-season-19552019
• Hotel Booking Demand: https://www.kaggle.com/jessemostipak/hotel-booking-demand
• New York Airbnb listings: https://www.kaggle.com/dgomonov/new-york-city-airbnb-open-data

Other sources to look for datasets:

• UCI Machine Learning Repository
• awesome-public-datasets
• Google Dataset Search

If you use an external source other than Kaggle, you'll create a new dataset on Kaggle by uploading a CSV file here: https://www.kaggle.com/datasets?new=true (make sure to keep your dataset public, otherwise it will not be downloadable using opendatasets)

Curated Datasets

opendatasets also provides some curated datsets that you can download by passing the Dataset ID to opendatasets.download. Here's an example:

import opendatasets
opendatasets.download('stackoverflow-developer-survey-2020')

The following datasets are available for download.

Dataset ID	Description	Source
stackoverflow-developer-survey-2020	Stack Overflow Developer Survey 2020	Stack Overflow
owid-covid-19-latest	Covid-19 Stats by Our World in Data	Our World in Data
state-of-javascript-2016	State of Javascript Annual Survey 2016	StateOfJS
state-of-javascript-2017	State of Javascript Annual Survey 2017	StateOfJS
state-of-javascript-2018	State of Javascript Annual Survey 2018	StateOfJS
state-of-javascript-2019	State of Javascript Annual Survey 2019	StateOfJS
countries-languages-spoken	Languages Spoken in Different Countries	Infoplease

More datasets will be added soon..

Contributing

This is an open source project and we welcome contributions.

Local Development Setup

1. Clone the repository:

git clone https://github.com/JovianML/opendatasets.git

2. Setup the Python environment for development

conda create -n opendatasets python=3.5
conda activate opendatasets
pip install -r requirements.txt

3. Open up the project in VS code and make your changes. Make sure to install the Python Extension for VS Code and select the opendatasets conda environment.

Adding Datasets

TODO - more details will be added here later

This package is developed and mainted by the Jovian.ml team.