https://github.com/bcongdon/pyvethirtyeight

:us: Python wrapper for Fivethirtyeight's Election Forecasts
https://github.com/bcongdon/pyvethirtyeight

fivethirtyeight forecast python-wrapper

Last synced: 4 months ago
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:us: Python wrapper for Fivethirtyeight's Election Forecasts

• Host: GitHub
• URL: https://github.com/bcongdon/pyvethirtyeight
• Owner: bcongdon
• License: mit
• Created: 2016-10-09T19:47:51.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2016-10-22T23:23:32.000Z (over 8 years ago)
• Last Synced: 2025-01-17T07:41:38.826Z (5 months ago)
• Topics: fivethirtyeight, forecast, python-wrapper
• Language: Python
• Homepage:
• Size: 9.77 KB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# PyveThirtyEight

> A Python wrapper for the 2016 [FiveThirtyEight](projects.fivethirtyeight.com/2016-election-forecast/) Presidential Election Forecast 

[![PyPI version](https://badge.fury.io/py/pyvethirtyeight.svg)](https://badge.fury.io/py/pyvethirtyeight)

[![Build Status](https://travis-ci.org/bcongdon/pyvethirtyeight.svg?branch=master)](https://travis-ci.org/bcongdon/pyvethirtyeight)

## Installation

```

pip install pyvethirtyeight

```

## Usage

```python

from pyvethirtyeight import President, Senate

# Presidential Election Forecasts

f = President()

# Latest Forecasts (Unordered)

latest = f.latest_forecasts()

latest[0].party # 'D'

# Current Leader (returns Forecast of latest leader)

leader = f.current_leader()

print(leader.models['plus']['winprob']) # 83.99

# Current Leader by Model

leader = f.current_leader(model='now')

print(leader.models['now']['winprob']) # 90.4

# All Forecasts

all_forecasts = f.all_forecasts()

# Same methods also work with Senate predictions

s = Senate()

print(s.latest_forecasts()[0].models['polls']['winprob']) # 67.33596

```

#### The Forecast Object

A `Forecast` is the prediction of the FiveThirtyEight model for a particular candidate at a particular moment in time

A `Forecast` has keys:

	- date (datetime) -> Forecast date

	- party (str) -> Candidate's party initial

	- candidate (str) -> Candidate's name

	- models (Dict) -> Dict of model predictions associated with candidate